Miracle-dz/UniFAR-FTUs huggingface dataset:
What is Creative Interviewing

This is a recording of a seminar presentation (audio plus powerpoint slidse). I am using the term ‘creative interviewing’ to refer to a form of interview that is qualitative, flexible, loosely or semi-structured (non-standardised) and involves the construction of data and knowledge through processes that can be seen as ‘creative’ in some way. The term ‘creative interviewing’ was coined for the social sciences in the 1980s by Jack Douglas, to denote the kind of interview that responded to situational dynamics and was flexible, rather than following a predefined structure (Douglas, 1985). It has also been used in the domain of journalism to denote an investigative rather than structured style of interviewing, where the interviewer as to think on their feet (Metzler, 2002). Creative interviews can also involve participants engaging in creative activities like drawing, collage, creating diagrams, taking pictures or looking at them (photo elicitation), walking, and so on. Creative interviews are usually treated for analytical purposes as ethnographic encounters, in the sense that the researcher is interested in, and participates in, as well as observes - the interactions involved, the situational dynamics, the surroundings and the physical and non-verbal elements.
Distributed task-specific processing of somatosensory feedback for voluntary motor control

Corrective responses to limb disturbances are surprisingly complex, but the neural basis of these goal-directed responses is poorly understood. Here we show that somatosensory feedback is transmitted to many sensory and motor cortical regions within 25 ms of a mechanical disturbance applied to the monkey’s arm. When limb feedback was salient to an ongoing motor action (task engagement), neurons in parietal area 5 immediately (~25 ms) increased their response to limb disturbances, whereas neurons in other regions did not alter their response until 15 to 40 ms later. In contrast, initiation of a motor action elicited by a limb disturbance (target selection) altered neural responses in primary motor cortex ~65 ms after the limb disturbance, and then in dorsal premotor cortex, with no effect in parietal regions until 150 ms post-perturbation. Our findings highlight broad parietofrontal circuits that provide the neural substrate for goal-directed corrections, an essential aspect of highly skilled motor behaviors. DOI: http://dx.doi. org/10.7554/eLife.13141. 001
PATERNAL POSTPARTUM DEPRESSION: A CONCEPT ANALYSIS

Paternal postpartum depression is a relatively unrecognized phenomenon in nursing tends to increasing gender functions shift and paternal involvement in childcare. Paternal postpartum depression refers to unhappy or sad is experienced by father following childbirth, despite of onset of paternal depression not exactly understood. Antecedence factors include hormonal, neuroticism, personal history of depression, depression in couple, marital satisfaction, life events and social support. Effect of paternal postpartum depression may be on his self, father – infant interaction and couple relationship. Paternal postpartum depression is measured in same ways that maternal postpartum depression has been measured. Such as the Schedule of Affective Disorders and Schizoprenia (SADS), the Structured Clinical Interview for DSM-II-R (SCID), The self report measures most commonly used for determining depression status were the Edinburgh Postnatal Depression Scale (EPDS), Beck Depression Inventory (BDI), General Health Questionnaire (GHQ) and the Center for Epidemiological Studies-Depression (CES-D). The possible differences in how men and women express emotional distress need to be acknowledged, thus specific instruments for assessing the dimensions of men’s depression need to be developed.
Acceptance Factors for using a Big Data Capability and Maturity Model

Big data is an emerging field that combines expertise across a range of domains, including software development, data management and statistics. However, it has been shown that big data projects suffer because they often operate at a low level of process maturity. To help address this gap, the Diffusion of Innovation Theory is used as a theoretical lens to identify factors that might drive an organization to try and improve their process maturity. Specifically, thirteen acceptance factors for teams to use (or not use) a Big Data CMM are identified. These results suggest that a positive perception exists with respect to relative advantage, compatibility and observability factors, and a negative perception exists with respect to perceived complexity. While more work is required to refine the list of factors, this insight can help guide the improvement of big data team processes.
Disaster Management Structure of Universities: Case Study of the Central Campus of the University of Tehran

Abstract Objective Research on the disaster management plans of renowned universities worldwide shows that such plans are generally compiled in 3 categories: structural, nonstructural, and organizational sections. The importance of earthquakes in Tehran and the high vulnerability of the University of Tehran to earthquakes encouraged us to challenge the university’s plans concerning disaster management. Methods An initial attempt was made to analyze the disaster management of 23 renowned universities worldwide and their structure compared with the present organizational structure of the University of Tehran. Then an expert opinion study was done to determine the appropriate management structure of the Incident Command System. Results These efforts resulted in an adhocratic system as the proper one for emergency situations after an earthquake. Furthermore, the results of the comparative study led to a general management structure that may be considered as a global pattern. Conclusions An appropriate organizational structure is proposed for the disaster management of the University of Tehran, which may be used as an appropriate disaster management structure for other universities. (Disaster Med Public Health Preparedness. 2017;11:681–693)
The stick-e note architecture: extending the interface beyond the user

