Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust and stable road model

In this paper a robust and stable model for road detection and road following in traffic scenes is proposed. Scene analysis consists of an initial phase, in which objects are recognized for the first time, and a phase of object tracking with simultaneous object recognition. Road surface analysis is done by means of an explicit model for the road shape that is adjusted stepwise to image regions. In the tracking phase the adjusted model is used for robust model-based segmentation of the road surface. For a reliable analysis of scenes containing obstacles, the system is equipped with a look-ahead mechanism.
A general purpose simulation environment for neural models

Current interest in neural networks has produced a diverse set of algorithms and architectures that vary in connectivity pattern, temporal behavior, update rules, and convergence properties. We have designed a flexible simulation system that can support the implementation of a wide range of neural network approaches. The UCLA-SFINX simulator is especially suited for the exploration of structured, irregular, and layered connectivity patterns. Func tions, such as those in early vision, are modeled using the regular connectivity of center/surround antagonistic receptive fields and can be implemented as the difference of concentric gaussians. Higher level cognitive functions, such as supervised and unsuper vised learning, have more irregular, dynamic connectivity structures and update mechanisms that are also supported. To visualize weight spaces, input/output training sets, image data, or other network characteristics, SFINX provides an X- windows based graphical output that assists in rapidly assessing the consequences of altering connectivity patterns, parameter tuning, and other experiments.
Immunogenicity and protective efficacy against Salmonella C2-C3 infection in mice immunized with a glycoconjugate of S. Newport Core-O polysaccharide linked to the homologous serovar FliC protein

ABSTRACT Nontyphoidal Salmonella (NTS) are important human enteric pathogens globally. Among the different serovars associated with human NTS disease, S. Newport (a serogroup C2-C3 Salmonella) accounts for a measurable proportion of cases. However, to date there are no licensed human NTS vaccines. NTS lipopolysaccharide-associated O polysaccharides are virulence factors and protective antigens in animal models. As isolated molecules, bacterial polysaccharides are generally poorly immunogenic, a limitation overcome by conjugation to a protein carrier. We report herein the development of a candidate serogroup C2-C3 glycoconjugate vaccine based on S. Newport Core-O polysaccharide (COPS) and phase 1 flagellin (FliC). S. Newport COPS and FliC were purified from genetically engineered reagent strains, and conjugated at the polysaccharide reducing end to FliC protein lysines with thioether chemistry. S. Newport COPS:FliC immunization in mice improved anti-polysaccharide immune responses, generated high anti-FliC IgG titers, and mediated robust protection against challenge with both the homologous serovar as well another serogroup C2-C3 serovar (S. Muenchen). Analyses of S. Newport COPS:FliC induced sera found that the anti-COPS IgG antibodies were specific for serogroup C2-C3 lipopolysaccharide, and could promote bactericidal killing by complement and uptake into phagocytes. These preclinical studies establish the protective capacity of serogroup C2-C3 OPS glycoconjugates, and provide a path forward for the development of a multivalent Salmonella vaccine for humans that includes serogroup C2-C3.
Efficient differentiable programming in a functional array-processing language

We present a system for the automatic differentiation (AD) of a higher-order functional array-processing language. The core functional language underlying this system simultaneously supports both source-to-source forward-mode AD and global optimisations such as loop transformations. In combination, gradient computation with forward-mode AD can be as efficient as reverse mode, and that the Jacobian matrices required for numerical algorithms such as Gauss-Newton and Levenberg-Marquardt can be efficiently computed.
Periosteal Electrical Dry Needling as an Adjunct to Exercise and Manual Therapy for Knee Osteoarthritis

Objectives: To compare the effects of adding electrical dry needling into a manual therapy (MT) and exercise program on pain, stiffness, function, and disability in individuals with painful knee osteoarthritis (OA). Materials and Methods: In total, 242 participants (n=242) with painful knee OA were randomized to receive 6 weeks of electrical dry needling, MT, and exercise (n=121) or MT and exercise (n=121). The primary outcome was related-disability as assessed by the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index at 3 months. Results: Individuals receiving the combination of electrical dry needling, MT, and exercise experienced significantly greater improvements in related-disability (WOMAC: F=35.504; P<0.001) than those receiving MT and exercise alone at 6 weeks and 3 months. Patients receiving electrical dry needling were 1.7 times more likely to have completely stopped taking medication for their pain at 3 months than individuals receiving MT and exercise (OR, 1.6; 95% confidence interval, 1.24-2.01; P=0.001). On the basis of the cutoff score of ≥5 on the global rating of change, significantly (&khgr;2=14.887; P<0.001) more patients (n=91, 75%) within the dry needling group achieved a successful outcome compared with the MT and exercise group (n=22, 18%) at 3 months. Effect sizes were large (standardized mean differences >0.82) for all outcome measures in favor of the electrical dry needling group at 3 months. Discussion: The inclusion of electrical dry needling into a MT and exercise program was more effective for improving pain, function, and related-disability than the application of MT and exercise alone in individuals with painful knee OA. Level of Evidence: Level 1b—therapy. Prospectively registered February 10, 2015 on www.clinicaltrials. gov (NCT02373631).
Gamified Workshops as Drivers for Attitudinal and Behavioral Shifts toward Sustainable Business Practices: The Role of Enjoyment, Curiosity and External Regulation

