Miracle-dz/UniFAR-FTUs huggingface dataset:
Do IPO Firms Purchase Analyst Coverage with Underpricing?

We examine the links among IPO underpricing, post-IPO analyst coverage, and the likelihood of switching underwriters. Our findings indicate a significant positive relation between underpricing and analyst coverage by the lead underwriter. This positive association is robust to controls for other determinants of underpricing previously documented in the literature and to controls for the endogeneity of underpricing and analyst coverage. In addition, after controlling for other potential determinants of switching underwriters, we find that the probability of switching underwriters between IPO and SEO is negatively related to the unexpected amount of post-IPO analyst coverage. We interpret these findings as consistent with the hypothesis that underpricing is, in part, compensation for expected post-IPO analyst coverage.
Texture classification using a new version of local binary patterns

Among various feature extraction methods for texture classification, Local Binary Patterns and Modified Local Binary Patterns, because of simplicity and classification accuracy, have emerged as one of the most popular ones. LBP has simple implementation, but with increasing the radius of neighborhood, computational complexity will be increased. MLBP cannot classify non uniform textures as well as uniform ones. In this paper a new version of LBP is developed that has less computational complexity than LBP and more classification accuracy than MLBP. The proposed method classifies non uniform textures as well as uniform ones. Classification accuracy on two standard datasets, Brodatz and Outex, indicates efficiency of the proposed approach.
Spatial Decorrelation in Orientation-Selective Cortical Cells

We propose a model for the lateral connectivity of orientation-selective cells in the visual cortex. We study the properties of the input signal to the visual cortex and find new statistical structures that have not been processed in the retino-geniculate pathway. Using the idea that the system performs redundancy reduction of the incoming signals, we derive the lateral connectivity that will achieve this for a set of orientation-selective local circuits, as well as the complete spatial structure of a network composed of such circuits. We compare the results with various physiological measurements.
Model independent information on solar neutrino oscillations

We present the results of a Bayesian analysis of solar neutrino data in terms of nu_e->nu_{mu,tau} oscillations, independent from the Standard Solar Model predictions for the solar neutrino fluxes. We show that such a model independent analysis allows to constraint the values of the neutrino mixing parameters in limited regions around the usual SMA, LMA, LOW and VO regions. Furthermore, there is a strong indication in favor of large neutrino mixing and large values of Delta m^2 (LMA region). We calculate also the allowed ranges of the neutrino fluxes and we show that they are in good agreement with the Standard Solar Model prediction. In particular, the ratio of the 8B flux with its Standard Solar Model prediction is constrained in the interval [0.45,1.42] with 99.73% probability. Finally, we show that the hypothesis of no neutrino oscillations is strongly disfavored in a model independent way with respect to the hypothesis of neutrino oscillations.
Pain Relief in Sows Can Help Reduce Post-Farrowing Activity, Which Could Lead to Reduced Piglet Crushing

and Implications Sows lying on their piglets causing them to be crushed is a major cause of piglet mortality. Crushing may be due to increased sow position changes from pressure sores that develop because of hard flooring in farrowing crates. The objective of this study was to determine if administration of an analgesic would allow sows to lie more restfully. Data collected showed that administration of butorphanol tartrate to sows decreased the number of body position changes. If piglet mortality can be decreased by administration of butorphanol, an analgesic protocol that is simple to conduct can be developed. Alternatively, utilization of more comfortable flooring or an increase in sow body fat may be a more practical solution that will allow the sow to lie more comfortably.
Impacts of Individual Innovativeness on the Acceptance of IT-based Innovations in Health Care Fields