This paper proposes a redefinition of the human-computer interface, extending its boundaries to encompass interaction with the user's physical environment. This extension to the interface enables computers to become aware of their context of use and intelligently adapt their activities and interface to suit their current circumstances. Context-awareness promises to greatly enhance user interfaces, but the complexity of capturing, representing and processing contextual data, presents a major obstacle to its further development. The Stick-e Note Architecture is proposed as a solution to this problem, offering a universal means of providing context-awareness through an easily understood metaphor based on the Post-It note.
Seismic retrofit of low-ductile columns through concrete jacketing with inoxydable reinforcement

Retrofit of structures often is an inevitable task especially when buildings are not designed for seismic actions or their design has followed older design codes. Many retrofit strategies have been proposed and practiced by previous researchers. Usage of fiber reinforced polymer [FRP], steel jacketing and reinforcement jacketing are among the most common retrofitting methods. For reinforcement jacketing, carbon steel has been widely employed by engineers, however, only a few applications of inoxydable reinforcements can be found in the literature. Moreover, when it comes to reinforcement jacketing, connection between the interface of original column and the jacket plays an important role and has attracted the attention of many researchers. Load transfer mechanism between original column and jacket is another field of study which has not been addressed in previous research. In this study application of inoxydable rebars for seismic retrofit of Reinforced Concrete (RC) columns was investigated. Two new connectors were used to increase the integrity between the original column and jacket. Load transfer mechanism between original column and jacket is another topic addressed in this research. This study included experimental and numerical analysis. For experimental study, 8 full scale RC columns were constructed and retrofitted with different reinforcement jacketing configurations. Numerical studies investigated the effect of different axial forces on the obtained results from experimental test. Results indicated that regardless of the employed retrofit configurations, the retrofitted columns have higher initial stiffness and ultimate strength compared to un-retrofitted columns. However, the retrofitted columns showed significantly lower ductility ratio when compared with un-retrofitted columns. All the retrofitted columns displayed a brittle failure mode in which spalling of concrete at the base of columns occurred without yield or buckling of reinforcements. Results indicated that confined jackets have higher ultimate strength and stiffness compared to un-confined jackets. However, they showed a lower ductility ratio when compared with un-confined jackets. It was observed that, when internal angle connection was used for retrofit, the highest ultimate strength, post-yield stiffness and effective stiffness were achieved. Monitoring the strain distribution between jackets and original columns revealed that confinement in jackets reduced the strain in the longitudinal reinforcement of original columns more than un-confined jackets. Strain values in the stirrups of confined jackets were significantly smaller than that of un-confined jackets. Strain ratios on the surface of concrete of confined jackets were larger than that of un-confined jackets. It is concluded that the proposed connectors have improved the ultimate strength of retrofitted columns as compared to conventionally retrofitted column, as they were unable to elevate the ultimate strengths to the level of a monolithic column.
Harmonium Models for Semantic Video Representation and Classi cation

Accurate and e cient video classi cation demands the fusion of multimodal information and the use of intermediate representations. Combining the two ideas into the one framework, we propose a probabilistic approach for video classi cation using intermediate semantic representations derived from multi-modal features. Based on a class of bipartite undirected graphical models named harmonium, our approach represents the video data as latent semantic topics derived by jointly modeling the transcript keywords and color-histogram features, and performs classi cation using these latent topics under a uni ed framework. We show satisfactory classi cation performance of our approach on a benchmark dataset as well as interesting insights into the data.
Efficient querying and maintenance of network provenance at internet-scale

Network accountability, forensic analysis, and failure diagnosis are becoming increasingly important for network management and security. Such capabilities often utilize network provenance - the ability to issue queries over network meta-data. For example, network provenance may be used to trace the path a message traverses on the network as well as to determine how message data were derived and which parties were involved in its derivation. This paper presents the design and implementation of ExSPAN, a generic and extensible framework that achieves efficient network provenance in a distributed environment. We utilize the database notion of data provenance to "explain" the existence of any network state, providing a versatile mechanism for network provenance. To achieve such flexibility at Internet-scale, ExSPAN uses declarative networking in which network protocols can be modeled as continuous queries over distributed streams and specified concisely in a declarative query language. We extend existing data models for provenance developed in database literature to enable distribution at Internet-scale, and investigate numerous optimization techniques to maintain and query distributed network provenance efficiently. The ExSPAN prototype is developed using RapidNet, a declarative networking platform based on the emerging ns-3 toolkit. Experiments over a simulated network and an actual deployment in a testbed environment demonstrate that our system supports a wide range of distributed provenance computations efficiently, resulting in significant reductions in bandwidth costs compared to traditional approaches.
Distributed Space-Time Coding for Two-Way Relay Networks