Gamification has recently gained a great deal of attention in various research communities. The application of game elements in non-game contexts has shown a lot of potential and the expectations of researchers and businesses are high. However, few studies exist that empirically test the effectiveness of gamification applications in business settings. To fill this gap, we present results from workshops that promoted environmentally friendly business practices. 261 individuals participated in a study in which various gamification elements were applied. Our findings illustrate that enjoyment and curiosity, both of which are strongly fostered by gamification elements, exert a significant influence on individuals’ attitudes and subsequently their behavioral intentions to adopt sustainable business practices. In contrast, the impact of external regulation turned out to be insignificant. The findings highlight the important role of enjoyment and curiosity for a sustainable change and bear important implications for academics and practitioners.
How to decompress the Pressure - The moderating Effect of IT Flexibility on the negative Impact of Governmental Pressure on Business Agility

In times of digital transformation banks need to behave agile and increase their speed in IT. At the same time, they are bound by an increasing number of regulatory rules at an increasing pace that force them to act carefully. Since governments frequently introduce new regulatory terms, especially in the finance sector, regulation is a changing phenomenon itself, which forces banks to adjust and change their systems constantly. To manage these challenges, we argue that successful businesses need to have a flexible IT architecture in place. This should enable them to update and reconfigure their systems in a cost effective and prompt manner. By doing this, they should be able to compensate for the regulatory pressure and remain agile. Based on an analysis of 119 survey results, we find that business agility is indeed lower for higher regulatory pressure and that this effect is mitigated by a flexible IT.
An Investigation of the Effects of Testosterone and Behavioral Expressions of Pain on Sex/Gender Differences in Pain Perception

Research indicates that women are more susceptible to pain than men, but the reason for this difference is unclear. While estrogen and progesterone have been implicated, testosterone has not received adequate consideration in the literature. Additionally, incorporating behavioral expressions, or exaggerations, of pain as an important aspect of pain perception is receiving increasing attention. The current study examined the role of testosterone in female pain expression and perception via the cold pressor test. Following all participant exclusions, 46 healthy participants (32 women) provided saliva samples for testosterone analysis using enzyme-linked immunosorbent assay before and after rating their pain during the cold pressor test. Participants used a visual analog scale to indicate how the 2℃ water was perceived, ranging from “worst pain imaginable” to “no pain. ” The researcher also noted whether a participant displayed overt behavioral expressions of pain such as jumping and cursing. The results revealed that men reported lower visual analog scale scores than women, indicating less perceived pain. A subgroup of women who displayed overt behavioral responses to pain seemed to be driving this sex/gender difference. It was expected that this subgroup of females would have corresponding changes in testosterone that would further explain the observed sex/gender differences, but this was not supported. Collectively, these data add to the previous literature investigating sex/gender differences in pain perception and highlight the importance of studying overt behavioral expressions of pain. Testosterone may alter this behavior and subsequent pain perception, but the contributions of testosterone are likely subtle and were not detected in this study.
"Do You Plead Connected?" - Understanding How Lawyers Deal With Constant Connectivity

Being available and responsive has become an imperative to accomplish the complex work of knowledge workers and to adequately satisfy today’s business needs. As a consequence, individuals are required to adopt strategies to cope with increasing connectivity levels. We conducted a Q methodological study among 34 lawyers from Switzerland and Austria to examine the adoption of different strategies for dealing with constant connectivity. Our findings reveal four ICT user types, whereof three types successfully deploy a coping strategy while one type fails. We observe that specific determinants such as the work environment, the hierarchical position, the perceived autonomy as well as personality traits have substantial influence on the adoption of a coping strategy.
Videoconferencing using spatially varying sensing with multiple and moving foveae

A new method for videoconferencing using the concept of spatially varying sensing is introduced. Various techniques are discussed for combining information obtained from multiple points-of-interest (foveae) in an image. A fovea can be used to follow a moving object of interest as well. A fast videoconferencing prototype for desktop computers is also described.
Sharpening the Ethnographer's Toolkit: Introducing the Freelist Method to Information Systems Research

