Miracle-dz/UniFAR-FTUs huggingface dataset:
Building Large Chinese Corpus for Spoken Dialogue Research in Specific Domains

Corpus is a valuable resource for information retrieval and data-driven natural language processing systems,especially for spoken dialogue research in specific domains. However,there is little non-English corpora, particular for ones in Chinese. Spoken by the nation with the largest population in the world, Chinese become increasingly prevalent and popular among millions of people worldwide. In this paper, we build a large-scale and high-quality Chinese corpus, called CSDC (Chinese Spoken Dialogue Corpus). It contains five domains and more than 140 thousand dialogues in all. Each sentence in this corpus is annotated with slot information additionally compared to other corpora. To our best knowledge, this is the largest Chinese spoken dialogue corpus, as well as the first one with slot information. With this corpus, we proposed a method and did a well-designed experiment. The indicative result is reported at last.
Sparse Quadratic Logistic Regression in Sub-quadratic Time

We consider support recovery in the quadratic logistic regression setting - where the target depends on both p linear terms $x_i$ and up to $p^2$ quadratic terms $x_i x_j$. Quadratic terms enable prediction/modeling of higher-order effects between features and the target, but when incorporated naively may involve solving a very large regression problem. We consider the sparse case, where at most $s$ terms (linear or quadratic) are non-zero, and provide a new faster algorithm. It involves (a) identifying the weak support (i.e. all relevant variables) and (b) standard logistic regression optimization only on these chosen variables. The first step relies on a novel insight about correlation tests in the presence of non-linearity, and takes $O(pn)$ time for $n$ samples - giving potentially huge computational gains over the naive approach. Motivated by insights from the boolean case, we propose a non-linear correlation test for non-binary finite support case that involves hashing a variable and then correlating with the output variable. We also provide experimental results to demonstrate the effectiveness of our methods.
Dynamic power management for long-term energy neutral operation of solar energy harvesting systems

In this work we consider a real-world environmental monitoring scenario that requires uninterrupted system operation over time periods on the order of multiple years. To achieve this goal, we propose a novel approach to dynamically adjust the system's performance level such that energy neutral operation, and thus long-term uninterrupted operation can be achieved. We first consider the annual dynamics of the energy source to design an appropriate power subsystem (i.e., solar panel size and energy store capacity), and then dynamically compute the long-term sustainable performance level at runtime. We show through trace-driven simulations using eleven years of real-world data that our approach outperforms existing predictive, e.g., EWMA, WCMA, and reactive, e.g., ENO-MAX, approaches in terms of average performance level by up to 177%, while reducing duty-cycle variance by up to three orders of magnitude. We further demonstrate the benefits of the dynamic power management scheme using a wireless sensor system deployed for environmental monitoring in a remote, high-alpine environment as a case study. A performance evaluation over two years reveals that the dynamic power management scheme achieves a two-fold improvement in system utility when compared to only applying appropriate capacity planning.
Adaptive learning control design for robotic manipulators driven by permanent magnet synchronous motors

On the basis of the ideas recently presented in Tomei and Verrelli (Tomei, P., and Verrelli, C.M. (2010), ‘Learning Control for Induction Motor Servo Drives with Uncertain Rotor Resistance’, International Journal of Control, 83, 1515–1528) and Marino et al. (Marino, R., Tomei, P., and Verrelli, C.M. (2011), ‘Robust Adaptive Learning Control for Nonlinear Systems with Extended Matching Unstructured Uncertainties’, International Journal of Robust and Nonlinear Control, Early View, doi: 10.1002/rnc.1720), we briefly show how the adaptive learning control design proposed in Liuzzo and Tomei (Liuzzo, S., and Tomei, P. (2009), Global Adaptive Learning Control of Robotic Manipulators by Output Error Feedback, International Journal of Adaptive Control and Signal Processing, 23, 97–109) can be extended to robotic manipulators driven by nonsalient-pole (surface) permanent magnet synchronous motors. Unstructured uncertain dynamics (that is no parameterisation is available for the uncertainties) of the rigid robot with rotational joints are considered as well as uncertainties in stator resistances of the synchronous motors are taken into account. Two solutions with clear stability proofs are presented: a global decentralised control via state feedback and a semi-global control via output feedback. Output tracking of known periodic reference signals and learning of corresponding uncertain input reference signals are achieved. Available results in the literature are thus improved since no simplification concerning negligible electrical motor dynamics is used.
Taz1p and Teb1p, two telobox proteins in Schizosaccharomyces pombe, recognize different telomere-related DNA sequences.