In this paper, we study the design of Distributed Space-Time Coding (DSTC) for two-way relay networks, where two users have bidirectional communication in the presence of two relay nodes and a direct link. Two new DSTC methods based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying are proposed that provide full transmission rate in the network. We evaluate the performance of the proposed methods and compare them by computer simulations. Our simulations show that both schemes achieve the maximum diversity and in addition, the proposed DF-based method outperforms the AF-based one.
Interpolation system for generating meteorological surfaces using to compute evapotranspiration in Haihe river basin

The generation of meteorological surfaces from point-source data is an overwork in computing evapotranspiration in Haihe river basin. To date, the software in common use can't meet this demand. Here we offer a high efficient, flexible, integrated interpolation system that employs a database to store climate weather data, a choice of interpolation methods, validation and carry on batch processing. We performed validations for five meteorological variables (minimum and maximum temperature, relative humidity, average wind speed and air pressure) with inverse distance weighting (IDW), thin plate smoothing spline (SPLINE) and ordinary kriging (OK) and achieved comparable success among all interpolation methods. IDW and OK precision are superior to SPLINE, but SPLINE is more effective and smoothing. There is not too big difference between IDW and OK, and the precision obviously improves after temperature and pressure are revised with the terrain.
BSkyTree: scalable skyline computation using a balanced pivot selection

Skyline queries have gained a lot of attention for multi-criteria analysis in large-scale datasets. While existing skyline algorithms have focused mostly on exploiting data dominance to achieve efficiency, we propose that data incomparability should be treated as another key factor in optimizing skyline computation. Specifically, to optimize both factors, we first identify common modules shared by existing non-index skyline algorithms, and then analyze them to develop a cost model to guide a balanced pivot point selection. Based on the cost model, we lastly implement our balanced pivot selection in two algorithms, BSkyTree-S and BSkyTree-P, treating both dominance and incomparability as key factors. Our experimental results demonstrate that proposed algorithms outperform state-of-the-art skyline algorithms up to two orders of magnitude.
SlackSim: a platform for parallel simulations of CMPs on CMPs

The fast simulation of chip multiprocessors (CMPs) presents a critical challenge to the architecture research community as both industry and academia shift their research focus to multicore design. Parallel simulation is a technique to accelerate microarchitecture simulation of CMPs by exploiting the inherent parallelism of CMPs. In this paper, we explore the simulation paradigm of simulating each core of a target CMP in one thread and then spreading the threads across the hardware thread contexts of a host CMP. We implement several parallel simulation schemes using POSIX Threads (Pthreads). We start with cycle-by-cycle simulation and then relax the synchronization condition in various schemes, which we call slack simulations. In slack simulations, the Pthreads simulating different simulated cores do not synchronize after each simulated cycle, but rather they are given some slack. The slack is the difference in cycle between the simulated times of any two target cores. Small slacks, such as a few cycles, greatly improve the efficiency of parallel CMP simulations, with no or negligible simulation error. We have developed a simulation framework called SlackSim to experiment with various slack simulation schemes. Unlike previous attempts to parallelize multiprocessor simulations on distributed memory machines, SlackSim takes advantage of the efficient sharing of data in the host CMP architecture. We demonstrate the efficiency and accuracy of some well known slack simulation schemes and of some new ones on SlackSim running on a state-of-the-art CMP platform.
T cell growth and differentiation induced by interleukin-HP1/IL-6, the murine hybridoma/plasmacytoma growth factor

Interleukin-HP1 (HP1)/IL-6 is a 25-30-kD protein produced by macrophages, fibroblasts, and certain T cell lines. It was originally identified as a mouse growth factor for B cell hybridomas and plasmacytomas, and was recently shown to stimulate growth and differentiation of normal B cells. Here we demonstrate that, in the presence of lectins or anti-T cell receptor antibodies, HP1/IL-6 has a growth factor activity equivalent to that of IL-2 for mature thymic and peripheral T cells of both the L3T4+ and Lyt-2+ subsets. Contrary to IL- 2 and IL-4, HP1/IL-6 was, however, not capable of supporting the growth of established T cell lines. In addition to its effects on T cell proliferation, HP1/IL-6 also enhanced the differentiation of mouse cytolytic T cell precursors in primary allogeneic mixed lymphocyte cultures. Fractionation of responding cell populations indicated that HP1/IL-6 was capable of restoring the response of accessory cell- depleted T cells to Con A. This observation suggests that the production of HP1/IL-6 by macrophages could, at least partly, explain their role in polyclonal T cell activation.
Coherence-assisted Wiener filter binaural speech enhancement

