Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluative and Psychophysiological Responses to Short Film Clips of Different Emotional Content

The study presents self-report and psychophysiological data obtained in response to short film clips representing scenes related to different emotions. This was done in order to obtain evidence on the structure of positive and negative affective states following a combined dimensional/categorical approach to emotion and based on responses to stimuli that are more realistic than the static pictures usually employed in the study of emotion. Affective ratings and self-report measures showed a differential structure of the response to positive and negative films (Experiment 1). While all negative films were rated as low in valence and high in arousal, positive films were differentiated into arousing (happy and pleasure contents) and de-arousing (relax contents) categories. A more complex pattern emerged in Experiment 2, using two psychophysiological measures that are differentially sensitive to the main affective dimensions of valence and arousal, skin conductance response (SCR) and facial electromyography (fEMG). First, high arousal positive and negative films produced larger skin conductance responses. Second, fEMG measures showed differentiated response patterns within the positive and negative film categories. Within the positive category, happy and relaxing films had opposed effects, with happy films increasing and relax films decreasing activity over the zygomaticus muscle region. In the case of negative films, only those eliciting disgust produced a differentiated pattern of fEMG activity characterized by large corrugator responses and a modest increase of zygomatic responses. These results are discussed in relation to the adequacy of the dimensional and categorical approaches to emotion, the usefulness of combining subjective and psychophysiological measures, and the advantages of using realistic, dynamic stimuli for the study of emotion.
Cost-Effective Provisioning of Spot Instances in Clouds

This paper describes a resource management and a scheduling policy, spot scheduling algorithm (SpotSA). Infrastructure-as-a-Service providers offers their unused resources in the form of variable-priced virtual machines (VMs), known as "spot instances", at prices significantly lower than their standard fixed-priced resources. The SpotSA addresses the problem of running deadline-constrained computational jobs on a pool of resources that composed solely of spot instances. The SpotSA considers the differences of spot instances in price and performance so that users can run applications quickly and economically. And the SpotSA is a part of the system architecture. The purpose of this system is to help organizations to run computational jobs on dynamically provisioned resources when these organizations do not have a local cluster of resources.
Toward Hazard Aware Spaces: Knowing Where, When and What Hazards Occur

While considering all existing hazards for humans due to (a) natural disastrous events, (b) failures of human hazard attention or (c) intentional harmful behaviors of humans, we address the problem of building hazard aware spaces (HAS) to alert innocent people. We have researched and developed components of a prototype HAS system for detecting fire using wireless “smart” micro electro-mechanical systems (MEMS) sensor networks, such as the MICA sensors manufactured by Crossbow Inc., and spectral cameras, for instance, thermal infrared (IR), visible spectrum and multi-spectral cameras. Within this context, the paper overviews technical challenges and prototyped scientific solutions to (1) robotic sensor deployment using remote control, (2) synchronization of sensors and cameras, (3) localization of sensors and objects, (4) calibration of measurements from sensors and spectral cameras, (5) proactive camera control, (6) hazard detection, (7) human alert, (8) hazard confirmation and understanding, and (9) hazard containment. The work presents innovative signal processing applications of sensor network technology, and includes also theoretical and practical limitations that have to be understood while working with novel technologies.
Journal of Economic Behavior & Organization Endogenous Peer Effects: Local Aggregate or Local Average?

JEL classification: A14 D85 Z13 Keywords: Social networks Identification of peer effects J test Individual-based policy Group-based policy a b s t r a c t We develop a unified model embedding different behavioral mechanisms of social interactions and design a statistical model selection test to differentiate between them in empirical applications. This framework is applied to study peer effects in education (effort in studying) and sport activities for adolescents in the United States. We find that, for education, students tend to conform to the social norm of their friends while, for sport activities, both the social multiplier and the social norm effect matter.
Alternative approaches to updating item parameter estimates in tests with item cloning

Item cloning techniques can greatly reduce the cost of item writing and enhance the flexibility of item presentation. To deal with the possible variability of the item parameters caused by item cloning, Glas and van der Linden (in press, 2006) proposed a multilevel item response model where it is assumed that the item parameters of a 3-parameter logistic (3PL) model or a 3-parameter normal ogive (3PNO) model are sampled from a multivariate normal distribution associated with a parent item. The model is referred to as the item cloning model (ICM). For the situation where each cloned item is presented to a substantial number of respondents, Glas and van der Linden (2006) proposed a Bayesian procedure for parameter estimation using a Markov chain Monte Carlo (MCMC) method (the Gibbs sampler). Two procedures for updating the parameter estimates in the ICM are compared. In the first procedure, the MCMC procedure is run on the combined original and new data set. In the second procedure, the estimates obtained on the original data set are used as priors in an MCMC run using the new data only. Results of simulation studies indicated that the second procedure tended to lead to some loss of precision in the parameter estimates. However, in the simulation studies presented here, this loss was limited. On the other hand, the gain in computation time for the second method was not substantial either.
Essays in Empirical Health Economics

