Miracle-dz/UniFAR-FTUs huggingface dataset:
Image quality assessment with manifold and machine learning

A crucial step in image compression is the evaluation of its performance, and more precisely the available way to measure the final quality of the compressed image. In this paper, a machine learning expert, providing a final class number is designed. The quality measure is based on a learned classification process in order to respect the one of human observers. Instead of computing a final note, our method classifies the quality using the quality scale recommended by the UIT. This quality scale contains 5 ranks ordered from 1 (the worst quality) to 5 (the best quality). This was done constructing a vector containing many visual attributes. Finally, the final features vector contains more than 40 attibutes. Unfortunatley, no study about the existing interactions between the used visual attributes has been done. A feature selection algorithm could be interesting but the selection is highly related to the further used classifier. Therefore, we prefer to perform dimensionality reduction instead of feature selection. Manifold Learning methods are used to provide a low-dimensional new representation from the initial high dimensional feature space. The classification process is performed on this new low-dimensional representation of the images. Obtained results are compared to the one obtained without applying the dimension reduction process to judge the efficiency of the method.
PKS 1954–388: RadioAstron Detection on 80,000 km Baselines and Multiwavelength Observations

Abstract We present results from a multiwavelength study of the blazar PKS 1954–388 at radio, UV, X-ray, and gamma-ray energies. A RadioAstron observation at 1.66 GHz in June 2012 resulted in the detection of interferometric fringes on baselines of 6.2 Earth-diameters. This suggests a source frame brightness temperature of greater than 2 × 1012 K, well in excess of both equipartition and inverse Compton limits and implying the existence of Doppler boosting in the core. An 8.4-GHz TANAMI VLBI image, made less than a month after the RadioAstron observations, is consistent with a previously reported superluminal motion for a jet component. Flux density monitoring with the Australia Telescope Compact Array confirms previous evidence for long-term variability that increases with observing frequency. A search for more rapid variability revealed no evidence for significant day-scale flux density variation. The ATCA light-curve reveals a strong radio flare beginning in late 2013, which peaks higher, and earlier, at higher frequencies. Comparison with the Fermi gamma-ray light-curve indicates this followed ~ 9 months after the start of a prolonged gamma-ray high-state—a radio lag comparable to that seen in other blazars. The multiwavelength data are combined to derive a Spectral Energy Distribution, which is fitted by a one-zone synchrotron-self-Compton (SSC) model with the addition of external Compton (EC) emission.
The Narrative-Emotion Process Coding System 2.0: A multi-methodological approach to identifying and assessing narrative-emotion process markers in psychotherapy

Abstract Objective: Recent studies suggest that it is not simply the expression of emotion or emotional arousal in session that is important, but rather it is the reflective processing of emergent, adaptive emotions, arising in the context of personal storytelling and/or Emotion-Focused Therapy (EFT) interventions, that is associated with change. Method: To enhance narrative-emotion integration specifically in EFT, Angus and Greenberg originally identified a set of eight clinically derived narrative-emotion integration markers were originally identified for the implementation of process-guiding therapeutic responses. Further evaluation and testing by the Angus Narrative-Emotion Marker Lab resulted in the identification of 10 empirically validated Narrative-Emotion Process (N-EP) markers that are included in the Narrative-Emotion Process Coding System Version 2.0 (NEPCS 2.0). Results: Based on empirical research findings, individual markers are clustered into Problem (e.g., stuckness in repetitive story patterns, over-controlled or dysregulated emotion, lack of reflectivity), Transition (e.g., reflective, access to adaptive emotions and new emotional plotlines, heightened narrative and emotion integration), and Change (e.g., new story outcomes and self-narrative discovery, and co-construction and re-conceptualization) subgroups. To date, research using the NEPCS 2.0 has investigated the proportion and pattern of narrative-emotion markers in Emotion-Focused, Client-Centered, and Cognitive Therapy for Major Depression, Motivational Interviewing plus Cognitive Behavioral Therapy for Generalized Anxiety Disorder, and EFT for Complex Trauma. Results have consistently identified significantly higher proportions of N-EP Transition and Change markers, and productive shifts, in mid- and late phase sessions, for clients who achieved recovery by treatment termination. Conclusions: Recovery is consistently associated with client storytelling that is emotionally engaged, reflective, and evidencing new story outcomes and self-narrative change. Implications for future research, practice and training are discussed.
Data center network placement and service protection in all-optical mesh networks