Objectives The purpose of this study is to identify the role of individual innovation to demographic variables for determining IT adoption behaviors. This study also examines the effect of individual innovation on IT adoption behaviors across IT types. Methods To verify the invariant effect of individual innovativeness, two groups of persons working in the health care field were surveyed. The first study subject group was radiologists and their adoption of e-purchasing the second group was emergency rescue crews and their adoption of GPS. Results Adopter categories in innovations (ACI) as the measurement of individual innovation were a significant variable in both studies. Innovative adopters were more likely to use new IT tools than the majority of early adopters, and the early majority was more likely to adopt IT than the laggards. After merging the two data sets into one for testing the role of IT types as a moderator, the significance of ACI did not change, compared to the two separate analyses. In the merged data set, innovative adopters were 2.34 times more likely to be adopters than the early majority. The early majority was 2.32 times more likely to be adopters than laggards. Moreover, there were no moderating effects of IT types. Thus, there were no reversed adoption rates according to levels of ACI and demographic variables. Conclusions ACI has invariant effects on IT adoption behaviors regardless of IT types and demographic differences. To implement a new innovation, understanding individual innovativeness will provide more sophisticated implementation strategies for health care organizations and appropriate education programs for their employees.
Effectiveness of Adolescent Suicide Prevention E-Learning Modules for Gatekeepers : A Randomized Controlled Trial

Objective: This RCT study investigated the effectiveness of an online adolescent suicide prevention program called Mental Health Online which aimed to improve the knowledge and the self-confidence of gatekeepers working with adolescents (12–20 years old). The program consisted of eight short e-learning modules each capturing an important aspect of the process of early recognition, guidance and referral of suicidal adolescents, alongside additional information on the topic of (adolescent) suicide prevention. Method: A total of 190 gatekeepers (ages 21 to 62 years) participated in this study and were randomized to either the experimental group or the waitlist control group. Participants from both groups were assessed three times (pretest, posttest and three month follow-up). The outcome measures of this study were actual knowledge, and participant’s ratings on perceived knowledge and perceived self-confidence using questionnaires developed specifically for this study. Results: The actual knowledge, perceived knowledge, and perceived self-confidence of gatekeepers in the experimental group improved significantly compared to those in the waitlist control group at posttest, and the effects remained significant at three month follow-up. The overall effect sizes were 0.76, 1.20, and 1.02 respectively, across assessments. Conclusions: The findings of this study indicate that online suicide prevention e-learning modules can be an effective educational method to enhance knowledge and self-confidence of gatekeepers with regard to adolescent suicide prevention. Gatekeepers with limited time and resources can benefit from the accessibility, simplicity and flexibility of online trainings. RCT on the effectiveness of the MHO modules 79
A random finite set approach for dynamic occupancy grid maps with real-time application

Grid mapping is a well-established approach for environment perception in robotic and automotive applications. Early work suggests estimating the occupancy state of each grid cell in a robot’s environment using a Bayesian filter to recursively combine new measurements with the current posterior state estimate of each grid cell. This filter is often referred to as binary Bayes filter. A basic assumption of classical occupancy grid maps is a stationary environment. Recent publications describe bottom-up approaches using particles to represent the dynamic state of a grid cell and outline prediction-update recursions in a heuristic manner. This paper defines the state of multiple grid cells as a random finite set, which allows to model the environment as a stochastic, dynamic system with multiple obstacles, observed by a stochastic measurement system. It motivates an original filter called the probability hypothesis density / multi-instance Bernoulli (PHD/MIB) filter in a top-down manner. The paper presents a real-time application serving as a fusion layer for laser and radar sensor data and describes in detail a highly efficient parallel particle filter implementation. A quantitative evaluation shows that parameters of the stochastic process model affect the filter results as theoretically expected and that appropriate process and observation models provide consistent state estimation results.
Compact Aspect Embedding for Diversified Query Expansions