Ethnography has been presented as a promising research method for information systems researchers. However, IS research using ethnographic techniques still remains scant. We believe this has occurred for four primary reasons: (1) the techniques needed to conduct effective ethnographic research are often discussed in vague detail; (2) data collection in ethnographic studies is perceived as unfocused and unsystematic; (3) ethnographic studies are perceived as highly time consuming and thus impractical; and (4) IS researchers may not be well-versed in understanding how to make sense of the findings of an ethnographic analysis. In this paper, we address these constraints by introducing a well-established ethnographic method called freelisting to ethnographic research in IS. Specifically, we discuss the essence of freelisting, how it fits into ethnography, and provide an example of how to conduct and analyze a freelist in IS. The benefits of freelisting for IS researchers are also explained.
Linear Algebraic Beamforming Design for Multiuser MISO Interference Channels: A Reduction in Search Space Dimension

Near-optimal transmit beamformers are designed for multiuser multiple-input single-output interference channels with slowly time-varying block fading. The main contribution of this article is to provide a method for deriving closed-form solutions to effective beamforming in both low and high signal-to-noise ratio regimes. The proposed method basically leverages side information obtained from the channel correlation between adjacent coding blocks. More specifically, our methodology is based on a linear algebraic approach, which is more efficient than the optimal scheme based on the Gaussian input in the sense of reducing the average number of search space dimensions for designing the near-optimal transmit beamformers. The proposed method is shown to exhibit near-optimal performance via computer simulations in terms of the average sum-rate.
Inverted Encoding Models Assay Population-Level Stimulus Representations, Not Single-Unit Neural Tuning

Inverted encoding models (IEMs) are a powerful tool for reconstructing population-level stimulus representations from aggregate measurements of neural activity (e.g., fMRI or EEG). In a recent report, Liu et al. (2018) tested whether IEMs can provide information about the underlying tuning of single units. Here, we argue that using stimulus reconstructions to infer properties of single neurons, such as neural tuning bandwidth, is an ill-posed problem with no unambiguous solution. Instead of interpreting results from these methods as evidence about single-unit tuning, we emphasize the utility of these methods for assaying population-level stimulus representations. These can be compared across task conditions to better constrain theories of large-scale neural information processing across experimental manipulations, such as changing sensory input or attention. Neuroscience methods range astronomically in scale. In some experiments, we record subthreshold membrane potentials in individual neurons, while in others we measure aggregate responses of thousands of neurons at the millimeter scale. A central goal in neuroscience is to bridge insights across all scales to understand the core computations underlying cognition (Churchland and Sejnowski, 1988). However, inferential problems arise when moving across scales: single-unit response properties cannot be inferred from fMRI activation in single voxels, subthreshold membrane potential cannot be inferred from extracellular spike rate, and the state of single ion channels cannot be inferred from intracellular recordings. These are all examples of an inverse problem in which an observation at a larger scale is consistent with an enormous number of possible observations at a smaller scale. Recent analytical advances have circumvented challenges inherent in inverse problems by instead transforming aggregate signals from their native “measurement space” (e.g., activation pattern across fMRI voxels) into a …
Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning

Bitcoin is a cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an entity’s real-world identity is hidden behind a pseudonym, a so-called address. Therefore, Bitcoin is widely assumed to provide a high degree of anonymity, which is a driver for its frequent use for illicit activities. This paper presents a novel approach for reducing the anonymity of the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities. We utilised a sample of 434 entities (with ≈ 200 million transactions), whose identity and type had been revealed, as training set data and built classifiers differentiating among 10 categories. Our main finding is that we can indeed predict the type of a yet-unidentified entity. Using the Gradient Boosting algorithm, we achieve an accuracy of 77% and F1-score of ≈ 0.75. We discuss our novel approach of Supervised Machine Learning for uncovering Bitcoin Blockchain anonymity and its potential applications to forensics and financial compliance and its societal implications, outline study limitations and propose future research directions.
Validity and test–retest reliability of the six-spot step test in persons after stroke

ABSTRACT Background and Purpose: After stroke, asymmetric weight distribution is common with decreased balance control in standing and walking. The six-spot step test (SSST) includes a 5-m walk during which one leg shoves wooden blocks out of circles marked on the floor, thus assessing the ability to take load on each leg. The aim of the present study was to investigate the convergent and discriminant validity and test–retest reliability of the SSST in persons with stroke. Methods: Eighty-one participants were included. A cross-sectional study was performed, in which the SSST was conducted twice, 3–7 days apart. Validity was investigated using measures of dynamic balance and walking. Reliability was assessed using intraclass correlation coefficient, standard error of the measurement (SEM), and smallest real difference (SRD). Results: The convergent validity was strong to moderate, and the test–retest reliability was good. The SEM% was 14.7%, and the SRD% was 40.8% based on the mean of four walks shoving twice with the paretic and twice with the non-paretic leg. Conclusion: Values on random measurement error were high affecting the use of the SSST for follow-up evaluations but the SSST can be a complementary measure of gait and balance.
Title : Field evidences for the positive effects of aerosols on tree growth Running head : Trees grow faster under aerosol conditions