Cloud services based on data center networks (DCNs) require a transmission infrastructure with high-capacity, low-latency, low-cost and high-availability, which can be offered by survivable optical networks. DCN placement is a fundamental issue in supporting cloud services in optical networks. It concerns not only the cost of providing cloud services, but also the service availability against failures via proper service replicas. In this paper, we jointly optimize DCN placement with service routing and protection to minimize the network cost, while ensuring fast protection of all services against a single link or server failure. An ILP (Integer Linear Program) is formulated to achieve optimal joint design. It integrates p-cycle (preconfigured protection cycle) for fast protection against a single link failure, and DCN replicas and fast service rerouting against a server failure. To make the design more scalable, a two-step heuristic is proposed for large-size networks. The first step separately solves the DCN placement and service routing problem in the failure-free scenario, and the second step takes fast service protection into account. The proposed design is validated by extensive simulation studies.
Resolving nanoparticle growth mechanisms from size- and time-dependent growth rate analysis

Abstract. Atmospheric new particle formation occurs frequently in the global atmosphere and may play a crucial role in climate by affecting cloud properties. The relevance of newly formed nanoparticles depends largely on the dynamics governing their initial formation and growth to sizes where they become important for cloud microphysics. One key to the proper understanding of nanoparticle effects on climate is therefore hidden in the growth mechanisms. In this study we have developed and successfully tested two independent methods based on the aerosol general dynamics equation, allowing detailed retrieval of time- and size-dependent nanoparticle growth rates. Both methods were used to analyze particle formation from two different biogenic precursor vapors in controlled chamber experiments. Our results suggest that growth rates below 10 nm show much more variation than is currently thought and pin down the decisive size range of growth at around 5 nm where in-depth studies of physical and chemical particle properties are needed.
Resolving spatial unfairness problem with reduced-handshaking in underwater acoustic sensor network

Underwater acoustic channel, characterized by long propagation delay and low data rate, suffers from space time uncertainty which causes spatial unfairness in underwater sensor network. In this paper, we propose a spatially fair MAC protocol which divides all the neighbor nodes of a receiving node into two groups by comparing their propagation delay with the average propagation delay of the receiving node. The receiver then permits a single node from each group based on their "earliest transmission time" in such a way that the chosen nodes do not collide with each other. We develop a simulation model to evaluate the performance of our proposed scheme. Simulation results show that the proposed scheme achieves better performance in terms of average RTS collision, network throughput and CTS success rate compared to the existing SF-MAC protocol.
Action recognition with gradient boundary convolutional network

Deep learning features for video action recognition are usually learned from RGB/gray images, image gradients, and optical flows. The single modality of the input data can describe one characteristic of the human action such as appearance structure or motion information. In this paper, we propose a high efficient gradient boundary convolutional network (ConvNet) to simultaneously learn spatio-temporal feature from the single modality data of gradient boundaries. The gradient boundaries represent both local spacial structure and motion information of action video. The gradient boundaries also have less background noise compared to RGB/gray images and image gradients. Extensive experiments are conducted on two popular and challenging action benchmarks, the UCF101 and the HMDB51 action datasets. The proposed deep gradient boundary feature achieves competitive performances on both benchmarks.
Need for uniqueness as a mediator of the relationship between face consciousness and status consumption in China

Strong economic development in China has led to a surge in status consumption as a means of gaining face. In Eastern culture, people interpret uniqueness as status distinction rather than separateness or deviance. This type of uniqueness can be used to meet others' expectations and gain social approval. Thus its relationship with face consciousness and status consumption is to be expected. This study investigates 2 hypotheses: (a) Face consciousness has a positive effect on status consumption and (b) Consumer need for uniqueness mediates the relationship between face consciousness and status consumption. Two-hundred and forty-six working respondents in eastern China completed a survey. Regression analysis of the results supported both hypotheses.
Graph-theoretic spatiotemporal context modeling for video saliency detection

As an important and challenging problem in computer vision, video saliency detection is typically cast as a spatiotemporal context modeling problem over consecutive frames. As a result, a key issue in video saliency detection is how to effectively capture the intrinsical properties of atomic video structures as well as their associated contextual interactions along the spatial and temporal dimensions. Motivated by this observation, we propose a graph-theoretic video saliency detection approach based on adaptive video structure discovery, which is carried out within a spatiotemporal atomic graph. Through graph-based manifold propagation, the proposed approach is capable of effectively modeling the semantically contextual interactions among atomic video structures for saliency detection while preserving spatial smoothness and temporal consistency. Experiments demonstrate the effectiveness of the proposed approach over several benchmark datasets.
Novel adenoviruses detected in British mustelids, including a unique Aviadenovirus in the tissues of pine martens (Martes martes)

