Miracle-dz/UniFAR-FTUs huggingface dataset:
Parental effects in ecology and evolution: mechanisms, processes and implications

As is the case with any metaphor, parental effects mean different things to different biologists—from developmental induction of novel phenotypic variation to an evolved adaptation, and from epigenetic transference of essential developmental resources to a stage of inheritance and ecological succession. Such a diversity of perspectives illustrates the composite nature of parental effects that, depending on the stage of their expression and whether they are considered a pattern or a process, combine the elements of developmental induction, homeostasis, natural selection, epigenetic inheritance and historical persistence. Here, we suggest that by emphasizing the complexity of causes and influences in developmental systems and by making explicit the links between development, natural selection and inheritance, the study of parental effects enables deeper understanding of developmental dynamics of life cycles and provides a unique opportunity to explicitly integrate development and evolution. We highlight these perspectives by placing parental effects in a wider evolutionary framework and suggest that far from being only an evolved static outcome of natural selection, a distinct channel of transmission between parents and offspring, or a statistical abstraction, parental effects on development enable evolution by natural selection by reliably transferring developmental resources needed to reconstruct, maintain and modify genetically inherited components of the phenotype. The view of parental effects as an essential and dynamic part of an evolutionary continuum unifies mechanisms behind the origination, modification and historical persistence of organismal form and function, and thus brings us closer to a more realistic understanding of life's complexity and diversity.
Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables—Part II: Case-Study

The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.
Exact conditional inference on h-sample problems for categorical data using algebraic algorithms

Riassunto: Nella recente letteratura il problema del calcolo del p-value nell’inferenza condizionata è stato trattato diffusamente e sono state fornite diverse soluzioni computazionali. In questo lavoro si propone l’utilizzo di un algoritmo algebrico per il calcolo approssimato del p-value esatto per test di uguaglianza tra distribuzioni categoriche. Tale algoritmo è basato sulla teoria dell’algebra computazionale ed è implementato usando un metodo MCMC.
Probabilistic ranking over relations

Probabilistic top-k ranking queries have been extensively studied due to the fact that data obtained can be uncertain in many real applications. A probabilistic top-k ranking query ranks objects by the interplay of score and probability, with an implicit assumption that both scores based on which objects are ranked and probabilities of the existence of the objects are stored in the same relation. We observe that in general scores and probabilities are highly possible to be stored in different relations, for example, in column-oriented DBMSs and in data warehouses. In this paper we study probabilistic top-k ranking queries when scores and probabilities are stored in different relations. We focus on reducing the join cost in probabilistic top-k ranking. We investigate two probabilistic score functions, discuss the upper/lower bounds in random access and sequential access, and provide insights on the advantages and disadvantages of random/sequential access in terms of upper/lower bounds. We also propose random, sequential, and hybrid algorithms to conduct probabilistic top-k ranking. We conducted extensive performance studies using real and synthetic datasets, and report our findings in this paper.
Multimodal analysis of verbal and nonverbal behaviour on the example of clinical depression

Clinical depression is a common mood disorder that may last for long periods, vary in severity, and could impair an individual’s ability to cope with daily life. Depression affects 350 million people worldwide and is therefore considered a burden not only on a personal and social level, but also on an economic one. Depression is the fourth most significant cause of suffering and disability worldwide and it is predicted to be the leading cause in 2020. Although treatment of depression disorders has proven to be effective in most cases, misdiagnosing depressed patients is a common barrier. Not only because depression manifests itself in different ways, but also because clinical interviews and self-reported history are currently the only ways of diagnosis, which risks a range of subjective biases either from the patient report or the clinical judgment. While automatic affective state recognition has become an active research area in the past decade, methods for mood disorder detection, such as depression, are still in their infancy. Using the advancements of affective sensing techniques, the long-term goal is to develop an objective multimodal system that supports clinicians during the diagnosis and monitoring of clinical depression. This dissertation aims to investigate the most promising characteristics of depression that can be “heard” and “seen” by a computer system for the task of detecting depression objectively. Using audio-video recordings of a clinically validated Australian depression dataset, several experiments are conducted to characterise depression-related patterns from verbal and nonverbal cues. Of particular interest in this dissertation is the exploration of speech style, speech prosody, eye activity, and head pose modalities. Statistical analysis and automatic classification of extracted cues are investigated. In addition, multimodal fusion methods of these modalities are examined to increase the accuracy and confidence level of detecting depression. These investigations result in a proposed system that detects depression in a binary manner (e.g. depressed vs. non-depressed) using temporal depression behavioural cues. The proposed system: (1) uses audio-video recordings to investigate verbal and nonverbal modalities, (2) extracts functional features from verbal and nonverbal modalities over the entire subjects’ segments, (3) preand post-normalises the extracted features, (4) selects features using the T-test, (5) classifies depression in a binary manner (i.e. severely depressed vs. healthy controls), and finally (6) fuses the individual modalities. The proposed system was validated for scalability and usability using generalisation experiments. Close studies were made of American and German depression datasets individually, and then also in combination with the Australian one. Applying the proposed system to the three datasets showed remarkably high classification
The Anthropology of Ritual: Monitoring and Stewarding Demonstrations in Northern Ireland

