Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptions and expectations of pension savings adequacy: a comparative study of Dutch and American workers

ABSTRACT What drives the perceptions of pension savings adequacy and what do workers expect to receive when they retire? These questions are assessed among married workers using an identical survey distributed to Dutch and American workers in 2007. Despite marked differences in expected pension replacement rates – where the Dutch replacement rates are systematically higher than the American rates – the perceived savings adequacy is more or less the same across Dutch and American workers. In both countries, about half of the respondents were confident they had amassed sufficient retirement savings. Individuals' perceived savings adequacy was found to be influenced by three groups of factors: trust in pension institutions (pension funds, banks, insurance companies and governments), social forces and psychological dispositions. This study shows that differences in the dispositions of workers (with respect to future orientation and financial planning) played a far larger role in explaining differences in perceptions of savings adequacy in the United States than in The Netherlands. Dutch workers rely and trust their pension fund and seem to leave thinking about and planning for retirement to its managers.
Learning Parameters by Prediction Markets and Kelly Rule for Graphical Models

We consider the case where a large number of human and machine agents collaborate to estimate a joint distribution on events. Some of these agents may be statistical learners processing large volumes of data, but typically any one agent will have access to only some of the data sources. Prediction markets have proven to be an accurate and robust mechanism for aggregating such estimates (Chen and Pennock, 2010), (Barbu and Lay, 2011). Agents in a prediction market trade on futures in events of interest. Their trades collectively determine a probability distribution. Crucially, limited trading resources force agents to prioritize adjustments to the market distribution. Optimally allocating these resources is a challenging problem. In the economic spirit of specialization, we expect prediction markets to do even better if agents can focus on beliefs, and hand off those beliefs to an optimal trading algorithm. Kelly (1956) solved the optimal investment problem for single-asset markets. In previous work, we developed efficient methods to update both the joint probability distribution and user's assets for the graphical model based prediction market (Sun et al., 2012). In this paper we create a Kelly rule automated trader for combinatorial prediction markets and evaluate its performance by numerical simulation.
Genetic diversity and mating types of Fusarium culmorum and Fusarium graminearum originating from different agro‐ecological regions in Turkey

Fusarium culmorum and F. graminearum are the major pathogens for dryland root/foot‐rot and head‐blight diseases in economically important grain crops. This study was aimed at the molecular characterization of Fusarium spp. isolates, which have been collected from cereal fields in three agro‐ecological regions in Turkey. Genetic diversity has been analyzed by generating RFLP markers from the intergenic spacer (IGS) region of ribosomal RNA. The selection of restriction enzymes for IGS‐RFLP studies has been found critical to maximize polymorphic markers. Only 3 of 14 restriction endonucleases were useful in differentiating Fusarium spp. isolates. PstI was the most efficient enzyme to produce a maximum of nine DNA markers in one individual and total 22 polymorphic representative banding patterns. Polymorphism based on IGS‐RFLP was high and average 88% in both species. There was no association between IGS diversity and geographic locations from which the samples were taken. Both MAT‐1 and MAT‐2 sequences were amplified in F. graminearum similarly to previous reports. Most of the F. culmorum isolates carried either MAT‐1 or MAT‐2 sequences, and differently two isolates carried both sequences. Mating type determination was helpful to distinguish F. pseudograminearum from F. graminearum, which cannot be discriminated by SCAR markers or morphological assessment. High genetic diversity by IGS‐RFLP markers in F. culmorum was discussed in relation to its fitness as the most common pathogen in dryland root rot complex (DLRRC).
CyLineUp: A Cytoscape app for visualizing data in network small multiples

CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using “small multiples”. This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user’s needs. The results can be exported as a high quality vector image.
Improving Interactive Video Retrieval by Exploiting Automatically-Extracted Video Structural Semantics

In this work the contribution of automatically-extracted (thus, imperfect) video structural semantics towards improving interactive video retrieval is examined. First, the automatic extraction of video structural semantics, i.e. the decomposition of the video into scenes that correspond to the different sub-stories or high-level events, is performed. Then, these are introduced to the interactive video retrieval paradigm. Finally, their potential contribution is experimentally evaluated. To this end, different members of a family of scene segmentation algorithms are applied to an extensive professional video collection coming from the TRECVID benchmarking activity, subsequently, a large number of user interactions with a retrieval system that exploits these structural semantics is simulated. The experimental results document the contribution of state-of-the-art automatically-extracted video structural semantics to the efficient and effective interactive video retrieval.
The Iowa Gambling Task in depression – what have we learned about sub-optimal decision-making strategies?