Several adenoviruses are known to cause severe disease in veterinary species. Recent evidence suggests that canine adenovirus type 1 (CAV-1) persists in the tissues of healthy red foxes (Vulpes vulpes), which may be a source of infection for susceptible species. It was hypothesized that mustelids native to the UK, including pine martens (Martes martes) and Eurasian otters (Lutra lutra), may also be persistently infected with adenoviruses. Based on high-throughput sequencing and additional Sanger sequencing, a novel Aviadenovirus, tentatively named marten adenovirus type 1 (MAdV-1), was detected in pine marten tissues. The detection of an Aviadenovirus in mammalian tissue has not been reported previously. Two mastadenoviruses, tentatively designated marten adenovirus type 2 (MAdV-2) and lutrine adenovirus type 1 (LAdV-1), were also detected in tissues of pine martens and Eurasian otters, respectively. Apparently healthy free-ranging animals may be infected with uncharacterized adenoviruses with possible implications for translocation of wildlife.
Leucocyte and Platelet‐rich Fibrin: a carrier of autologous multipotent cells for regenerative medicine

The wound healing is a complex process wherein inflammation, proliferation and regeneration evolve according to a spatio‐temporal pattern from the activation of coagulation cascade to the formation of a plug clot including fibrin matrix, blood‐borne cells and cytokines/growth factors. Creating environments conducive to tissue repair, the haemoderivatives are commonly proposed for the treatment of hard‐to‐heal wounds. Here, we explored in vitro the intrinsic regenerative potentialities of a leucocyte‐ and platelet‐rich fibrin product, known as CPL‐MB, defining the stemness grade of cells sprouting from the haemoderivative. Using highly concentrated serum‐based medium to simulate wound conditions, we isolated fibroblast‐like cells (CPL‐CMCs) adhering to plastic and showing stable in vitro propagation, heterogeneous stem cell expression pattern, endothelial adhesive properties and immunomodulatory profile. Due to their blood derivation and expression of CXCR4, CPL‐CMCs have been suggested to be immature cells circulating in peripheral blood at quiescent state until activation by both coagulation event and inflammatory stimuli such as stromal‐derived factor 1/SDF1. Expressing integrins (CD49f, CD103), vascular adhesion molecules (CD106, CD166), endoglin (CD105) and remodelling matrix enzymes (MMP2, MMP9, MMP13), they showed a transendothelial migratory potential besides multipotency. Taken together, our data suggested that a standardized, reliable and economically feasible blood product such as CPL‐MB functions as an artificial stem cell niche that, under permissive conditions, originate ex vivo immature cells that could be useful for autologous stem cell‐based therapies.
Within What Distance Does “Greenness” Best Predict Physical Health? A Systematic Review of Articles with GIS Buffer Analyses across the Lifespan

Is the amount of “greenness” within a 250-m, 500-m, 1000-m or a 2000-m buffer surrounding a person’s home a good predictor of their physical health? The evidence is inconclusive. We reviewed Web of Science articles that used geographic information system buffer analyses to identify trends between physical health, greenness, and distance within which greenness is measured. Our inclusion criteria were: (1) use of buffers to estimate residential greenness; (2) statistical analyses that calculated significance of the greenness-physical health relationship; and (3) peer-reviewed articles published in English between 2007 and 2017. To capture multiple findings from a single article, we selected our unit of inquiry as the analysis, not the article. Our final sample included 260 analyses in 47 articles. All aspects of the review were in accordance with PRISMA guidelines. Analyses were independently judged as more, less, or least likely to be biased based on the inclusion of objective health measures and income/education controls. We found evidence that larger buffer sizes, up to 2000 m, better predicted physical health than smaller ones. We recommend that future analyses use nested rather than overlapping buffers to evaluate to what extent greenness not immediately around a person’s home (i.e., within 1000–2000 m) predicts physical health.
A 0.8-V Resistor-Based Temperature Sensor in 65-nm CMOS With Supply Sensitivity of 0.28 °C/V

A 0.8-V resistor-based CMOS temperature sensor in 65-nm CMOS process with low supply sensitivity is presented. The temperature-to-voltage conversion gain is maximized by utilizing two types of on-chip resistors with positive and negative temperature coefficient. Reusing the resistor sensor frontend as a reference, the voltage generator of the subsequent A/D converter inherently removes the supply dependence of temperature-to-digital conversion. A 10-bit sub-ranging A/D converter employing 5-bit amplifying interpolation D/A converter enables low-voltage and low-noise A/D conversion. Over a range of −45 °C ~ 85 °C, the proposed sensor achieves 0.12 °<inline-formula> <tex-math notation="LaTeX">${\mathrm {C}}_{\mathrm{ rms}}$ </tex-math></inline-formula> temperature resolution with a conversion time of <inline-formula> <tex-math notation="LaTeX">$10~ \mu \text{s}$ </tex-math></inline-formula>. After a 2-point calibration, the sensor achieves an inaccuracy of less than +1.6/−1 °C while consuming 47 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> from 0.8-V supply voltage. Measured supply sensitivity is 0.28 °C/V over 0.6 ~1.2 V, which is one of the lowest ever reported among sub-1-V temperature-to-digital converter designs.
Variation of Care Time Between Nursing Units in Classification-Based Nurse-to-Resident Ratios: A Multilevel Analysis