This dissertation includes four essays concerned with empirical health economics research questions. The first chapter presents a general introduction and a summary of the entire thesis. The second chapter deals with the question whether education causally affects health. It is a joint research project with Hendrik Jurges and Steffen Reinhold. The third chapter analyzes the emergence of health inequality in early childhood using panel data from the United Kingdom. The fourth chapter is dedicated to the research question whether there is a causal link between fertility and mental health in old age. The last chapter is on Attention Deficit Hyperactivity Disorder (ADHD). This research project sheds light on the question whether changes in household composition affect the probability that children develop a symptomatology of ADHD.
Classification of heart sound based on s-transform and neural network

The skill of cardiac auscultatory is very important to physicians for accurate diagnosis of many heart diseases. However, it needs some training and experience to improve the skills of medical students in recognizing and distinguishing the primary symptoms of cardiac diseases based on the heart sound that heard. This paper presents a method for feature extraction and classification of heart sound signals. The S-Transform (ST) technique is used to extract the features of heart sound. Then, the features were applied as inputs to classifier. The Multilayer Perceptron Network has been used to classify heart sound cases. The performance of the technique has been evaluated using 250 cardiac periods of heart sound recorded from heart sound simulator. The result has shown over 98% correct classification which shows the method used is suitable to classify heart sound cases.
A Cross-Layer Synchronous Dynamic Token Protocol for Ad Hoc Networks

This paper proposes a novel Cross-layer Synchronous Dynamic Token Protocol (CLSDTP) in single channel that is based on token-passing scheme. The protocol introduces a token relay algorithm which is fast and adaptive to topology variation, presents a collision avoidance algorithm which solves the exposed and hidden terminal problem through the information of network topology and current data transmission carried by the token. This information in the token is also used by the routing algorithm. The routing discovery and maintenance have been completed in the course of token relay. The short token rotation period ensures that the routing information can be exchanged in time. The CLSDTP improves the spatial multiplexing compared with the RTS/CTS access mechanism. In the same time, the system overhead has been largely depressed and the time effectiveness has been improved because of the information sharing by the MAC and routing layer. The results of the simulation show that CLSDTP can significantly improve the system performance.
How Do Bacteria Know They Are on a Surface and Regulate Their Response to an Adhering State?

Bacteria adhere to virtually all natural and synthetic surfaces [1,2]. Although there are a number of different reasons as to why bacteria adhere to a surface, the summarizing answer is brief: ‘‘Adhesion to a surface is a survival mechanism for bacteria’’. Nutrients in aqueous environments have the tendency to accumulate at surfaces [1,3], giving adhering bacteria a benefit over free floating, so-called planktonic ones. This is why mountain creeks may contain crystal clear, drinkable water, while stepping stones underneath the water may be covered with a slippery film of adhering microbes. In the oral cavity, adhesion to dental hard and soft tissues is life-saving to the organisms, because microbes that do not manage to adhere and remain planktonic in saliva are swallowed with an almost certain death in the gastrointestinal tract. Bacterial adhesion is generally recognized as the first step in biofilm formation, and for the human host, the ability of a bacterium to adhere is a definite virulence factor, especially in immunocompromised patients and in the growing number of elderly patients relying on biomaterials implants and devices for the restoration of function after (oncological) intervention surgery, trauma, or wear [4]. Well-known examples of biomaterials implants are dental implants, vascular grafts, and prosthetic hips and knee joints. Bacterial adhesion is a virulence factor, because it stimulates the organism to produce extracellular polymeric substances (EPSs), such as polysaccharides, proteins, nucleic acids, and lipids [5], through which they embed themselves in a protective matrix. This protective matrix provides mechanical stability to a biofilm and constitutes the main difference between planktonic bacteria and bacteria adhering to a surface in a socalled biofilm mode of growth. Bacteria organized in biofilms are at least ten to 1,000 times more resistant to antibiotics [6] than bacteria in a planktonic state and can cope much better with unfavorable external conditions in the host immune system than their planktonic counterparts. Not surprisingly, the fate of an infection associated with a biomaterials implant is mostly removal and replacement of the implant [7], at high costs to the health care system and great inconvenience to the patient.
Time-Frequency Analysis of Seismic Sequences 1

