Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure of a growing accretionary prism, Hikurangi margin, New Zealand

The Hikurangi margin of eastern North Island, New Zealand, represents the feather edge of the Indian plate at its convergent boundary with the subducting Pacific plate. A migrated seismic reflection profile across this margin clearly displays the structural evolution of an accretionary prism. A 25-km-wide band of “protothrusts” is delineated between the toe of the slope and a converging seamount; this illustrates an early stage in the seaward propagation of a deformation front. Landward-tilted trench-slope basins are separated by ridges that have clearly defined thrusts, which appear to sole out at a decollement. The decollement continues at an angle of only 3° beneath the 150-km-wide margin to a depth of 14 km near the coast where it coincides with an onshore zone of high seismicity.
Assessing the utility of lidar remote sensing technology to identify mule deer winter habitat

Winter habitat for mule deer (Odocoileus hemionus) is a critical concern throughout interior British Columbia, Canada. In winter, mule deer require a food source of twigs and woody browse and face significant winter snow cover. A range of studies have established that good winter range for mule deer reduces the impact of a negative energy balance by providing adequate food, good vegetative cover, and shallow snow. Generally, sites with old Douglas-fir and moderate to high canopy cover on warmer aspects and moderately steep slopes are preferred, resulting in a suite of structural stand conditions, which can be used to map mule deer winter range habitat within the interior Douglas-fir range. The increased availability of light detection and ranging (lidar) data to management agencies and the recent adoption of lidar technology by forestry agencies allow us to assess the capacity of this technology to map some variables important to winter mule deer habitat suitability, using criteria similar to those defined using conventional aerial photography. Results indicate that lidar-derived solar radiation regime, elevation, and overstorey cover are all useful attributes in decision-tree models relating lidar to conventionally derived descriptors of mule deer winter habitat. These lidar-derived models describe up to 75% of the variance in overall stand structure and confirm that this technology is a viable tool which can be used to assess habitat throughout this region.
Comparative study on safety, efficacy, and midterm results of balloon mitral valvotomy performed with triple lumen and double lumen mitral valvotomy catheters

The triple lumen Inoue balloon is routinely used for Balloon Mitral Valvotomy (BMV) in India. Its major limitation is the high cost. The double lumen Accura balloon is less expensive, making it an attractive alternative in the developing countries. The study was meant to assess the safety, efficacy and midterm results of Accura balloon with respect to the Inoue balloon.
Modeling carryover and anticipation effects for Chinese tone recognition

This paper presents our new approach to model tone coarticulation of Chinese continuous speech for tone recognition. We suggest that coarticulation effects between two neighboring tones are rather unstable, since they may be uni-directional, bi-directional, or none despite of the same phonetic contexts. Instability is suggested due to non-local prosodic events like prosodic phrase boundaries or stress effects. Hence, we propose that context dependent tone models should be estimated according to the exact underlying coarticulation effects. To simplify label work for coarticulation effects, label sets as few as 3 labels are adopted. Also F0 contours of tone nuclei are used to facilitate human to discriminate tone coarticulation effects. A new search algorithm for the output candidates was also proposed to adopt the new modeling method of tone coarticulation effects. Preliminary experiments on a female’s utterances of data corpus HKU96 showed the effectiveness of the new approach.
"Hearing from all sides" How legislative testimony influences state level policy-makers in the United States.