A validity test was conducted to determine how care level–based nurse-to-resident ratios compare with actual daily care times per resident in Germany. Stability across different long-term care facilities was tested. Care level–based nurse-to-resident ratios were compared with the standard minimum nurse-to-resident ratios. Levels of care are determined by classification authorities in long-term care insurance programs and are used to distribute resources. Care levels are a powerful tool for classifying authorities in long-term care insurance. We used observer-based measurement of assignable direct and indirect care time in 68 nursing units for 2028 residents across 2 working days. Organizational data were collected at the end of the quarter in which the observation was made. Data were collected from January to March, 2012. We used a null multilevel model with random intercepts and multilevel models with fixed and random slopes to analyze data at both the organization and resident levels. A total of 14% of the variance in total care time per day was explained by membership in nursing units. The impact of care levels on care time differed significantly between nursing units. Forty percent of residents at the lowest care level received less than the standard minimum registered nursing time per day. For facilities that have been significantly disadvantaged in the current staffing system, a higher minimum standard will function more effectively than a complex classification system without scientific controls.
Time dependence in perpendicular media with a soft underlayer

In this paper we describe measurements of magnetic viscosity or time dependence in magnetic thin films suitable for use as perpendicular recording media. Generally, such effects cannot be measured using conventional magnetometry techniques due to the presence of a thin (0.1 /spl mu/m) soft underlayer (SUL) in the media necessary to focus the head field. To achieve our results we have developed an ultrastable MOKE magnetometer, the construction of which is described. This has enabled us to measure nominally identical films with and without the presence of the SUL. We find that the presence of the SUL narrows the energy barrier distribution in the perpendicular film increasing the nucleation field (H/sub n/), reducing the coercivity (H/sub c/) and results in an increase in the squareness of the loop. This in turn results in an increase in the magnitude of the viscosity in the region of the H/sub c/ but that the range of fields over which the viscosity occurs is reduced.
Living and controlled polymerization : synthesis, characterization and properties of the respective polymers and copolymers

The living/controlled polymerisation techniques opened new vistas in polymer chemistry. The leading authorities in this field and its pioneers contributed chapters to this collective volume. The controlled polymerisation techniques have enabled preparation of polymers, copolymers, and block copolymers with predetermined molecular weights and narrow polydispersity, in which functional groups or biologically active molecules could be placed at well defined locations. They have also enabled preparation of advanced polymeric structures with precisely determined architectures and improved properties. Moreover, they have provided opportunities for preparation of novel polymeric materials from monomers, which before have not been suitable or accessible for such purposes. Properties of some of these polymeric materials may be significantly different from those of the existing ones. They provide opportunities for new applications. Several patents have already been approved for such speciality applications as, drug delivery, biocompatible surfaces, thermoplastic elastomers, moisture curable sealants, and so on. Many more products, based on polymers fabricated by the living/ controlled polymerisation techniques, will certainly emerge in such specialised areas as, nanotechnology, medical devices, smart polymers, sensors , smart separation technologies, optical fibres and other optical applications, various biomaterials, etc.
Cost efficient subcategory-aware CNN for object detection

In this paper, we propose an accurate and cost efficient deep CNN network for object detection. In contrast to the previous region-based methods like Sub-CNN [1], our detector is almost fully convolutional so that the computation cost can be reduced efficiently. By introducing position-sensitive score maps and exploiting subcategory information, our method is less time consuming while maintaining competitive performance on detecting objects with various scales. In addition, we remove image pyramid used in Sub-CNN to achieve further acceleration. The experimental results show that our approach is 1.3 times faster than Sub-CNN with only 14% number of parameters and archives comparable results on the challenging KITTI dataset. Compared with the state-of-the-art methods for object detection, our approach provides an efficient solution that takes into account both accuracy and speed.
Testing vs. building accounting theory with experimental research: insights from management research

With this conceptual paper, we want to raise scholars' awareness of the underused potential of experiments in accounting research. We refer to research taxonomies from the management discipline to explore the role of experimental research in testing and building accounting theory. Although the contribution of laboratory research to testing theory is well acknowledged, we argue that exploratory experimental research efforts also have the potential to build new theory, pointing at the underused potential of experiments in current accounting research. In doing so, we (i) provide a clear understanding of theory building and theory testing in accounting research; (ii) present a guideline for assessing the degree of theory building and theory testing inherent in any (experimental) study. Furthermore, we argue that an inter-study triangulation aligning experimental and archival methodologies will have the potential to produce results that are robust to internal and external validity concerns, thus advancing accounting theory.