In this work a multi-channel speech enhancement system is proposed for diffuse noise reduction in future binaural hearing aids. The system assumes a near-frontal target and exploits knowledge of the spatial coherence between the measurement signals to compute the noise reduction Wiener filter gains without the need for external voice-activity detection or noise estimation. The left and right channel gains are combined to produce a system with a binaural output that preserves interaural time and level differences. Experiments with speech and noise signals measured using hearing aids in real reverberant environments demonstrate the noise reduction and intelligibility preservation performance of the proposed system.
Parametric model-based noise reduction for ToF depth sensors

This paper presents a novel Time-of-Flight (ToF) depth denoising algorithm based on parametric noise modeling. ToF depth image includes space varying noise which is related to IR intensity value at each pixel. By assuming ToF depth noise as additive white Gaussian noise, ToF depth noise can be modeled by using a power function of IR intensity. Meanwhile, nonlocal means filter is popularly used as an edge-preserving denoising method for removing additive Gaussian noise. To remove space varying depth noise, we propose an adaptive nonlocal means filtering. According to the estimated noise, the search window and weighting coefficient are adaptively determined at each pixel so that pixels with large noise variance are strongly filtered and pixels with small noise variance are weakly filtered. Experimental results demonstrate that the proposed algorithm provides good denoising performance while preserving details or edges compared to the typical nonlocal means filtering.
Folate Intake and Stomach Cancer Incidence in a Prospective Cohort of Swedish Women

Background: Experimental and epidemiologic evidence suggests that folate may play a role in the development of some cancers. Case-control studies and one prospective cohort study on folate intake in relation to stomach cancer risk have yielded inconsistent results. Methods: We prospectively investigated the relation between folate intake and the incidence of stomach cancer among 61,433 women in the Swedish Mammography Cohort. Participants completed a food frequency questionnaire at baseline (1987-1990) and again in 1997. During follow-up through December 2004, 156 incident stomach cancer cases were diagnosed. Cox proportional hazards models were used to calculate multivariate-adjusted hazard ratios. Results: There was no association between dietary folate intake (i.e., folate from food sources) and the risk of stomach cancer. The multivariate hazard ratio for the highest compared with the lowest category of updated average dietary folate intake was 1.04 (95% confidence interval, 0.61-1.86; Ptrend = 0.91). The relation between dietary folate intake and stomach cancer did not vary significantly by intake of alcohol, methionine, or caffeine. Conclusion: Results from this prospective study do not support an association between dietary folate intake and risk of stomach cancer. (Cancer Epidemiol Biomarkers Prev 2006;15(7):1409–12)
Stress Associated with Being a Student Teacher: Opening out the Perspective

Studies of student teacher stress have focused almost exclusively on the teaching practice placement; this has produced at best a partial picture and may have contributed to an underestimation of the pressures on such individuals. The aim of the current study was to take a more wide-ranging look at the stress and anxiety felt by primary teaching students in the course of their training. A questionnaire survey was followed up by a small number of interviews. It was found that students experience stresses of various types, both on placement and in college. The writers draw attention to high expectations, uncertainty and the emotional aspect of becoming a primary teacher.
Rapid Damage Detection in the Bam Area Using Multitemporal SAR and Exploiting Ancillary Data

In this paper, the problem of rapid earthquake damage detection in urban areas using multitemporal synthetic aperture radar data is addressed. It is shown that the combination of intensity and phase features enhances the damage pattern extracted from the data temporal stack using a spatially aware classifier. Moreover, the use of ancillary data, easily available for urban areas, further improves the accuracy by discarding uninteresting parts of the scene and forcing homogeneous classification within city blocks to avoid "class-blurring" effects consequential to the window-based computation of relevant measures. The procedure is validated based on results for the town of Bam, Iran, and compared with ground-based survey maps
Boosting social network connectivity with link revival

Online social networking platforms have become a popular channel of communications among people. However, most people can only keep in touch with a limited number of friends. This phenomenon results in a low-connectivity social network in terms of communications, which is inefficient for information propagation and social engagement. In this paper, we introduce a new recommendation service, called link revival, that suggests users to re-connect with their old friends, such that the resulted connection will improve the social network connectivity. To achieve high connectivity improvement under the dynamic social network evolvement, we propose a graph prediction-based recommendation strategy, which selects proper candidates based on the prediction of their future behaviors. We then develop an effective model that exploits non-homogeneous Poisson process and second-order self-similarity in prediction. Through comprehensive experimental studies on two real datasets (Phone Call Network and Facebook Wall-posts), we demonstrate that our proposed approach can significantly increase the social network connectivity, and that the approach outperforms other baseline solutions. The results also show that our solution is more suitable for online social networks like Facebook, partially due to the stronger long range dependency and lower communication costs in the interactions.