Band shift assays were used to study proteins from the fission yeast that bind double-stranded telomeric repeat sequences. We also examine general DNA binding properties of the telobox domain, which characterizes telomere-binding proteins from a range of species. We demonstrate that Taz1p has a high affinity for the fission yeast telomeric repeat, consistent with genetic results implicating this protein in telomere maintenance. A second Schizosaccharomyces pombe telobox protein, Teb1p, is shown to bind with high affinity to the vertebrate repeat and with low affinity to the fission yeast telomeric DNA. When tested on G-rich single-stranded telomeric DNA, all these proteins bind with very low affinity, much like the human telomere-binding protein TRF1. Recombinant proteins containing just the telobox domains reproduce the specificity of binding demonstrated for the corresponding full-length proteins, indicating that the telobox domain is indeed responsible for specific DNA recognition. The presence of possible Teb1p-binding sites upstream of many genes suggests a role for this protein as a general transcription factor. Finally, band shift experiments with whole cell extracts from wild-type and taz1 (-)strains suggest that in addition to Taz1p, S.pombe has another major telomere-binding activity.
Architecture and characterization of a calibrator for PMUs operating in power distribution systems

In recent years, the Phasor Measurement Unit (PMU) technology is rapidly evolving towards the potential deployment also in power distribution systems (DSs). In general, this specific field of applications requires PMUs whose accuracy levels are beyond those required by the IEEE Std. C37.118. Additionally, there is the need to define the architecture of an associated calibration system capable to assess the metrological performances of these devices. In this paper, we first analyse the impact of the uncertainties (in term of phase and magnitude) introduced by arbitrary PMUs on a state estimation (SE) process performed on the IEEE 13-bus distribution test feeder. The outcomes of this analysis are used to infer the most stringent steady-state performances of PMUs for DSs monitoring and, consequently, to define the requirements and the hardware architecture of a PMU calibrator presently developed at the Author's laboratories. A preliminary metrological characterization of the proposed calibrator is presented in the paper.
I-Os in the Vanguard of Big Data Analytics and Privacy

In this response to Guzzo, Fink, King, Tonidandel, and Landis (2015), we suggest industrial–organizational (I-O) psychologists join business analysts, data scientists, statisticians, mathematicians, and economists in creating the vanguard of expertise as we acclimate to the reality of analytics in the world of big data. We enthusiastically accept their invitation to share our perspective that extends the discussion in three key areas of the focal article—that is, big data sources, logistic and analytic challenges, and data privacy and informed consent on a global scale. In the subsequent sections, we share our thoughts on these critical elements for advancing I-O psychology's role in leveraging and adding value from big data.
Variance and Sample Size Calculations in Quality‐of‐Life‐Adjusted Survival Analysis (Q‐TWiST)

Summary. The Quality‐Adjusted Time Without Symptoms or Toxicity (Q‐TWiST) statistic previously introduced by Glasziou, Simes and Gelber (1990, Statistics in Medicine9, 1259–1276) combines toxicity, disease‐free survival, and overall survival information in assessing the impact of treatments on the lives of patients. This methodology has received positive reviews from clinicians as intuitive and useful, but to date, the variance of this statistic has remained unspecified. We review aspects of the Q‐TWiST method for analyzing clinical trial data, extend the method to accommodate multiple treatment arms, and provide closed‐form asymptotic variance formulas. We also provide a framework for designing Q‐TWiST clinical trials with sample sizes determined using the derived asymptotic variance formulas. Trials currently collecting quality of life data did not have the benefit of these sample size calculation techniques in designing their studies.
Measurement of the psychosis continuum: Modelling the frequency and distress of subclinical psychotic experiences