BACKGROUND This paper investigates whether state legislators find testimony influential, to what extent testimony influences policy-makers' decisions, and defines the features of testimony important in affecting policy-makers' decisions. METHODS We used a mixed method approach to analyze responses from 862 state-level legislators in the United States (U.S.). Data were collected via a phone survey from January-October, 2012. Qualitative data were analyzed using a general inductive approach and codes were designed to capture the most prevalent themes. Descriptive statistics and cross tabulations were also completed on thematic and demographic data to identify additional themes. RESULTS Most legislators, regardless of political party and other common demographics, find testimony influential, albeit with various definitions of influence. While legislators reported that testimony influenced their awareness or encouraged them to take action like conducting additional research, only 6% reported that testimony changes their vote. Among those legislators who found testimony influential, characteristics of the presenter (e.g., credibility, knowledge of the subject) were the most important aspects of testimony. Legislators also noted several characteristics of testimony content as important, including use of credible, unbiased information and data. CONCLUSION Findings from this study can be used by health advocates, researchers, and individuals to fine tune the delivery of materials and messages to influence policy-makers during legislative testimony. Increasing the likelihood that information from scholars will be used by policy-makers may lead to the adoption of more health policies that are informed by scientific and practice-based evidence.
The presence of both serotonin 1A receptor (HTR1A) and dopamine transporter (DAT1) gene variants increase the risk of borderline personality disorder

Dysfunction in the dopaminergic and serotonergic neurotransmitter systems has been demonstrated to be important in the etiology of borderline personality disorder (BPD). We investigated the relationship of two BPD risk factors, the HTR1A promoter polymorphism -1019C > G (rs6295) and the dopamine transporter (DAT1) repeat allele, with BPD in a major depressive disorder cohort of 367 patients. Out-patients with major depressive disorder were recruited for two treatment trials and assessed for personality disorders, including BPD. DNA samples were collected and the rs6295 polymorphism was detected with a TaqMan® assay. The DAT1 repeat allele was genotyped using a modified PCR method. The impact of polymorphisms on BPD was statistically analyzed using uncontrolled logistic and multiple logistic regression models. BPD patients had higher frequencies of the DAT1 9,9 (OR = 2.67) and 9,10 (OR = 3.67) genotypes and also those homozygous HTR1A G allele (OR = 2.03). No significant interactions between HTR1A and DAT1 genotypes, were observed; however, an increased risk of BPD was observed for those patients who were either 9,10; G,G (OR = 6.64) and 9,9; C,G (OR = 5.42). Furthermore, the odds of BPD in patients exhibiting high-risk variants of these two genes differed from those of patients in low-risk groups by up to a factor of 9. Our study provides evidence implicating the importance of the serotonergic and dopaminergic systems in BPD and that the interaction between genes from different neurotransmitters may play a role in the susceptibility to BPD.
Meeting the challenges of an aging workforce.

BACKGROUND Demographic, labor market and economic forces are combining to produce increases in the number and percentage of U.S. workers 55 and older. In some ways these workers will be our most skilled and productive employees but in others the most vulnerable. METHODS The literature on aging and work was reviewed, including demographic trends, physical and cognitive changes, safety and performance, work ability, and retirement patterns. RESULTS AND CONCLUSIONS Older workers have more serious, but less frequent, workplace injuries and illnesses than younger ones. There is evidence that many of these problems can be prevented and their consequences reduced by anticipating the physical and cognitive changes of age. Many employers are aware that such efforts are necessary, but most have not yet addressed them. There is a need for implementation and evaluative research of programs and policies with four dimensions: the work environment, work arrangements and work-life balance, health promotion and disease prevention, and social support. Employers who establish age-friendly workplaces that promote and support the work ability of employees as they age may gain in safety, productivity, competitiveness, and sustainable business practices.
A novel data security framework using E-MOD for big data

With the development of various new technologies in the field of network technology and also cloud computing, there is also lots of data that is involved in all of it. Thus the concept of big data is introduced which is not an entirely new technology but an extension to Data Mining. Thus securing this Big Data is both important as well as challenging. Since the size of the data is very large it is not possible to secure the whole of big data. Therefore in this paper we are introducing a Big Data security mechanism wherein we will first select only certain attributes that has a higher value than the rest and secure them, which in turn provides security to the whole of Big Data. Since we are using a selection mechanism, the relevance between the attributes of a dataset is very important. Therefore we focus on two main things-Firstly, securing Big data through protecting valuable information inside. Secondly, it is impossible to protect all big data and its attributes. We consider big data as a single object which has its own attributes. We assume that a attribute which have a higher relevance is more important than other attributes. Then we focus on securing the data using the MOBAT technique. Now we propose a Data masking technique that will protect these attributes. Data masking is a technique in which we replace the original set of data with another set of data that is not real but realistic. The Big Data is masked using a mathematical formula that makes use of modulus operator. Thus through these techniques we are providing security to Big Data.
Recall Memory for Topographic Maps and Natural Terrain: Effects of Experience and Task Performance