Theoretical and eddy-covariance studies demonstrate that aerosol-loading stimulates canopy photosynthesis, but field evidence for the aerosol effect on tree growth is limited. Here we measured in-situ daily stem growth rates of aspen trees under a wide range of aerosol-loading in China. The results showed that daily stem growth rates were positively correlated with aerosol-loading, even at exceptionally high aerosol levels. Using structural equation modelling analysis, we showed that variations in stem growth rates can be largely attributed to two environmental variables co-varying with aerosol loading: diffuse fraction of radiation and vapor pressure deficit (VPD). Furthermore, we found that these two factors influence stem growth by influencing photosynthesis from different parts of canopy. By using field observations and a mechanistic photosynthesis model, we demonstrate that photosynthetic rates of both sun and shade leaves increased under high aerosol-loading conditions but for different reasons. For sun leaves, the photosynthetic increase was primarily attributed to the concurrent lower VPD; for shade leaves, the positive aerosol effect was tightly connected with increased diffuse light. Overall, our study provides the first field-evidence of increased tree growth under high aerosol loading. We highlight the importance of understanding biophysical mechanisms of aerosol-meteorology interactions, and incorporating the different pathways of aerosol effects into earth system models to improve the prediction of large-scale aerosol impacts, and the associated vegetation-mediated climate feedbacks.
Understanding the Adoption of Smart Community Services: Perceived Usefulness, Enjoyment, and Affective Community Commitment

Smart community is an emerging form of community that provides various convenient services (smart community services (SCS)) through smart community platform to community residents. However, in practice, residents have limited SCS acceptance, which deserves to be further investigated in the literature. This study investigates the SCS adoption of residents by integrating technological belief factors (perceived usefulness and enjoyment), and social influence factor (affective community commitment). A survey of 191 residents identifies perceived usefulness, perceived enjoyment, and affective community commitment as important determinants of SCS adoption. Affective community commitment weakens the effect of perceived enjoyment yet strengthen the effect of perceived usefulness on SCS adoption. Our study fills the research gap on smart community as well as enriches the IT acceptance literature. This study also offers practical recommendations that can aid practitioners in conducting smart community programs.
Efficacy of a Calcium Sucrose Phosphate Based Toothpaste in Elevating the Level of Calcium, Phosphate Ions in Saliva and Reducing Plaque: A Clinical Trial

Aim: To evaluate and compare the efficacy of “calcium sucrose phosphate” (CaSP) toothpaste (Enafix 5%) with ordinarily used calcium, phosphate-containing toothpaste in elevating the level of calcium, phosphate ions in saliva. Secondary aims were to evaluate substantivity and plaque-reducing ability of CaSP toothpaste. Materials and Methods: Thirty study participants of age group 6–13 years were divided into two groups: Group X (Control group) was made to continue brushing with their regularly used calcium, phosphate-containing toothpaste and Group Y (Test group) was allotted CaSP toothpaste. 1 ml of unstimulated saliva was periodically collected from both groups to determine any alteration in the salivary calcium, phosphate level. Parameters such as substantivity and plaque-reducing ability of CaSP toothpaste were also evaluated. Salivary mineral's intergroup comparison was evaluated by Student's t-test while its intragroup comparison along with the plaque amount variation in Group Y was evaluated by ANOVA and Tukey's post hoc test. Results: Group Y showed an increase in the salivary calcium level though not statistically significant. The increase was pronounced in samples collected on day 1. Group Y showed a consistent level of calcium, phosphate in samples collected immediately and 6 h postbrushing, indicating its substantivity. In addition, Group Y had an impact in reducing the plaque level when the 1st-month plaque score was compared with the 12th-month score. Conclusion: CaSP leads to an increase in the salivary calcium level though it was not statistically significant. Supervised brushing and dietary habits showed a positive effect on both the groups. CaSP toothpaste also showed substantivity and plaque-reducing ability.
High performance computing for land cover dynamics

Presents the overall goals of the authors' research program on the application of high performance computing to remote sensing applications, specifically applications in land cover dynamics. This involves developing scalable and portable programs for a variety of image and map data processing applications, eventually integrated with new models for parallel I/O of large scale images and maps. After an overview of the multiblock PARTI run time support system, the authors explain extensions made to that system to support image processing applications, and then present an example involving multiresolution image processing. Results of running the parallel code on both a TMC CM5 and an Intel Paragon are discussed.