Objective: Dimensional models of psychosis symptom frequency at clinical levels are representative of symptom dimensionality that is inclusive of distress. However, factor models of psychotic-like experiences, or subclinical symptomatology, in the general population have only ever been estimated using information on the frequency of occurrence. To ascertain whether dimensional representations of psychosis at subclinical levels are reflective of clinical manifestations of psychosis, factor models must utilise data that permits the measurement of both frequency and distress of psychosis experiences. Method: Psychotic-like experiences were assessed in a nonclinical sample (N = 462) using the 20 positive items from the CAPE42, which is a self-report questionnaire of psychotic experiences. For each item of the CAPE the frequency and distress ratings were recoded to form composite scores. Seven factor analytic models were specified and tested using confirmatory factor analysis. Results: The five-factor model of Wigman et al. (hallucinations, paranoia, grandiosity, delusions and paranormal beliefs factors) represented the best fitting model for both frequency and composite data. Conclusions: The findings constitute further evidence for a continuum of psychosis within the general population. Future analyses, aimed at delineating the dimensionality of psychosis, must advance towards the inclusion of distress as a central and necessary adjunct to measurement.
Psychometric properties of the Turkish version of the Leahy Emotional Schema Scale-II -

Objective: The emotional schema theory (EST) reflects two styles of coping with emotions, i.e. normalizing, or pathological. These emotional schemas may be evaluated by the Leahy Emotional Schemas Scale (LESS). To ease the application of the LESS, a shortened version of it was introduced in 2012. Nevertheless, the psychometric properties of this new version has not been published so far. This study aims to evaluate the psychometric properties of the LESS-II in a sample consisting of clinically depressed outpatients and healthy controls. Methods: A total of 457 participants were recruited for this study. Only patients diagnosed with major depressive disorder, or participants with no axis I disorder were eligible to take part in the study. The participants completed the LESS, the Metacognitions Questionnaire-30, the Beliefs about Emotions Scale and the interviewer used the Montgomery Asberg Depression Rating Scale to determine the severity of the depression. Results: This study has shown that the LESS-II has good internal consistency, is a reliable and valid tool to assess emotional schemas in a clinically depressed patient population, has strong and significant correlations with the LESS, and to a great extent, is able to differentiate between clinically depressed patients and healthy controls. Discussion: The LESS-II has been shown to be a reliable and valid tool for the assessment of emotional schemas in a Turkish clinical population, and the findings provide further support for the evidence base of the clinical application of the EST.
Rifampin Resistance Mutations Are Associated with Broad Chemical Remodeling of Mycobacterium tuberculosis*

Global control of tuberculosis has become increasingly complicated with the emergence of multidrug-resistant strains of Mycobacterium tuberculosis. First-line treatments are anchored by two antibiotics, rifampin and isoniazid. Most rifampin resistance occurs through the acquisition of missense mutations in the rifampin resistance-determining region, an 81-base pair region encoding the rifampin binding site on the β subunit of RNA polymerase (rpoB). Although these mutations confer a survival advantage in the presence of rifampin, they may alter the normal process of transcription, thereby imposing significant fitness costs. Because the downstream biochemical consequences of the rpoB mutations are unknown, we used an organism-wide screen to identify the number and types of lipids changed after rpoB mutation. A new mass spectrometry-based profiling platform systematically compared ∼10,000 cell wall lipids in a panel of rifampin-resistant mutants within two genetically distinct strains, CDC1551and W-Beijing. This unbiased lipidomic survey detected quantitative alterations (>2-fold, p < 0.05) in more than 100 lipids in each mutant. By focusing on molecular events that change among most mutants and in both genetic backgrounds, we found that rifampin resistance mutations lead to altered concentrations of mycobactin siderophores and acylated sulfoglycolipids. These findings validate a new organism-wide lipidomic analysis platform for drug-resistant mycobacteria and provide direct evidence for characteristic remodeling of cell wall lipids in rifampin-resistant strains of M. tuberculosis. The specific links between rifampin resistance and named lipid factors provide diagnostic and therapeutic targets that may be exploited to address the problem of drug resistance.
Cultural Differences in the Relationship between Intrusions and Trauma Narratives Using the Trauma Film Paradigm