Our earlier study found patients with depression to show a preference for larger reward as measured by the Iowa Gambling Task (IGT). In this IGT version, larger rewards were associated with even larger consequent losses. In the light of the clinical markers defining depressive disorder, this finding might appear controversial at first. Performance of depressed patients on various decision-making (DM) tasks is typically found to be impaired. Evidence points toward reduced reward learning, as well as the difficulty to shift strategy and integrate environmental changes into DM contingencies. This results in an impaired ability to modulate behavior as a function of reward, or punishment, respectively. Clinical symptoms of the disorder, the genetic profile, as well as personality traits might also influence DM strategies. More severe depression increased sensitivity to immediate large punishment, thus predicting future decisions, and was also associated with higher harm avoidance. Anhedonic features diminished reward learning abilities to a greater extent, even predicting clinical outcome. Several questions about how these aspects relate remain to be clarified. Is there a genetic predisposition for the DM impairment preceding mood symptoms? Is it the consequence of clinical signs or even learned behavior serving as a coping strategy? Are patients prone to develop an aversion of loss or are they unable to sense or deal with reward or the preference of reward? Does the DM deficit normalize or is a persisting impairment predictor for clinical outcome or relapse risk? To what extent is it influenced by medication effects? How does a long-lasting DM deficit affect daily life and social interactions? Strikingly, research evidence indicates that depressed patients tend to behave less deceptive and more self-focused, resulting in impaired social DM. The difficulty in daily interpersonal interactions might contribute to social isolation, further intensifying depressive symptoms.
How many roads lead to Rome? Equifinality set-size and commitment to goals and means.

Four studies examined the relation between the number of equifinal means to a goal, actors' commitment to that goal, and their commitment to the means. In Study 1, participants freely generated varying number of means to two of their work goals. In Study 2, they generated social means to their goals (people they viewed as helpful to goal attainment). In Studies 3 and 4, the number of means to participants' goals was experimentally manipulated. All four studies found that means commitment is negatively related, whereas goal commitment is positively related, to means number. Consistent support was also obtained for the notion that the relation between means number and goal commitment is mediated by the expectancy of goal attainment, and by goal importance. Conceptual and practical implications of the findings were considered that link together the notions of substitutability and dependency within a goal systemic framework. Copyright © 2010 John Wiley & Sons, Ltd.
An ontology-driven framework to support scenario representation in a 3D operator training simulator

This paper presents a framework to support the development of three-dimensional virtual scenarios for an operator training simulator for electrical systems. Given the need to represent a variety of scenarios of interest, this can be an effort and time consuming task. The proposed framework promotes a systematic approach when building scenarios and is supported by tools from the ontology-based domain. An editing tool is also under construction. As it will be discussed in the paper, this approach resulted in the simplification of the scenario building process which is achieved by interchanging descriptions at different levels of abstraction. The descriptions concern the situation to be represented; plant objects' representation, both visual and behavioural, the latter represented as Coloured Petri Nets (CPN) models.
Big Data, new epistemologies and paradigm shifts

This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology.
Slow wave sleep enhancement with gaboxadol reduces daytime sleepiness during sleep restriction.

STUDY OBJECTIVES To evaluate the impact of enhanced slow wave sleep (SWS) on behavioral, psychological, and physiological changes resulting from sleep restriction. DESIGN A double-blind, parallel group, placebo-controlled design was used to compare gaboxadol (GBX) 15 mg, a SWS-enhancing drug, to placebo during 4 nights of sleep restriction (5 h/night). Behavioral, psychological, and physiological measures of the impact of sleep restriction were assessed in both groups at baseline, during sleep restriction and following recovery sleep. SETTING Sleep research laboratory. PARTICIPANTS Forty-one healthy adults; 9 males and 12 females (mean age: 32.0 +/- 9.9 y) in the placebo group and 10 males and 10 females (mean age: 31.9 +/- 10.2 y) in the GBX group. INTERVENTIONS Both experimental groups underwent 4 nights of sleep restriction. Each group received either GBX 15 mg or placebo on all sleep restriction nights, and both groups received placebo on baseline and recovery nights. MEASUREMENTS AND RESULTS Polysomnography documented a SWS-enhancing effect of GBX with no group difference in total sleep time during sleep restriction. The placebo group displayed the predicted deficits due to sleep restriction on the multiple sleep latency test (MSLT) and on introspective measures of sleepiness and fatigue. Compared to placebo, the GBX group showed significantly less physiological sleepiness on the MSLT and lower levels of introspective sleepiness and fatigue during sleep restriction. There were no differences between groups on the psychomotor vigilance task (PVT) and a cognitive test battery, but these measures were minimally affected by sleep restriction in this study. The correlation between change from baseline in MSLT on Day 6 and change from baseline in SWS on Night 6 was significant in the GBX group and in both group combined. CONCLUSIONS The results of this study are consistent with the hypothesis that enhanced SWS, in this study produced by GBX, reduces physiological sleep tendency and introspective sleepiness and fatigue which typically result from sleep restriction.
Using a tactile prompt to increase instructor delivery of behavior- specific praise and token reinforcement and their collateral effects on stereotypic behavior in students with autism spectrum disorders

