Miracle-dz/UniFAR-FTUs huggingface dataset:
A Conjoint Analysis of Online Consumer Satisfaction

The ability to measure the level of customer satisfaction with online shopping is essential in gauging the success and failure of e-commerce. To do so, Internet businesses must be able to determine and understand the values of their existing and potential customers. Hence, it is important for IS researchers to develop and validate a diverse array of metrics to comprehensively capture the attitudes and feelings of online customers. What factors make on-line shopping appealing to customers? What customer values take priority over others? This study's purpose is to answer these questions, examining the role of several technology, shopping, and product factors on online customer satisfaction. This is done using a conjoint analysis of consumer preferences based on data collected from 188 young consumers. Results indicate that the three most important attributes to consumers for online satisfaction are privacy (technology factor), merchandising (product factor), and convenience (shopping factor). These are followed by trust, delivery, usability, product customization, product quality, and security. Implications of these findings are discussed and suggestions for future research are provided. 1. Introduction Internet commerce involves the sale and purchase of products and services over the Internet [Keeney 1999]. It was touted to have massive sales potential, with previous expectations of over $1 trillion by 2002 [Burke 1997; Mehler et al. 1997]. Yet, these expectations have fallen well short of the $1 trillion estimate, with the U.S. Census Bureau reporting that U.S. e-commerce sales in 2002 equaled only $43.5 billion and $70 billion in 2003. However, online spending is on the rise. Retail e-commerce sales in the second quarter of 2004 were approximately $15.7 billion, an increase of 23.1 percent from the second quarter of 2003 (U.S. Census Bureau 2003). E-commerce sales in the second quarter of 2004 accounted for 1.7 percent of total sales, while in the second quarter of 2003 e-commerce sales were 1.5 percent of total sales (U.S. Census Bureau 2003). Given the continual rise in online spending and its increasing influence on total retail sales in the U.S. further exploration of per person spending patterns is warranted. Clearly, consumers must be satisfied with their e-commerce shopping experience to acquire more goods and services on-line. Given the need to understand what users want in a Web site [Straub & Watson 2001], it is important for IS researchers to develop and validate a diverse array of metrics to comprehensively capture the attitudes and feelings of online …
Impact of patient involvement in mental health research: longitudinal study

Background It is deemed good practice to involve patients routinely in research but no study has investigated the practical benefits, particularly to successful recruitment. Aims To identify whether patient involvement is associated with study success. Method All studies listed on the Mental Health Research Network (MHRN) portfolio database (n = 374) were interrogated using logistic regression, ANOVA and Pearson's correlation to identify associations with study characteristics, funding bodies and recruitment success. Results Patient involvement increased over time although in some areas of research it was limited. Some funders, especially the National Institute for Health Research (NIHR), had more associated patient involvement than others. Studies that involved patients to a greater extent were more likely to have achieved recruitment targets (χ2 = 4.58, P<0.05), defined as reaching at least 90% of the target. Conclusions This is the first time associations with study success have been identified for patient involvement. Researchers might now consider ways to involve patients more comprehensively as this is associated with study success. Further research is needed to explore this finding.
Organ Preservation in Rectal Cancer: The Patients' Perspective

Organ preservation after a clinical complete response to radiochemotherapy is currently one of the most discussed topics in the management of rectal cancer. However, the patients' perspective has only been poorly studied so far. In this multicenter study, we examined 49 patients with locally advanced rectal cancer. The willingness to participate in an organ preservation study and the acceptance of the associated aspects such as intensified radiochemotherapy protocols, the need for close follow-up examinations and local regrowth rates were assessed. Attitudes were correlated with baseline quality of life parameters and psychological scales for “fear of progression”, “locus of control”, “depression”, and the “willingness to take risks”. A total of 83% of patients would consider the deferral of surgery in case of a clinical complete response (cCR). Three monthly follow-up studies and a 25% local regrowth rate are considered acceptable by 95% and 94% respectively. While 41% would be willing to exchange cure rates for a non-operative treatment strategy, a potentially more toxic radiochemotherapy in order to increase the probability of a cCR was the aspect with the lowest acceptance (55%). Psychological factors, in particular “locus of control” and “willingness to take risks”, influenced patient preferences regarding most of the assessed parameters. While in general a broad acceptance of an organ-preserving treatment can be expected, patient preferences and concerns regarding different aspects of this strategy vary widely and require specific consideration during shared decision making.
Sup norms of newforms on $GL_2$ with highly ramified central character