Rioting in Northern Ireland sometimes appears endemic. The control of public space, through the utilisation of rituals and symbols, has played a significant part in the violent conflict and has remained a central issue since the 1998 Multi-Party Agreement institutionalised the peace process. This article draws upon ethnographic research and anthropological models of ritual to explore policy interventions in conflict resolution over potential public disorders. In particular, it looks at the use of monitors, mediators and marshals at parades and demonstrations and describes how anthropological fieldwork has played a role in developing projects and policies that offer solutions to a cycle of intercommunal street violence.
Direct Load Control in Microgrids to Enhance the Performance of Integrated Resources Planning

Load management is usually not considered in details during the planning stage due to its complexity and uncertainty in nature. However, this practice is changed in microgrids since the load composition in microgrids is more specific and manageable. In addition, the development of advanced metering infrastructure provides a more convenient mechanism for data collection and system control. This paper presents an integrated resources planning model based on optimal direct load control (DLC) (such as control of the air-conditioning load) in microgrids for load shifting and peak shaving to reduce/defer investments and minimize total social costs. This paper begins with the introduction of DLC and the models of the relevant distributed generation resources, including photovoltaic, wind turbines, diesel engines, and batteries. An algorithm is presented to combine the microgrid planning and DLC strategy. The results of the case study show that the proposed model provides an effective approach for the least cost planning in microgrids by using load management as competitive virtual power sources.
Extended lymph node dissection in robotic radical prostatectomy: Current status

Introduction: The role and extent of extended pelvic lymph node dissection (ePLND) during radical prostatectomy (RP) for prostate cancer patients remains unclear. Materials and Methods: A PubMed literature search was performed for studies reporting on treatment regimens and outcomes in patients with prostate cancer treated by RP and extended lymph node dissection between 1999 and 2013. Results: Studies have shown that RP can improve progression-free and overall survival in patients with lymph node-positive prostate cancer. While this finding requires further validation, it does allow urologists to question the former treatment paradigm of aborting surgery when lymph node invasion from prostate cancer occurred, especially in patients with limited lymph node tumor infiltration. Studies show that intermediate- and high-risk patients should undergo ePLND up to the common iliac arteries in order to improve nodal staging. Conclusions: Evidence from the literature suggests that RP with ePLND improves survival in lymph node-positive prostate cancer. While studies have shown promising results, further improvements and understanding of the surgical technique and post-operative treatment are required to improve treatment for prostate cancer patients with lymph node involvement.
Intensity-modulated radiotherapy for hepatocellular carcinoma: dosimetric and clinical results

Since the introduction of 3-dimensional conformal radiotherapy (3DCRT), new radiotherapy techniques have expanded the indication of radiotherapy for the treatment of hepatocellular carcinoma (HCC), from the hitherto palliative to a now curative-intent purpose. Intensity-modulated radiotherapy (IMRT), currently the most advanced radiotherapy technique, is considered an attractive option for the treatment of HCC, and is more widely applied because it can deliver a higher dose to the tumor than 3DCRT while sparing surrounding normal organs. However, the advantages and potential disadvantages of IMRT for treating HCC have not been fully established. This article deals with three different IMRT techniques, including static IMRT and volumetric modulated arc therapy using conventional multileaf collimator (MLC) mounted linear accelerators, and helical IMRT using binary MLC mounted helical tomotherapy machine. We review dosimetric and clinical studies for these IMRT techniques for the treatment of HCC.
Suspended InAs nanowire Josephson junctions assembled via dielectrophoresis