Re ection patterns play an important role in seismic sequence stratigraphy, therefore making their quantitative description essential for the construction and validation of sequence stratigraphic models from seismic data. The characteristics of a seismic re ection pattern can be elicited from the data by representing the data as a joint function of time and frequency. Developments in the eld of time-frequency analysis have led to t f representations with better resolution than can be obtained with classical methods for local frequency analysis. This justi es a study of the application of these new representations to the analysis of seismic data. Some examples of the t f representation of the seismic response of layered sequences are given. They clearly show the contribution of the stratigraphic sequence to the spectral content of the data. As an illustration of how sequence stratigraphic models can be constructed from a t f representation it is shown how the observed pattern in real seismic data can be matched to a sequence model.
Where Are the Effects of Family Structure? The EducationalLevel, Current Partnership, and Income Level of the Czech AdultPopulation Socialised in Single-Parent Families

Socialisation in a single-parent family has been associated with negative consequences both in previous research and popular discourse. This article investigates whether this association may be different in a society with a high rate of divorce and extramarital fertility. Using data from the Czech contribution to the EU-SILC survey, it tests hypotheses concerning the difference between the current situation of adults who grew up in single-parent families and those who were raised in intact families. We look for the infl uence of socialisation on single-parent families in three areas—educational attainment, current partnership situation, and current family income. The results of regression analyses show that the differences between children from single-parent families and those from intact ones are very small in the area of education (the infl uence is apparent only at the secondary school graduation level, no difference is present at the tertiary education level), relatively weak in the area of partnership situation, and imperceptible from the viewpoint of family income. These results exclude a causal explanation for the infl uence of single-parent families on outcomes, cast doubt on selective principles, and open space for interpretation in terms of mechanisms of family de-institutionalisation
Older People’s Experiences of Mobility and Mood in an Urban Environment: A Mixed Methods Approach Using Electroencephalography (EEG) and Interviews

There are concerns about mental wellbeing in later life in older people as the global population becomes older and more urbanised. Mobility in the built environment has a role to play in improving quality of life and wellbeing, as it facilitates independence and social interaction. Recent studies using neuroimaging methods in environmental psychology research have shown that different types of urban environments may be associated with distinctive patterns of brain activity, suggesting that we interact differently with varying environments. This paper reports on research that explores older people’s responses to urban places and their mobility in and around the built environment. The project aim was to understand how older people experience different urban environments using a mixed methods approach including electroencephalography (EEG), self-reported measures, and interview results. We found that older participants experience changing levels of “excitement”, “engagement” and “frustration” (as interpreted by proprietary EEG software) whilst walking between a busy built urban environment and an urban green space environment. These changes were further reflected in the qualitative themes that emerged from transcribed interviews undertaken one week post-walk. There has been no research to date that has directly assessed neural responses to an urban environment combined with qualitative interview analysis. A synergy of methods offers a deeper understanding of the changing moods of older people across time whilst walking in city settings.
Mechanisms of hair cell death and protection

Purpose of reviewSensory hair cells are mechanotransducers of the inner ear that are essential for hearing and balance. Hair cell death commonly occurs following acoustic trauma or exposure to ototoxins, such as the aminoglycoside antibiotics and the antineoplastic agent cisplatin. Loss of these inner ear sensory cells can lead to permanent sensorineural hearing loss, balance disturbance, or both. Currently, the only effective clinical intervention is prevention from exposure to known ototoxic insults. To help improve therapeutic strategies, a better understanding of the molecular mechanisms underlying hair cell degeneration is required. Current knowledge of these cell death mechanisms and potential therapeutic targets are discussed in this review. Recent findingsStudies have shown that caspase-9 and caspase-3 are key mediators of hair cell death induced by noise, aminoglycosides, and cisplatin. The Bcl-2 family consists of a group of proapoptotic and antiapoptotic molecules that act upstream of and regulate caspase activation. Recent studies have shed light on the roles of molecules acting more upstream, including mitogen-activated protein kinases and p53. SummaryThe mechanisms of sensory hair cell degeneration in response to different ototoxic stimuli share a final common pathway: caspase activation. Inhibition of caspases prevents or delays hair cell death and may preserve hearing/balance function. Inhibition of mitogen-activated protein kinases protects against noise-induced and aminoglycoside-induced but not cisplatin-induced hair cell death, which suggests divergent upstream regulatory mechanisms.
A Dependency-Driven Parser for German Dependency and Constituency Representations

We present a dependency-driven parser that parses both dependency structures and constituent structures. Constituency representations are automatically transformed into dependency representations with complex arc labels, which makes it possible to recover the constituent structure with both constituent labels and grammatical functions. We report a labeled attachment score close to 90% for dependency versions of the TIGER and TuBa-D/Z treebanks. Moreover, the parser is able to recover both constituent labels and grammatical functions with an F-Score over 75% for TuBa-D/Z and over 65% for TIGER.
An improved reconstruction procedure for the correction of local magnification effects in three‐dimensional atom‐probe