Recently, the problem of bounding the sup norms of $L^2$-normalized cuspidal automorphic newforms $\phi$ on $GL_2$ in the level aspect has received much attention. However at the moment non-trivial upper bounds are only available either if the level is squarefree or the character $\chi$ of $\phi$ is not too highly ramified. In this paper, we establish a non-trivial upper bound in the level aspect for general $\chi$. When $\chi$ is highly ramified, our estimate improves on the previous upper bounds obtained by Saha. If the level $N$ is a square, our result reduces for any $\chi$ to $$\|\phi\|_\infty \ll N^{\frac14+\epsilon},$$ at least under the Ramanujan Conjecture (which is known for holomorphic cusp forms). In particular, when $\chi$ has conductor $N$ (i.e., $\chi$ is maximally ramified), this matches a lower bound due to Templier and our result is essentially optimal in this case.
Audiovisual Simultaneity Judgment and Rapid Recalibration throughout the Lifespan

Multisensory interactions are well established to convey an array of perceptual and behavioral benefits. One of the key features of multisensory interactions is the temporal structure of the stimuli combined. In an effort to better characterize how temporal factors influence multisensory interactions across the lifespan, we examined audiovisual simultaneity judgment and the degree of rapid recalibration to paired audiovisual stimuli (Flash-Beep and Speech) in a sample of 220 participants ranging from 7 to 86 years of age. Results demonstrate a surprisingly protracted developmental time-course for both audiovisual simultaneity judgment and rapid recalibration, with neither reaching maturity until well into adolescence. Interestingly, correlational analyses revealed that audiovisual simultaneity judgments (i.e., the size of the audiovisual temporal window of simultaneity) and rapid recalibration significantly co-varied as a function of age. Together, our results represent the most complete description of age-related changes in audiovisual simultaneity judgments to date, as well as being the first to describe changes in the degree of rapid recalibration as a function of age. We propose that the developmental time-course of rapid recalibration scaffolds the maturation of more durable audiovisual temporal representations.
Learning Representations for Predicting Future Activities

Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics. In this work, we address future prediction at the abstract level of activities. We propose a network module for learning embeddings of the environment's dynamics in a self-supervised way. To take the ambiguities and high variances in the future activities into account, we use a multi-hypotheses scheme that can represent multiple futures. We demonstrate the approach by classifying future activities on the Epic-Kitchens and Breakfast datasets. Moreover, we generate captions that describe the future activities
Probing the cold magnetised Universe with SPICA-POL (B-BOP)

Abstract Space Infrared Telescope for Cosmology and Astrophysics (SPICA), the cryogenic infrared space telescope recently pre-selected for a ‘Phase A’ concept study as one of the three remaining candidates for European Space Agency (ESA's) fifth medium class (M5) mission, is foreseen to include a far-infrared polarimetric imager [SPICA-POL, now called B-fields with BOlometers and Polarizers (B-BOP)], which would offer a unique opportunity to resolve major issues in our understanding of the nearby, cold magnetised Universe. This paper presents an overview of the main science drivers for B-BOP, including high dynamic range polarimetric imaging of the cold interstellar medium (ISM) in both our Milky Way and nearby galaxies. Thanks to a cooled telescope, B-BOP will deliver wide-field 100–350 $\mu$m images of linearly polarised dust emission in Stokes Q and U with a resolution, signal-to-noise ratio, and both intensity and spatial dynamic ranges comparable to those achieved by Herschel images of the cold ISM in total intensity (Stokes I). The B-BOP 200 $\mu$m images will also have a factor $\sim $30 higher resolution than Planck polarisation data. This will make B-BOP a unique tool for characterising the statistical properties of the magnetised ISM and probing the role of magnetic fields in the formation and evolution of the interstellar web of dusty molecular filaments giving birth to most stars in our Galaxy. B-BOP will also be a powerful instrument for studying the magnetism of nearby galaxies and testing Galactic dynamo models, constraining the physics of dust grain alignment, informing the problem of the interaction of cosmic rays with molecular clouds, tracing magnetic fields in the inner layers of protoplanetary disks, and monitoring accretion bursts in embedded protostars.
Large polar caps for twisted magnetosphere of magnetars