this study evaluated the effectiveness of a tactile cue, the gentle reminder™, as a prompt to increase instructor use of behavior-specific praise and token reinforcement. First, instructors were told to deliver reinforcement when a student was engaged in behavior that was incompatible with stereotypy. they were then told they would feel a vibration every 10 minutes to remind them to use reinforcement for these behavior. A tactile prompt was then programmed to vibrate every 10 minutes. it was expected that the teacher’s use of reinforcement would increase and in turn, this would lead to a reduction in the level of student stereotypic behavior. A multiple baseline design across participants was used to evaluate the effects of the tactile prompt on instructor behavior and the collateral effects on student stereotypic behavior. After implementation of the tactile prompt, instructors’ use of reinforcement for behavior incompatible with stereotypy increased systematically across all three instructors. the instructor’s use of reinforcement increased more than once every 10 minutes when the tactile cue was implemented. in addition, there was a decrease observed in the level of the students’ stereotypic behavior after
The recognition and treatment of growth disorders – A 50-year retrospective

The past 50 years have seen great progress in the understanding and treatment of classic growth disorders. Advances such as the recognition of hormone receptor defects, the development of recombinant growth hormone, and the expanding awareness of epigenetic phenomena affecting growth are among these great achievements. Yet growth failure remains a pervasive problem among children with complex health conditions, such as survivors of childhood cancers, premature infants, organ transplant recipients, and children with cystic fibrosis. The significant increases in life expectancy among these groups underscores the potential consequences of poor growth, whether due to the underlying conditions or medical treatments, as they may have long-lasting effects into adulthood. The ongoing contributions of human biologists to the study of human growth remain essential in the recognition and treatment of growth disorders, by defining normal patterns of growth and body composition, the interplay of growth and maturation, the role of environmental, behavioral and genetic factors, and the long-term consequences of growth patterns. Examples will be given based on two common genetic disorders, cystic fibrosis and sickle-cell anemia, to highlight the relationships between growth failure, survival, and malnutrition. Also, a study of bone mineral accretion in children with cystic fibrosis will illustrate the importance of understanding patterns of growth in healthy children, and their application in the diagnosis and management of children with chronic disease. These examples accentuate the need for continued participation of human biologists in the study of growth and development and the care of children.
Developments in work psychology: Emerging issues and future trends

The discipline of work psychology has accomplished a great deal in a short space of time, and is thriving. The  eld has undoubtedly evolved to perform a valuable role in society and in promoting the well-being of employees at work. This advancement can be attributed partially to the growing appreciation of the utility of work psychology in enhancing individual and organizational prosperity. The expertise of both academic and practitioner work psychologists has had an enormous in uence in the way many organizations operate, ranging from multinational commercial organizations, through to public-owned companies and the voluntary sector. The review articles presented in this centennial special issue attest to this proposition, and demonstrate the achievements of work psychology over the past few decades. The intention of this issue is to provide a collection of review papers from some of the leading authors in the  eld, focusing on the theme of the British Psychological Society centenary celebrations, which is ‘Psychology; the state of the science and emerging issues’. The purpose of this discussion paper is to provide a descriptive re ection of the topics presented in this issue, highlighting emergent themes, and presenting some of the apparent inter-dependencies. The brief for authors was to synthesize existing literature in the area, to outline a future research agenda, and to comment on potential implications for applied practice. The topics included are by no means exhaustive, and there are certainly numerous other issues in work psychology that deserve attention. Indeed, the sheer diversity of research areas and spheres of applied practice currently embraced by work psychology is quite remarkable. Over time, attention has extended from a focus at the employee level of analysis towards a breadth of impact in areas spanning organizational strategy, human-computer interaction and the work/non-work divide. This paper presents an overview of the recurrent themes emerging from the review articles presented in this issue. Five key themes are identi ed to be considered for future research and practice in work psychology: (1) the transformation of the organizational context, (2) employer demands versus employee
High Performance Spectral Simulation of Turbulent Flows in Massively Parallel Machines With Distributed Memory