Two studies explored the influence of culture on the relationship between British and East Asian adults’ autobiographical remembering of trauma film material and associated intrusions. Participants were shown aversive film clips to elicit intrusive images. Then participants provided a post-film narrative of the film content (only Study 1). In both studies, participants reported intrusive images for the film in an intrusion diary during the week after viewing. On returning the diary, participants provided a narrative of the film (delayed). The trauma film narratives were scored for memory-content variables. It was found that for British participants, higher levels of autonomous orientation (i.e. expressions of autonomy and self-determination) and self-focus in the delayed narratives were correlated significantly with fewer intrusions. For the East Asian group, lower levels of autonomous orientation and greater focus on others were correlated significantly with fewer intrusions. Additionally, Study 2 found that by removing the post-film narrative task there was a significant increase in the number of intrusions relative to Study 1, suggesting that the opportunity to develop a narrative resulted in fewer intrusions. These findings suggest that the greater the integration and contextualization of the trauma memory, and the more the trauma memory reflects culturally appropriate remembering, the fewer the intrusions.
Comparative usability and performance evaluation of surgeon interfaces in laser phonomicrosurgery

Robot-assisted surgical procedures, such as Laser Phonomicrosurgery (LP), suffer from susceptibility to variation in surgeon skill and equipment characteristics. Ergonomic and human-centered approaches acquire increased importance in the design of surgeon-machine interfaces. This paper proposes a protocol for comparative evaluation of surgeon-machine interfaces based on two criteria: (i) the subjective evaluation of their usability using questionnaires, and (ii) the objective evaluation of their performance using an imaging-based feature extraction method. Two interfaces in LP, the traditional (“AcuBlade”) interface and the novel (“Virtual Scalpel”) interface, were evaluated to demonstrate the effectiveness of the proposed scheme. A series of experimental trials were conducted using the interfaces in surgery-like tasks in a controlled environment. The subjective evaluation pointed to the superiority of the Virtual Scalpel interface (score: 83.06) in terms of confidence and ease of use, and learnability, over the AcuBlade interface (score: 65.56). The objective evaluation showed the Virtual Scalpel interface having an overall score (55.96) significantly superior to the AcuBlade (51.37). It is thus shown that the multidimensional evaluation approach allowed to clearly distinguish between levels of perceived usability and effective performance of surgeon-machine interfaces from a user-centered perspective.
Analysis of Cluttered Scenes Using an Elastic Matching Approach for Stereo Images

We present a system for the automatic interpretation of cluttered scenes containing multiple partly occluded objects in front of unknown, complex backgrounds. The system is based on an extended elastic graph matching algorithm that allows the explicit modeling of partial occlusions. Our approach extends an earlier system in two ways. First, we use elastic graph matching in stereo image pairs to increase matching robustness and disambiguate occlusion relations. Second, we use richer feature descriptions in the object models by integrating shape and texture with color features. We demonstrate that the combination of both extensions substantially increases recognition performance. The system learns about new objects in a simple one-shot learning approach. Despite the lack of statistical information in the object models and the lack of an explicit background model, our system performs surprisingly well for this very difficult task. Our results underscore the advantages of view-based feature constellation representations for difficult object recognition problems.
Cost-effectiveness of nutritional counseling for obese patients and patients at risk of ischemic heart disease