Two experiments were conducted to examine the recall of information from natural landscapes and topographic maps. In Experiment 1, the nature of information recalled from photos of landscape scenes by experienced and novice topographic-map readers was influenced by the performance of a map-matching task, but did not vary much as a function of experience with topographic maps. In Experiment 2, the nature of information recalled from topographic maps by experienced topographic- map readers was not influenced by the performance of a scene-matching task, but did vary somewhat as a function of experience with maps. The results are explained by reference to the contexts in which specialized knowledge that develops as part of experience with topographic maps will be activated. Characteristics of this specialized knowledge are discussed, as are proposals for further research on the information-processing that occurs during map use. Memoire de rappel pour les cartes topographiques et le terrain naturel: les effets.
Determination of Lunar physical libration from polar observations in the project ILOM (Japan)

In the frame of the second stage of the Japanese space mission SELENE-2 [1] the project ILOM (Insitu Lunar Orientation Measurement) planned after 2017 year is a kind of instrument for positioning on the Moon. It will be set near the lunar pole and will determine parameters of lunar physical libration by positioning of several tens of stars in the field of view regularly for longer than one year. We found the method which allows determining of libration angles in the node Iσ and in inclination ρ with certain accuracy. It’s shown that libration in longitude τ cannot be determined from observation of polar stars, because polar distance of a star is not sensitive to longitudinal oscillation of a Lunar body.
Absence of Detectable Replication of Human Bocavirus Species 2 in Respiratory Tract

Human bocavirus (HBoV) commonly infects young children and is associated with respiratory disease; disease associations of the divergent HBoV-2 species are unknown. Frequent HBoV-2 detection in fecal samples indicated widespread circulation in the United Kingdom and Thailand, but its lack of detection among 6,524 respiratory samples indicates likely differences from HBoV-1 in tropism/pathogenesis.
Letter of Intent for Experiments at 50 GeV PS of the JPARC

S. Adler, A.O. Bazarko, P. C. Bergbusch, E.W. Blackmore, D.A. Bryman, S. Chen, I-H. Chiang, M.V. Diwan, J. S. Frank, T. Fujiwara, J. S. Haggerty, J. Hu, T. Inagaki, M.M. Ito, D. E. Jaffe, V. Jain, S. Kabe, S. H. Kettell, P. Kitching, M. Kobayashi, T. K. Komatsubara, A. Konaka, Y. Kuno, M. Kuriki, K.K. Li, L. S. Littenberg, J. A. Macdonald, P. D. Meyers, J. Mildenberger, M. Miyajima, N. Muramatsu, T. Nakano, C. Ng, S. Ng, T. Nomura, T. Numao, J.-M. Poutissou, R. Poutissou, G. Redlinger, T. Sato, K. Shimada, T. Shimoyama, T. Shinkawa, F. C. Shoemaker, J. R. Stone, R. C. Strand, S. Sugimoto, Y. Tamagawa, T. Tsunemi, C. Witzig, and Y. Yoshimura
Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT‐8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA‐17