Here we have demonstrated the possibility of very high performance in the implementation of a global spectral methodology on a massively parallel architec ture with distributed memory. Spectral simulations of channel flow and thermal convection in a three-dimen sional Cartesian geometry have yielded a very high performance—up to 26 Gflops/s on a 512-node CM5. In general, implementation of spectral methodology in parallel processors with distributed memory requires nonlocal interprocessor data transfer that is not re stricted to being between nearest neighbors. In spite of their increased communication overhead, better per formance is possible in global methodologies owing to their dense matrix operations and organized data com munication. In this paper we outline a general method ology for the data-parallel implementation of spectral methods on massively parallel machines with distrib uted memory. Following the steps presented here, very high performance can be obtained on a wide vari ety of massively parallel architectures.
Characterization of the Campylobacter fetus sapA promoter: evidence that the sapA promoter is deleted in spontaneous mutant strains

Wild-type Campylobacter fetus cells possess S-layer proteins (S+ phenotype), whereas after laboratory passage, spontaneous stable mutants that do not express these proteins (S- phenotype) arise. To determine the molecular mechanisms by which C. fetus changes to the S- phenotype, we studied wild-type strain 23D, from which the sapA gene encoding the 97-kDa S-layer protein has been cloned, and strain 23B, a spontaneous S- mutant. We compared these strains with another pair of strains, LP (S+) and HP (S-). Southern analysis with the cloned sapA gene as a probe indicated that both pairs of strains have multiple sapA homologs. Using gene disruption and replacement techniques, we constructed an isogenic strain of 23D that differed only in sapA expression (strain 23D:401:1). A 6.0-kb HindIII fragment from 23D:401:1 containing 3.4 kb of sapA upstream region then was cloned into pBluescript to produce pBG101. Nucleotide sequence analysis of sapA upstream region revealed a consensus promoter at -121 bp from the translational start site. Primer extension analysis placed a single in vivo transcription initiation site at the -114-bp position of sapA. A DNA probe derived from the sapA promoter region hybridized to a 5.5-kb HindIII fragment of chromosomal DNA from strain 23D but not to DNA from strain 23B. Northern RNA blot analysis showed no sapA mRNA in strain 23B. These data indicate that the lack of S-layer protein expression in spontaneous mutant strains is caused by the deletion of promoter sequences.
Categorizing cubes: Revisiting pose normalization

This paper introduces and analyzes the novel task of categorical classification of cuboidal objects - e.g., distinguishing washing machines versus filing cabinets. To do so, it makes use of recent methods for automatic alignment of cuboidal objects in images. Given such geometric alignments, the natural approach for recognition might extract pose-normalized appearance features from a canonically-aligned coordinate frame. Though such approaches are extraordinarily common, we demonstrate that they are not optimal, both theoretically and empirically. One reason is that such approaches require accurate shape alignment. However, even with ground-truth alignment, pose-normalized representations may still be sub-optimal. Instead, we introduce methods based on pose-synthesis, a somewhat simple approach of augmenting training data with geometrically perturbed training samples. We demonstrate, both theoretically and empirically, that synthesis is a surprisingly simple but effective strategy that allows for state-of-the-art categorization and automatic 3D alignment. To aid our empirical analysis, we introduce a novel dataset for cuboidal object categorization.
Analog baseband channel for GSM/UMTS/WLAN/Bluetooth reconfigurable multistandard terminals

This paper presents a reconfigurable analog baseband channel for multistandard receivers. The circuit, consisting of two variable gain amplifiers and a low-pass filter, fulfills the requirements of GSM, WCDMA (UMTS), WLAN (IEEE 802.11a/b/g), and Bluetooth. The gain, bandwidth and power consumption of the circuit are changed through a digital control word depending on the selected standard. Simulation results, including all of the tests prescribed by the different standards, confirm the validity of the proposed solution. The in-band IIP3 evaluated with maximum gain (68dB/39dB) is 5dBm/1dBm for UMTS/WLAN respectively, while the power consumption is 51.7mW/55mW in the two cases