Diversified query expansion (DQE) based approaches aim to select a set of expansion terms with less redundancy among them while covering as many query aspects as possible. Recently they have experimentally demonstrate their effectiveness for the task of search result diversification. One challenge faced by existing DQE approaches is how to ensure the aspect coverage. In this paper, we propose a novel method for DQE, called compact aspect embedding, which exploits trace norm regularization to learn a low rank vector space for the query, with each eigenvector of the learnt vector space representing an aspect, and the absolute value of its corresponding eigenvalue representing the association strength of that aspect to the query. Meanwhile, each expansion term is mapped into the vector space as well. Based on this novel representation of the query aspects and expansion terms, we design a greedy selection strategy to choose a set of expansion terms to explicitly cover all possible aspects of the query.We test our method on several TREC diversification data sets, and show that our method significantly outperforms the state-of-the-art search result diversification approaches.
Exosomes derived from mature dendritic cells increase endothelial inflammation and atherosclerosis via membrane TNF‐α mediated NF‐κB pathway

Whether dendritic cell (DC) derived exosomes play a role in the progression of endothelial inflammation and atherosclerosis remains unclear. Using a transwell system and exosome release inhibitor GW4869, we demonstrated that mature DCs contributed to endothelial inflammation and exosomes were involved in the process. To further confirm this finding, we isolated exosomes from bone marrow dendritic cell (BMDC) culture medium (named DC‐exos) and stimulated human umbilical vein endothelial cell (HUVEC) with these DC‐exos. We observed that mature DC‐exos increased HUVEC inflammation through NF‐κB pathway in a manner similar to that of lipopolysaccharide. After a protein array analysis of exosomes, we identified and confirmed tumour necrosis factor (TNF)‐α on exosome membrane being the trigger of NF‐κB pathway in HUVECs. We then performed an in vivo study and found that the aorta endothelial of mice could uptake intravenously injected exosomes and was activated by these exosomes. After a period of 12 weeks of mature DC‐exos injection into ApoE−/− mice, the atherosclerotic lesions significantly increased. Our study demonstrates that mature DCs derived exosomes increase endothelial inflammation and atherosclerosis via membrane TNF‐α mediated NF‐κB pathway. This finding extends our knowledge on how DCs affect inflammation and provides a potential method to prevent endothelial inflammation and atherosclerosis.
Effect Of Shade, Organic Materials And Varieties On Growth And Production Of Upland Rice

There is a shade factor and low organic matter content of the soil is a problem that needs to be addressed in the development of upland rice cultivation as intercrops in the plantation area. Based on these considerations, then one study that needs to be done is to conduct experiments on the effect of shade factor combined with the the provision of the organic material to the some varieties of upland rice that has been recommended nationally. The objective of experiment is to study the influence of shade, organic materials and varieties on the growth and production of upland rice. This research using experimental design of Split - Split Plot Design with 3 treatment factors and 3 replications or blocks. The first factor is the treatment of shade with 3 levels shade percentage (0%, 20% and 40%). The second factor is the dosage of organic material consists of 3 levels (0 g / polybag, 25 g / polybag, 50 g / polybag and 75 g / polybag). The third factor is the treatment of varieties consists of 4 types of upland rice varieties (Si Kembiri, Situ Patengggang, Situ Bagendit and Tuwoti). The research results showed that the effect of shade on upland rice varieties decrease number of tillers, number of panicles, number of productive grains, grain production per hill of uplnd rice plants and total sugar content of upland rice plants. Effect of organic matter increases number of panicles, number of productive grains, grain production per hill of upland rice plants and total sugar content of upland rice plants. It is known that the the variety of Situ Patenggang provides better growth and production compared with three other varieties (Si Kembiri, Situ Bagendit and Tuwoti) in shaded conditions.
A natural language query interface for searching personal information on smartwatches

Currently, personal assistant systems, run on smartphones and use natural language interfaces. However, these systems rely mostly on the web for finding information. Mobile and wearable devices can collect an enormous amount of contextual personal data such as sleep and physical activities. These information objects and their applications are known as quantified-self, mobile health or personal informatics, and they can be used to provide a deeper insight into our behavior. To our knowledge, existing personal assistant systems do not support all types of quantified-self queries. In response to this, we have undertaken a user study to analyze a set of “textual questions/queries” that users have used to search their quantified-self or mobile health data. Through analyzing these questions, we have constructed a light-weight natural language based query interface - including a text parser algorithm and a user interface - to process the users' queries that have been used for searching quantified-self information. This query interface has been designed to operate on small devices, i.e. smartwatches, as well as augmenting the personal assistant systems by allowing them to process end users' natural language queries about their quantified-self data.
Modeling Model Uncertainty