[1] In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties (CPP) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (METEOSAT−8) and the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellites. This paper presents the CPP algorithm and determines if SEVIRI can be used together with AVHRR to build a consistent and accurate data set of cloud optical thickness (COT) and cloud liquid water path (CLWP) over Europe for climate research purposes. After quantifying the differences in 0.6 and 1.6 μm operational calibrated reflectances of SEVIRI and AVHRR, a recalibration procedure is proposed to normalize and absolutely calibrate these reflectances. The effects of recalibration, spatial resolution, and viewing geometry differences on the SEVIRI and AVHRR cloud property retrievals are evaluated. The intercomparison of 0.6 and 1.6 μm operationally calibrated reflectances indicates ∼6 and ∼26% higher reflectances for SEVIRI than for AVHRR. These discrepancies result in retrieval differences between AVHRR and SEVIRI of ∼8% for COT and ∼60% for CLWP. Owing to recalibration these differences reduce to ∼5%, while the magnitude of the median COT and CLWP values of AVHRR decrease ∼2 and ∼60% and the SEVIRI values increase ∼10 and ∼55%, respectively. The differences in spatial resolution and viewing geometry slightly influence the retrieval precision. Thus the CPP algorithm can be used to build a consistent and high-quality data set of SEVIRI and AVHRR retrieved cloud properties for climate research purposes, provided the instrument reflectances are recalibrated, preferably guided by the satellite operators.
Decision theoretic task coordination for a visually-guided interactive mobile robot

In this paper, we present a visually-guided mobile robot that is capable of executing a task requiring complex human-robot interaction (HRI). The robot delivers verbal messages among the inhabitants of an office-like environment. Essential to the robot's robust performance is our behavior-based robot control architecture enhanced with a state of the art decision theoretic planner that takes into account the temporal characteristics of the robot's actions. The decision theoretic layer is based on the partially observable Markov decision process (POMDP) framework allowing us to achieve principled coordination of complex subtasks implemented as robot behaviors/skills. We compute approximate POMDP policies using the randomized point-based value iteration algorithm and we present heuristics for improving its computational efficiency.
Dip-angle Decomposition in Relation with Subsurface Offset Extended Wave-equation Migration

Our proposal provides post-migration techniques for computing angle-domain common-image gathers (CIGs) from seismic images, extended by the subsurface offset, in relation with wave-equation migration methods. In addition to the commonly used decomposition of the scattering-angles, we associate the wave-equation migration with dip-domain image gathers as well. Our methodology suggests a system of Radon transform operators by introducing local transform relations between the subsurface offset image and the angle-domain components. The same subsurface offset extended image is employed to decompose scattering and dip angle CIGs individually, or to decompose a multi-angle CIG by showing simultaneously both angles on the gather's axis. It is our belief that dip-angle information, decomposed by wave-equation migration, would have a great impact in making the scattering-angle reflection coefficient more reliable and noise-free, in addition to the expected acceleration of wave-equation inversion methods.
Attitudinal variables and a possible mediating mechanism for vaccination practice in health care workers of a local hospital in L'Aquila (Italy)

ABSTRACT Active immunization is an important concern for health care workers (HCWs) susceptible subjects and potential sources of infection for patients. However, the vaccine coverage for vaccine preventable diseases (VPDs) is below recommended standards. The aims of the study were to estimate the hospitals' HCWs' susceptibility and vaccination coverage rates for VPDs and to analyze the role of HCWs' attitudes and knowledge as determinants of the immunization practices. A cross-sectional study enrolled 334 HCWs (physicians, nurses, others) at local hospital in L'Aquila (Italy). By means of an anonymous questionnaire, self-report data about history of disease and active vaccination for seasonal influenza, chickenpox, measles-mumps-rubella and hepatitis B were collected, as well as attitudes and knowledge about vaccination in HCWs. The employees showed high levels of susceptibility and insufficient vaccination coverage rates, particularly for influenza. Specific trends were detected for different VPDs across age strata and professional categories, not always consistent with literature. Overall, the level of knowledge about recommended vaccination for HCWs was low, in all categories. The active immunization status against influenza was found the most clearly associated with difference levels in 3 psychometric variables: personal responsibility, beliefs on usefulness and beliefs on risk of vaccination. A mediation mechanism was analyzed between these constructs, and an interesting indirect effect was highlighted for beliefs that could enhance the advantage of increased responsibility for HCWs. Further effort in research is needed to evaluate the black-box of longitudinal intervention studies (education, environmental changes, policies), to improve HCWs immunization.
Sparse localized facial motion dictionary learning for facial expression recognition