The magnetic field of magnetars may be twisted compared with that of normal pulsars. Previous works mainly discussed magnetic energy release in the closed field line regions of magnetars. For a twisted magnetic field, the field lines will inflate in the radial direction. Similar to normal pulsars, the idea of light cylinder radius is introduced. More field lines will cross the light cylinder and become open for a twisted magnetic field. Therefore, magnetars may have a large polar cap, which may correspond to the hot spot during outburst. Particle flow in the open field line regions will result in the untwisting of the magnetic field. Magnetic energy release in the open field line regions can be calculated. The model calculations can catch the general trend of magnetar outburst: decreasing X-ray luminosity, shrinking hot spot etc. For magnetic energy release in the open field line regions, the geometry will be the same for different outburst in one magnetar.
Target Localization Using Ensemble Support Vector Regression in Wireless Sensor Networks

This paper considers a target localization problem whose goal is to estimate the location of an unknown object. It is one of the key issues in applications of wireless sensor networks (WSNs). With recent advances in fabrication technology, deployment of a large WSNs has become economically feasible. On the other hand, this has caused the curse of dimensionality in applying learning algorithms such as support vector regression (SVR). To handle this, we use an ensemble implementation of SVRs for target localization and validate it experimentally. This paper draws a comparison between the conventional SVR method and the proposed method in terms of the accuracy and robustness. Experimental results show that the prediction performance of the proposed method is more accurate and robust to the measurement noise than conventional SVR predictor.
The Implications of Pricing on Social Learning

We study the implications of endogenous pricing for learning and welfare in the classic herding model. When prices are determined exogenously, it is known that learning occurs if and only if signals are unbounded. By contrast, we show that learning can occur when signals are bounded as long as non-conformism among consumers is scarce. More formally, learning happens if and only if signals exhibit the vanishing likelihood property introduced bellow. We discuss the implications of our results for potential market failure in the context of Schumpeterian growth with uncertainty over the value of innovations.
Dendritic Cell Activating Receptor 1 (DCAR1) Associates With FcεRIγ and Is Expressed by Myeloid Cell Subsets in the Rat

Dendritic cell activating receptor-1 (DCAR1) is a cell-surface receptor encoded by the Antigen Presenting Lectin-like gene Complex (APLEC). We generated a mouse monoclonal antibody against rat DCAR1, and used this to characterize receptor expression and function. Rat DCAR1 was expressed on minor subsets of myeloid cells in lymphoid tissue, but was uniformly expressed at a high level by eosinophils, and at a low level by neutrophils. It was expressed by eosinophils in the peritoneal cavity and the lamina propria of the gut, and by subsets of macrophages or dendritic cells at these sites. Polarization of peritoneal macrophages showed that DCAR1 expression was absent on M1 macrophages, and increased on M2 macrophages. DCAR1 could be expressed as a homodimer and its associated with the activating adaptor protein FcεRIγ. This association allowed efficient phagocytosis of antibody-coated beads. Additionally, cross-linking of DCAR1 on the surface of rat eosinophils lead to production of reactive oxygen species. These data show that DCAR1 is an activating receptor. Its expression on M2 macrophages and eosinophils suggests that it may play a role in the immune response to parasites.
Treadmill exercise prevents diabetes-induced increases in lipid peroxidation and decreases in Cu,Zn-superoxide dismutase levels in the hippocampus of Zucker diabetic fatty rats