Recently there has been a great deal of interest in studying monetary policy under model uncertainty. We point out that different assumptions about the uncertainty may result in drastically different robust' policy recommendations. Therefore, we develop new methods to analyze uncertainty about the parameters of a model, the lag specification, the serial correlation of shocks, and the effects of real time data in one coherent structure. We consider both parametric and nonparametric specifications of this structure and use them to estimate the uncertainty in a small model of the US economy. We then use our estimates to compute robust Bayesian and minimax monetary policy rules, which are designed to perform well in the face of uncertainty. Our results suggest that the aggressiveness recently found in robust policy rules is likely to be caused by overemphasizing uncertainty about economic dynamics at low frequencies.
Modelling of Torque-Vectoring Drives for Electric Vehicles: a Case Study

This paper shows some aspects of the implementation of a gear model with losses, nonlinear elasticity and forcing errors in the Modelica language utilizing concept of replaceable functions. Using such gear model for a torque vectoring drive modeling, a case study about a powertrain dynamic behavior in a simplified vehicle model is carried out. The total vehicle model is analyzed in several detail stages of the powertrain reaching from a fixed efficiency with constant spring stiffness to a model using nonlinear losses and nonlinear tooth stiffness. Subsequently, the simulation results of such levels of modeling detail proving tendency to drive line oscillation are presented and discussed.
Recycled metasomatized lithosphere as the origin of the Enriched Mantle II (EM2) end‐member: Evidence from the Samoan Volcanic Chain

An in‐depth Sr‐Nd‐Pb‐He‐Os isotope and trace element study of the EMII‐defining Samoan hot spot lavas leads to a new working hypothesis for the origin of this high 87Sr/86Sr mantle end‐member. Systematics of the Samoan fingerprint include (1) increasing 206Pb/204Pb with time ‐ from 18.6 at the older, western volcanoes to 19.4 at the present‐day hot spot center, Vailulu'u Seamount, (2) en‐echelon arrays in 206Pb/204Pb – 208Pb/204Pb space which correspond to the two topographic lineaments of the 375 km long volcanic chain – this is much like the Kea and Loa Trends in Hawai'i, (3) the highest 87Sr/86Sr (0.7089) of all oceanic basalts, (4) an asymptotic decrease in 3He/4He from 24 RA [ Farley et al., 1992 ] to the MORB value of 8 RA with increasing 87Sr/86Sr, and (5) mixing among four components which are best described as the “enriched mantle”, the depleted FOZO mantle, the (even more depleted) MORB Mantle, and a mild HIMU (high 238U/204Pb) mantle component. A theoretical, “pure” EMII lava composition has been calculated and indicates an extremely smooth trace element pattern of this end‐member mantle reservoir. The standard recycling model (of ocean crust/sediment) fails as an explanation for producing Samoan EM2, due to these smooth spidergrams for EM2 lavas, low 187Os/188Os ratios and high 3He/4He (>8 RA). Instead, the origin of EM2 has been modeled with the ancient formation of metasomatised oceanic lithosphere, followed by storage in the deep mantle and return to the surface in the Samoan plume.
Learning in a flipped english classroom from university students' perspectives

This study set out to explore university students' perceptions of learning English as a foreign language in a flipped classroom. In this study, a flipped learning task was proposed as a means to promote the students' active learning, which required them to watch teacher-selected conversational videos online, transcribe the video content, and make a role-playing video with an assigned partner based on the transcribed text. The results showed that the majority of the students had positive perceptions in terms of the attainment value, intrinsic value, utility value, and satisfaction of the flipped learning task. They considered the flipped learning task facilitative mainly because of the increased use of English in and out of class, the enhanced English learning motivation, and their improved confidence in using English, although a few of them felt that the task was rather difficult and time-consuming. These findings thus offer practical insights for English language teachers.
Sequential male mate choice under sperm competition risk