This paper presents a new framework for facial motion modeling with applications to facial expression recognition. First, we design sparse localized facial motion dictionaries from dense motion flow data of facial expression image sequences. Regularization based on spatial localized support map in addition to the sparsity constraints enables spatially localized dictionary learning. Proposed localized dictionaries are effective for local facial motion description as well as global facial motion analysis. Experimental results using CK+ database shows promising results for automatic facial expression recognition from motion flow data.
Encoding properties of the mechanosensory neurons in the Johnston's organ of the hawk moth, Manduca sexta

Antennal mechanosensors play a key role in control and stability of insect flight. In addition to the well-established role of antennae as airflow detectors, recent studies have indicated that the sensing of antennal vibrations by Johnston's organs also provides a mechanosensory feedback relevant for flight stabilization. However, few studies have addressed how the individual units, or scolopidia, of the Johnston's organs encode these antennal vibrations and communicate it to the brain. Here, we characterize the encoding properties of individual scolopidia from the Johnston's organs in the hawk moth, Manduca sexta, through intracellular neurophysiological recordings from axons of the scolopidial neurons. We stimulated the flagellum–pedicel joint using a custom setup that delivered mechanical stimuli of various (step, sinusoidal, frequency and amplitude sweeps) waveforms. Single units of the Johnston's organs typically displayed phaso-tonic responses to step stimuli with short (3–5 ms) latencies. Their phase-locked response to sinusoidal stimuli in the 0.1–100 Hz frequency range showed high fidelity (vector strengths>0.9). The neurons were able to encode different phases of the stimulus motion and were also extremely sensitive to small amplitude (<0.05 deg) deflections with some indication of directional tuning. In many cases, the firing frequency of the neurons varied linearly as a function of the stimulus frequency at wingbeat and double wingbeat frequencies, which may be relevant to their role in flight stabilization. Iontophoretic fills of these neurons with fluorescent dyes showed that they all projected in the antennal mechanosensory and motor center (AMMC) area of the brain. Taken together, these results showcase the speed and high sensitivity of scolopidia of the Johnston's organs, and hence their ability to encode fine antennal vibrations.
Research of collaborative filtering recommendation algorithm based on trust propagation model

Traditional collaborative filtering recommendation algorithm is one of the methods to solve the information overloading problem in E-Commerce. However, there are four urgent problems in this algorithm namely data sparse, cold start, attack-resistant and scalability. This paper makes a trust propagation model called TPM; proposes a hybrid index called TS index and a novel collaborative filtering recommendation algorithm called TPCF using TPM and TS index. The results of experiments using the dataset of Epinions.com, a popular ecommerce review website, show that TPCF is more attack-resistant and improves the precision and coverage rate compared with the traditional collaborative filtering recommendation algorithm using Pearson's correlation coefficient. TPCF has a better performance against the traditional collaborative filtering recommendation algorithm on the problems of data sparse, cold start and attack-resistant.
Detection of Viral Proteins in Human Cells Lines by Xeno-Proteomics: Elimination of the Last Valid Excuse for Not Testing Every Cellular Proteome Dataset for Viral Proteins

Cell cultures used routinely in proteomic experiments may contain proteins from other species because of infection, transfection or just contamination. Since infection or contamination may affect the results of a biological experiment, it is important to test the samples for the presence of “alien” proteins. Usually cells are tested only for the most common infections, and most of the existing tests are targeting specific contaminations. Here we describe a three-step procedure for reliable untargeted detection of viral proteins using proteomics data, and recommend this or similar procedure to be applied to every proteomics dataset submitted for publication.