We present a novel technique for the realization of suspended Josephson junctions based on InAs semiconductor nanowires. The devices are assembled using a technique of drop-casting guided by dielectrophoresis, which allows one to finely align the nanostructures on top of the electrodes. The proposed architecture removes the interaction between the nanowire and the substrate which is known to influence disorder and the orientation of the Rashba vector. The relevance of this approach in view of the implementation of hybrid Josephson junctions based on semiconducting nanowires coupled with high-temperature superconductors is discussed.
Navigating a Literacy Landscape: Teaching Conceptual Understanding with Multiple Text Types

The authors draw on Cognitive Flexibility Theory (Spiro, Coulson, Feltovich, & Anderson, 2004) as a lens to examine one seventh-grade English language arts teacher's pedagogical approach to using multiple text types to develop students' conceptual understandings about the 1957 integration of Little Rock's Central High School. Multiple text types included but were not limited to memoir, expository texts, photographs, documentaries, docudrama, and Web documents. Findings suggest the teacher's use of multiple text types required a systematic and strategic juxtaposition of texts along with questioning, resulting in a teacher-centered approach.
Is it Really that Difficult to Parse German?

This paper presents a comparative study of probabilistic treebank parsing of German, using the Negra and TuBa-D/Z tree-banks. Experiments with the Stanford parser, which uses a factored PCFG and dependency model, show that, contrary to previous claims for other parsers, lexicalization of PCFG models boosts parsing performance for both treebanks. The experiments also show that there is a big difference in parsing performance, when trained on the Negra and on the TuBa-D/Z treebanks. Parser performance for the models trained on TuBa-D/Z are comparable to parsing results for English with the Stanford parser, when trained on the Penn treebank. This comparison at least suggests that German is not harder to parse than its West-Germanic neighbor language English.
RoboCupRescue - Robot League Team KURT3D, Germany

A mobile robot named KURT3D was developed at the Fraunhofer Institute for Autonomous Intelligent Systems during the last three years. The key innovation of this system lies in the capability for autonomous or operator- assisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, KURT3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of KURT3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we are confident of managing the rescue robot league competition, too.
Combination of direct and indirect evidence in mixed treatment comparisons

Mixed treatment comparison (MTC) meta‐analysis is a generalization of standard pairwise meta‐analysis for A vs B trials, to data structures that include, for example, A vs B, B vs C, and A vs C trials. There are two roles for MTC: one is to strengthen inference concerning the relative efficacy of two treatments, by including both ‘direct’ and ‘indirect’ comparisons. The other is to facilitate simultaneous inference regarding all treatments, in order for example to select the best treatment. In this paper, we present a range of Bayesian hierarchical models using the Markov chain Monte Carlo software WinBUGS. These are multivariate random effects models that allow for variation in true treatment effects across trials. We consider models where the between‐trials variance is homogeneous across treatment comparisons as well as heterogeneous variance models. We also compare models with fixed (unconstrained) baseline study effects with models with random baselines drawn from a common distribution. These models are applied to an illustrative data set and posterior parameter distributions are compared. We discuss model critique and model selection, illustrating the role of Bayesian deviance analysis, and node‐based model criticism. The assumptions underlying the MTC models and their parameterization are also discussed. Copyright © 2004 John Wiley & Sons, Ltd.
‘These are the things I may never learn from books’. Clinical psychology students’ experiences of their development of practical wisdom

Clinical psychologists in their clinical work rely on both theoretical knowledge and practical wisdom. However, during education theoretical knowledge receives more attention. Since practical wisdom is fundamental in clinical work, it has been argued that it should be emphasized in education. In order to further understand how practical wisdom might be supported, this work investigates how clinical psychology students, who within a year were about to graduate, perceived that education had supported the development of clinical wisdom. Seven students were interviewed about their experiences of how education had supported their clinical wisdom. The interviews were analyzed using interpretative phenomenological analysis. The participants sensed that practical wisdom was connected to personal experiences and reflection, and thus was hard to distinguish from personal development. Moreover, they sensed that education concerning practical wisdom should be specifically mentioned in the curriculum, and that theory and practice should be more integrated. The findings are discussed with respect to learning experiences and future educational possibilities.
Job Stress, Emotional Labor, and Emotional Intelligence as Predictors of Turnover Intention: Evidence from Two Service Occupations