A new 3DAP reconstruction procedure is proposed that accounts for the evaporation field of a secondary phase. It applies the existing cluster selection software to identify the atoms of the second phase and, subsequently, an iterative algorithm to homogenise the volume laterally. This procedure, easily implementable on existing reconstruction software, has been applied successfully on simulated and real 3DAP analyses. Copyright © 2007 John Wiley & Sons, Ltd.
Multi-level coding and multi-stage decoding in MAC, broadcast, and relay channel

It is known that multi-level coding (MLC) with multi-stage decoding (MSD) approaches the point-to-point constellation constrained channel capacity subject to appropriate choice of code rates at each level. MLC/MSD in the context of multi-node networks has not been previously investigated, and is the subject of this paper. It is shown that MLC/MSD can approach the MAC capacity. Issues related to achieving non-corner points of the capacity region are discussed. A MLC-based superposition scheme for the degraded broadcast channel is discussed and an achievable region outlined. The half-duplex orthogonal degraded relay channel is studied under MLC/MSD. The achievable rate is calculated under two conditions: First we consider end-to-end layer-by-layer decoding, where each layer is decoded at the relay and destination only with help from previous layers. Then, we remove this constraint via a parity-forwarding approach at the relay, where the destination performs two multi-stage decoding operations: one corresponding to the relay-destination link and then one corresponding to the source-destination link. The achievable rate under parity forwarding is shown to be superior.
Path Analysis Association between Domestic Violence, Anxiety, Depression and Perceived Stress in Mothers and Children’s Development

Objective Given that several factors involved in the incidence or exacerbation of developmental disorders in children, the present study aimed to investigate the relationship between some of the risk factors affecting mothers’ health and development in children using path analysis. Materials & Methods The present cross-sectional analytical study was conducted on 750 mothers and their children in health centers in Tehran, Iran in 2014 enrolled through multi-stage random sampling. Data were collected using a demographic and personal information questionnaire, the Perceived Stress Scale, Beck’s depression Inventory, Spielberger’ anxiety inventory, the WHO domestic violence questionnaire and an ages & stages questionnaire for assessing children’s development. Data were analyzed using SPSS.19 (Chicago, IL, USA) and Lisrel 8.8. Results Developmental delay was observed in 12.1% of the children. The mean stress score was 23.94±8.62 in the mothers, 50.7% of whom showed mild to severe depression, 84.2% moderate to severe anxiety and 35.3% had been subjected to domestic violence. The path analysis showed that children’s development was affected directly by perceived stress (β=-0.09) and depression (β=-0.17) and indirectly by domestic violence (β=-0.05278) and anxiety (β=-0.0357). Of all the variables examined, depression had the biggest influence on development in the children (β=-0.17). The proposed model showed a good fit (GFI=1, RMSEA=0.034). Conclusion Children’s development was influenced indirectly by domestic violence and anxiety and directly by perceived stress and depression in mothers. It is thus suggested that more concern and attention be paid to women’s mental health and the domestic violence they experience.
An Intelligent Decision Support System for Supply Chain Integration

The integration of supply chain has become an important aspect in business environment due to the various business competitive pressures. This research proposes an intelligent decision support system for supply chain integration to support a supply chain’s competitive strategy of and help an organization gain a competitive advantage. Three major issues and related information technologies (IT), including a multi-agent architecture, data cube technique, and an ANN-based system, are investigated to explore the integration of supply chain activities. A multi-agent based architecture is proposed to support the selection and negotiation of purchasing bids and assist the decision making. The concept of data cube is used to investigate the multidimensional data of ordering information and evaluate the decision criteria of purchasing and ordering processes. A system combines supplier selection evaluation and artificial neural network (ANN) technique is designed to evaluate and forecast the supplier’s performance.
Improving Feature-Based Biomedical Event Extraction System by Integrating Argument Information

We describe a system for extracting biomedical events among genes and proteins from biomedical literature, using the corpus from the BioNLP’13 Shared Task on Event Extraction. The proposed system is characterized by a wide array of features based on dependency parse graphs and additional argument information in the second trigger detection. Based on the Uturku system which is the best one in the BioNLP’09 Shared Task, we improve the performance of biomedical event extraction by reducing illegal events and false positives in the second trigger detection and the second argument detection. On the development set of BioNLP’13, the system achieves an F-score of 50.96% on the primary task. On the test set of BioNLP’13, it achieves an F-score of 47.56% on the primary task obtaining the 5th place in task 1, which is 1.78 percentage points higher than the baseline (following the Uturku system), demonstrating that the proposed method is efficient.