Objectives: Obesity and dyslipidemia are risk factors for ischemic heart disease, and prevention and treatment in primary care can reduce these risks. The objective of this cost-effectiveness analysis was to compare the costs and effects (in terms of life years gained) of providing nutritional counseling by a general practitioner (GP) or a dietician. Methods: A total of 60 GPs, who accepted to participate, were randomized either to give nutritional counseling or to refer patients to a dietician for counseling. The life years gained was estimated using a Cox regression model. Costs were estimated on the basis of registered use of time (dieticians) or agreed salaries (GPs). Results: The effect of nutritional counseling comparing GPs and dieticians is greatest when counseling is performed by a GP—0.0919 years versus 0.0274 years. These effects appear to be moderate, but they are significant. It is also proven that the GP group was the most cost-effective—the cost of gaining 1 extra life year was estimated to be 8,213 DKK compared with the dietician group, for which the incremental cost-effectiveness ratio was estimated to be 59,987 DKK. Conclusions: The effects were moderate, but other studies of other patient groups and interventions report effects within the same magnitude. The GP group was the most cost-effective, but it must be concluded that both counseling strategies were relatively cost-effective. Even though the cost of gaining an extra life year was estimated to be 59,987 DKK in the dietician group, this might be an acceptable price.
Evaluating third-party Bad Neighborhood blacklists for Spam detection

The distribution of malicious hosts over the IP address space is far from being uniform. In fact, malicious hosts tend to be concentrated in certain portions of the IP address space, forming the so-called Bad Neighborhoods. This phenomenon has been previously exploited to filter Spam by means of Bad Neighborhood blacklists. In this paper, we evaluate how much a network administrator can rely upon different Bad Neighborhood blacklists generated by third-party sources to fight Spam. One could expect that Bad Neighborhood blacklists generated from different sources contain, to a varying degree, disjoint sets of entries. Therefore, we investigate (i) how specific a blacklist is to its source, and (ii) whether different blacklists can be interchangeably used to protect a target from Spam. We analyze five Bad Neighborhood blacklists generated from real-world measurements and study their effectiveness in protecting three production mail servers from Spam. Our findings lead to several operational considerations on how a network administrator could best benefit from Bad Neighborhood-based Spam filtering.
Hybrid Collaboration Recommendation from Bibliometric Data - the Medical Technology Perspective

Medical product development is becoming more and more complex and requires highly-specialized and interdisciplinary collaborations. Their success relies essentially on the selection of suitable partners. However, how to find suitable partners and how to match capabilities of an unknown partner with complex project requirements? Suitability must at least be judged with respect to professional competencies, collaboration capability and project-specific requirements — none of which are easily determined. So, partner selection is mostly dominated by regional proximity or even coincidence. This is a typical scenario for recommender systems. Therefore, we aim at discovering the unexploited potential of collaboration partners by proposing a novel recommendation approach that merges trust with health-sensitive semantic information. This hybrid approach should help to identify collaborators matching complex project requirements faster, better and more holistically.
ArchTrace: Policy-Based Support for Managing Evolving Architecture-to-Implementation Traceability Links

Traditional techniques of traceability detection and management are not equipped to handle evolution. This is a problem for the field of software architecture, where it is critical to keep synchronized an evolving conceptual architecture with its realization in an evolving code base. ArchTrace is a new tool that addresses this problem through a policy-based infrastructure for automatically updating traceability links every time an architecture or its code base evolves. ArchTrace is pluggable, allowing developers to choose a set of traceability management policies that best match their situational needs and working styles. We discuss ArchTrace, its conceptual basis, its implementation, and our evaluation of its strengths and weaknesses in a retrospective analysis of data collected from a 20 month period of development of Odyssey, a large-scale software development environment. Results are promising: with respect to the ideal set of traceability links, the policies applied resulted in 95% precision at 89% recall