This study investigated the extent to which job stress, emotional labor, and emotional intelligence predict turnover intention among bank and health workers. Sample comprised 270 employees (bank = 149; health = 121), whose ages averaged 33.04 (SD = 7.86). Results of the hierarchical multiple regression revealed that job stress did not predict turnover intention. However, emotional labor increased employees’ turnover intention. Emotional intelligence led to a reduction in employees’ level of turnover intention. Bank workers reported higher level of turnover intention than health workers. In order to reduce turnover intention among employees in service occupations, emotional demands placed on them should be reduced while their level of emotional intelligence should be enhanced. DOI: 10.5901/mjss.2014. v5n6p351
Privacy-Preserving Location-Proximity for Mobile Apps

Location Based Services (LBS) have seen alarming privacy breaches in recent years. While there has been much recent progress by the research community on developing privacy-enhancing mechanisms for LBS, their evaluation has been often focused on the privacy guarantees, while the question of whether these mechanisms can be adopted by practical LBS applications has received limited attention. This paper studies the applicability of Privacy-Preserving Location Proximity (PPLP) protocols in the setting of mobile apps. We categorize popular location social apps and analyze the trade-offs of privacy and functionality with respect to PPLP enhancements. To investigate the practical performance trade-offs, we present an in-depth case study of an Android application that implements InnerCircle, a state-of-the-art protocol for privacy-preserving location proximity. This study indicates that the performance of the privacy-preserving application for coarse-grained precision is comparable to real applications with the same feature set.
Controlling the search for expanded query representations by constrained optimization in latent variable space

We investigate a new family of algorithms for finding reliable query representations based on pseudo-relevance feedback, by replacing the traditional E-step in EM methods with a more general convex optimization step that allows constraints and objectives to bias the search by direct influence in the space of latent variables. This bias amounts to a penalized form of maximum likelihood objective, and we investigate adding a translation kernel and a word diversity constraint. Combined with simple generative models for IR, constraining the posterior distribution of the latent variables is also a natural way to incorporate evidence of user intent and feedback, such as observations on words, documents, or specific word-document pairs. More generally, we believe such an approach provides an interesting starting point for unified probabilistic approaches in which multiple sources of context are used to guide parameter estimation in models of query intent under taskor domain-specific constraints.
A Cryptic DNA Binding Domain at the COOH Terminus of TFIIIB70 Affects Formation, Stability, and Function of Preinitiation Complexes*

TFIIIC-dependent assembly of yeast TFIIIB on class III genes unmasks a high avidity of TFIIIB for DNA. TFIIIB contains TATA-binding protein (TBP), TFIIIB90/B", and TFIIIB70/Brf1, which is homologous to TFIIB. Using limited proteolysis, we have found that the COOH terminus of TFIIIB70 (residues 510–596) forms a protease-resistant domain that binds DNA tightly as seen by Southwestern, DNase I footprinting, and gel shift assays. Consistent with a role for this DNA binding activity, preinitiation complexes were formed less efficiently with truncated TFIIIB70 lacking the COOH-terminal domain and displayed an increased sensitivity to heparin. B′ (TFIIIB70 + TBP)·TFIIIC·DNA complexes were also particularly unstable. In addition, TFIIIB·TFIIIC·DNA complexes containing truncated TFIIIB70 were impaired in promoting transcription initiation.
Feature Estimation for Vocal Fold Edema Detection Using Short-Term Cepstral Analysis

Digital signal processing techniques have been used to perform an acoustic analysis for vocal quality assessment due to the simplicity and the noninvasive nature of the measurement procedures. Their employment is of special interest, as they can provide an objective diagnosis of pathological voices, and may be used as complementary tool in laryngoscope exams. The acoustic modeling of pathological voices is very important to discriminate normal and pathological voices. The degree of reliability and effectiveness of the discriminating process depends on the appropriate acoustic feature extraction. This paper aims at specifying and evaluating the acoustic features for vocal fold edema through a parametric modeling approach based on the resonant structure of the human speech production mechanism, and a nonparametric approach related to human auditory perception system. For this purpose, LPC and LPC-based cepstral coefficients, and mel-frequency cepstral coefficients are used. A vector-quantizing-trained distance classifier is used in the discrimination process.
Mining Ethnic Content Online with Additively Regularized Topic Models

Social studies of the Internet have adopted large-scale text mining for unsupervised discovery of topics related to specific subjects. A recently developed approach to topic modeling, additive regularization of topic models (ARTM), provides fast inference and more control over the topics with a wide variety of possible regularizers than developing LDA extensions. We apply ARTM to mining ethnic-related content from Russian-language blogosphere, introduce a new combined regularizer, and compare models derived from ARTM with LDA. We show with human evaluations that ARTM is better for mining topics on specific subjects, finding more relevant topics of higher or comparable quality.