In the present study, we investigated the effects of treadmill exercise on lipid peroxidation and Cu,Zn-superoxide dismutase (SOD1) levels in the hippocampus of Zucker diabetic fatty (ZDF) rats and lean control rats (ZLC) during the onset of diabetes. At 7 weeks of age, ZLC and ZDF rats were either placed on a stationary treadmill or made to run for 1 h/day for 5 consecutive days at 16~22 m/min for 5 weeks. At 12 weeks of age, the ZDF rats had significantly higher blood glucose levels and body weight than the ZLC rats. In addition, malondialdehyde (MDA) levels in the hippocampus of the ZDF rats were significantly higher than those of the ZLC rats whereas SOD1 levels in the hippocampus of the ZDF rats were moderately decreased. Notably, treadmill exercise prevented the increase of blood glucose levels in ZDF rats. In addition, treadmill exercise significantly ameliorated changes in MDA and SOD1 levels in the hippocampus although SOD activity was not altered. These findings suggest that diabetes increases lipid peroxidation and decreases SOD1 levels, and treadmill exercise can mitigate diabetes-induced oxidative damage in the hippocampus.
Cartoon Graphics in the Communication of Accounting Information

The relative merits of schematic faces for the communication of multivariate information have been explored in a number of disciplines. Existing studies in the financial environment suggest that they may be superior to conventional methods in both their communications and decision-making qualities. This paper employs an innovative research design to demonstrate the relative usefulness of schematic faces in the failed/non-failed decision-making context compared to accounting statements and financial ratios. An optimum assignment of financial variables to facial characteristics is suggested, one which demonstrates the usefulness of schematic faces as a decision tool in the financial environment. Schematic faces are shown to be processed more quickly and with no loss of accuracy, compared to more traditional means of presenting financial information. Existing applications of schematic faces have been deficient in a number of areas. This study employs a complex research design involving multiple treatments to overcome the confounding problems of subject variability while also addressing the impact of differential priors and differential misclassification costs.
NGC 300 ULX1: spin evolution, super-Eddington accretion, and outflows

NGC 300 ULX1 is an ultraluminous X-ray pulsar, showing an unprecedented spin evolution, from about 126 s to less than 20 s in only 4 yr, consistent with steady mass accretion rate. Following its discovery we have been monitoring the system with Swift and NICER to further study its properties. We found that even though the observed flux of the system dropped by a factor of ≳20, the spin-up rate remained almost constant. A possible explanation is that the decrease in the observed flux is a result of increased absorption of obscuring material due to outflows or a precessing accretion disc.
Stimulating the Dorsolateral Prefrontal Cortex Decreases the Asset Bubble: A tDCS Study

Many studies have discussed the neural basis of asset bubbles. They found that the dorsolateral prefrontal cortex (DLPFC) played an important role in bubble formation, but whether a causal relationship exists and the mechanism of the effect of the DLPFC on bubbles remains unsettled. Using transcranial direct current stimulation (tDCS), we modulated the activity of the DLPFC and investigated the causal relationship between the DLPFC and the asset bubble in the classical learning-to-forecast experiment. 126 subjects were randomly divided into three groups and received different stimulations (left anodal/right cathodal, right anodal/left cathodal, or sham stimulation), respectively. We also conducted a 2-back task before and after stimulation to measure changes in subjects’ cognitive abilities and explore in detail the cognitive mechanism of the effect of DLPFC stimulation on asset bubbles. Based on our results, we found that the bubble of the left anodal/right cathodal stimulation group was significantly smaller than that of the sham stimulation group. In the meantime, subjects performed significantly better in the 2-back task after left anodal/right cathodal stimulation but not right anodal/left cathodal or sham stimulation, which is consistent with their performance in the learning-to-forecast experiment, supporting the cognitive mechanism to some extent. Furthermore, we examined different forecasting rules across individuals and discovered that the left anodal/right cathodal stimulation group preferred the adaptive learning rule, while the sham and right anodal/left cathodal stimulation groups adopted a pure trend-following rule that tended to intensify market volatility aggressively.
Impact of Brain Injury on Processing of Emotional Prosodies in Neonates