Lay Summary New research shows that male house mice can be coy too. Male eagerness to mate is a central tenet of sexual selection theory, based on the expectation that male reproductive success is limited mainly by access to females. Here, we show that where sperm supplies are limited, males too can display considerable restraint in mating, targeting reproductive effort toward particular females.
Seasonal changes in Fe species and soluble Fe concentration in the atmosphere in the Northwest Pacific region based on the analysis of aerosols collected in Tsukuba, Japan

Atmospheric iron (Fe) can be a significant source of nutrition for phytoplankton inhabiting remote oceans, which in turn has a large influence on the Earth's climate. The bioavailability of Fe in aerosols depends mainly on the fraction of soluble Fe (= [Fe Sol ]/[Fe Total ], where [Fe Sol ] and [Fe Total ] are the atmospheric concentrations of soluble and total Fe, respectively). However, the numerous factors affecting the soluble Fe fraction have not been fully understood. In this study, the Fe species, chemical composition, and soluble Fe concentrations in aerosols collected in Tsukuba, Japan were investigated over a year (nine samples from December 2002 to October 2003) to identify the factors affecting the amount of soluble Fe supplied into the ocean. The soluble Fe concentration in aerosols is correlated with those of sulfate and oxalate originated from anthropogenic sources, suggesting that soluble Fe is mainly derived from anthropogenic sources. Moreover, the soluble Fe concentration is also correlated with the enrichment factors of vanadium and nickel emitted by fossil fuel combustion. These results suggest that the degree of Fe dissolution is influenced by the magnitude of anthropogenic activity, such as fossil fuel combustion. X-ray absorption fine structure (XAFS) spectroscopy was performed in order to identify the Fe species in aerosols. Fitting of XAFS spectra coupled with micro X-ray fluorescence analysis (μ-XRF) showed the main Fe species in aerosols in Tsukuba to be illite, ferrihydrite, hornblende, and Fe(III) sulfate. Moreover, the soluble Fe fraction in each sample measured by leaching experiments is closely correlated with the Fe(III) sulfate fraction determined by the XAFS spectrum fitting, suggesting that Fe(III) sulfate is the main soluble Fe in the ocean. Another possible factor that can control the amount of soluble Fe supplied into the ocean is the total Fe(III) concentration in the atmosphere, which was high in spring due to the high mineral dust concentrations during spring in East Asia. However, this factor does not contribute to the amount of soluble Fe to a larger degree than the effect of Fe speciation, or more strictly speaking the presence of Fe(III) sulfate. Therefore, based on these results, the most significant factor influencing the amount of soluble Fe in the North Pacific region is the concentration of anthropogenic Fe species such as Fe(III) sulfate that can be emitted from megacities in Eastern Asia.
Lenalidomide in the Treatment of Young Patients with Multiple Myeloma: From Induction to Consolidation/Maintenance Therapy

Multiple myeloma is the second most common hematologic malignancy. It accounts for 20,580 new cancer cases in the USA in 2009, including 11,680 cases in men, 8,900 cases in women, and 10,580 deaths overall. Although the disease remains still incurable, outcomes have improved substantially over recent years thanks to the use of high-dose therapy and the availability of novel agents, such as the immunomodulatory drugs thalidomide and lenalidomide, and the proteasome inhibitor bortezomib. Various trials have shown the advantages linked to the use of novel agents in the transplant and not-transplant settings. In particular, this paper will present an overview of the results achieved with lenalidomide-containing combinations in patients eligible for high-dose therapies, namely, young patients. The advantages obtained should always be outweighed with the toxicity profile associated with the regimen used. Therefore, here, we will also provide a description of the main adverse events associated with lenalidomide and its combination.