Being able to appropriately process different emotional prosodies is an important cognitive ability normally present at birth. In this study, we used event-related potential (ERP) to assess whether brain injury impacts the ability to process different emotional prosodies (happy, fear, and neutral) in neonates; whether the ERP measure has potential value for the evaluation of neurodevelopmental outcome in later childhood. A total of 42 full-term neonates were recruited from the neonatology department of Peking University First Hospital from June 2014 to January 2015. They were assigned to the brain injury group (n = 20) or control group (n = 22) according to their clinical manifestations, physical examinations, cranial images and routine EEG outcomes. Using an oddball paradigm, ERP data were recorded while subjects listened to happy (20%, deviation stimulus), fearful (20%, deviation stimulus) and neutral (80%, standard stimulus) prosodies to evaluate the potential prognostic value of ERP indexes for neurodevelopment at 30 months of age. Results showed that while the mismatch responses (MMRs) at the frontal lobe were larger for fearful than happy prosody in control neonates, this difference was not observed in neonates with brain injuries. This finding suggests that perinatal brain injury may influence the cognitive ability to process different emotional prosodies in neonatal brain; this deficit could be reflected by decreased MMR amplitudes in response to fearful prosody. Moreover, the decreased MMRs at the frontal lobe was associated with impaired neurodevelopment at 30 months old.
Observability of forming planets and their circumplanetary discs II. – SEDs and near-infrared fluxes

Detection of forming planets means detection of the circumplanetary disc (CPD) in reality, since the planet is still surrounded by a disc at this evolutionary stage. Yet, no comprehensive CPD modelling was done in near-infrared (near-IR) wavelengths, where high contrast imaging is a powerful tool to detect these objects. We combined 3D radiative hydrodynamic simulations of various embedded planets with radmc-3d radiative transfer post-processing that includes scattering of photons on dust particles. We made synthetic images for Very Large Telescope NaCo/ERIS in the Ks, L′, and M′ bands as well as examined the spectral energy distributions (SEDs) of discs between 1 μm and 10 cm. We found that the observed magnitudes from the planet’s vicinity will mostly depend on the CPD parameters, not on the planet’s. The CPD is 20–100x brighter than the embedded planet in near-IR. We also show how the CPD parameters, e.g. the dust-to-gas ratio will affect the resulting CPD magnitudes. According to the SEDs, the best contrast ratio between the CPD and circumstellar discs is in sub-mm/radio wavelengths and between 8–33 μm in case if the planet opened a resolvable, deep gap (⁠≥5MJup⁠), while the contrast is particularly poor in the near-IR. Hence, to detect the forming planet and its CPD, the best chance today is targeting the sub-mm/radio wavelengths and the 10-μm silicate feature vicinity. In order to estimate the forming planet’s mass from the observed brightness, it is necessary to run system specific disc modelling.
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation

Existing Rademacher complexity bounds for neural networks rely only on norm control of the weight matrices and depend exponentially on depth via a product of the matrix norms. Lower bounds show that this exponential dependence on depth is unavoidable when no additional properties of the training data are considered. We suspect that this conundrum comes from the fact that these bounds depend on the training data only through the margin. In practice, many data-dependent techniques such as Batchnorm improve the generalization performance. For feedforward neural nets as well as RNNs, we obtain tighter Rademacher complexity bounds by considering additional data-dependent properties of the network: the norms of the hidden layers of the network, and the norms of the Jacobians of each layer with respect to all previous layers. Our bounds scale polynomially in depth when these empirical quantities are small, as is usually the case in practice. To obtain these bounds, we develop general tools for augmenting a sequence of functions to make their composition Lipschitz and then covering the augmented functions. Inspired by our theory, we directly regularize the network's Jacobians during training and empirically demonstrate that this improves test performance.