Miracle-dz/UniFAR-FTUs huggingface dataset:
A causal model of inclusive innovation for healthcare solutions: a methodological approach to implement a new theoretical vision of social interactions and policies

ABSTRACT This paper is about knowledge production and its application to healthcare solutions oriented towards underprivileged people. Based on the existing literature, we use a different lens to approach the agents, interactions and policies related to the creation, adoption and diffusion of inclusive innovation. We propose a theoretical causal model with which conceptual and practical problems with regard to innovative and inclusive healthcare solutions could be analyzed and assessed, and discuss how public policy could contribute to stimulate processes of creation, adoption and diffusion of this kind of solutions. This paper is based on a qualitative analysis of three exemplary case studies of different developing countries. This brings elements for understandings the major influences on innovative and inclusive healthcare solutions, which are presented as a theoretical model in the form of a causal graph.
Chemokine receptor specific for IP10 and mig: structure, function, and expression in activated T-lymphocytes

A human receptor that is selective for the CXC chemokines IP10 and Mig was cloned and characterized. The receptor cDNA has an open reading frame of 1104-bp encoding a protein of 368 amino acids with a molecular mass of 40,659 dalton. The sequence includes seven putative transmembrane segments characteristic of G-protein coupled receptors. It shares 40.9 and 40.3% identical amino acids with the two IL-8 receptors, and 34.2-36.9% identity with the five known CC chemokine receptors. The IP10/Mig receptor is highly expressed in IL-2-activated T lymphocytes, but is not detectable in resting T lymphocytes. B lymphocytes, monocytes and granulocytes. It mediates Ca2+ mobilization and chemotaxis in response to IP10 and Mig, but does not recognize the CXC-chemokines IL-8, GRO alpha, NAP-2, GCP-2. ENA78, PF4, the CC- chemokines MCP-1, MCP-2, MCP-3, MCP-4, MIP-1 alpha, MIP-1 beta. RANTES, 1309, eotaxin, nor lymphotactin. The exclusive expression in activated T-lymphocytes is of high interest since the receptors for chemokines which have been shown so far to attract lymphocytes, e.g., MCP-1, MCP- 2, MCP-3, MIP-1 alpha, MIP-1 beta, and RANTES, are also found in monocytes and granulocytes. The present observations suggest that the IP10/Mig receptor is involved in the selective recruitment of effector T cells.
A Task Scheduling Algorithm with Memory Function

In this paper, a scheduling algorithm with memory function suitable for homogeneous tasks on heterogeneous computing has been studied. With the objective to find the best point between matching and load balancing, the concept of memory has been used to improve the existing algorithm, and the simulation of our algorithm has been performed. The results demonstrated that our new algorithm has shorten the makespan greatly, and better scheduling performance has been achieved.
A Survey on Automatic Drowsy Driver Detection System in Image Processing

Due to the increasing growth in population, the occurrence of vehicle accidents has also seen an increase. A detailed analysis shows that, around half million accidents occur in a year, in India alone. Drowsiness and sleeping while driving are now identified as one of the reasons behind fatal crashes and highway accidents caused by drivers. Various drowsiness detection techniques researched are discussed in this paper. These techniques are classified and then compared using their features. Computer vision based image processing techniques is one of them. This uses various images of driver to detect drowsiness states using his/her eyes states, facial expressions and head poses. This technique is on the focus of this survey paper. Keywords— Driver fatigue, Drowsiness detection techniques, Image processing, Facial expressions, Eye states, Head poses, Accidents ------------------------------------------------------------ɚ-------------------------------------------------------------
Role for Daple in non‐canonical Wnt signaling during gastric cancer invasion and metastasis

In gastric cancer, the non‐canonical Wnt signaling pathway is activated by Wnt5a, which has a critical role in disease outcome. Previous studies have shown that Wnt5a mediates the expression of the extracellular matrix protein laminin γ2 through Rac and JNK activation to promote gastric cancer progression. However, the mechanism of this regulatory pathway has not been completely addressed. The scaffold protein Dvl is a major component of the Wnt signaling pathway. Here, we show that Dvl‐associating protein with a high frequency of leucine residues (Daple) mediates Wnt5a‐induced laminin γ2 expression. Immunohistochemical analysis showed marked expression of Daple in advanced clinical stages of gastric cancer, where it highly correlated with Wnt5a/b and laminin γ2 expression, the depth of wall invasion, and the frequency of lymph node metastasis. In cultured cancer cells, Daple depletion led to the suppression of Wnt5a‐induced Rac and JNK activation, laminin γ2 expression, and cell migration and invasion. Accordingly, Daple depletion also suppressed liver metastasis in a mouse xenograft model of gastric cancer. These results suggest that the non‐canonical Wnt signaling pathway contributes to gastric cancer progression at least in part via Daple, which provides a new therapeutic opportunity for the treatment of the disease.
Automatic clustering for digital photograph collections using time and content information

In this paper, we propose an automatic clustering method for large photographs collections using time and content features. First, we think about various types of feature vectors that are suitable to represent time and content of photographs, and we computed the similarity measures that can be represented an affinity between these photos. Next, we consider a clustering method for photo collection. Here, we first build a coarser clustering by automatically partitioning a given photo collection into several clusters using the Mean shift clustering algorithm. Second, we construct dense clustering by optimizing a Gaussian Dirichlet process mixture model taking initial clusters model as coarser clustering result. Finally, we have conducted the experiment which is able to evaluate a performance of our clustering method for various events photos collection. Experimental results show that both three types of features and Gaussian Dirichlet process mixture model brings about higher values of accuracy and precision in the clustering of photo-collection.
Food Fortification and Decline in the Prevalence of Neural Tube Defects: Does Public Intervention Reduce the Socioeconomic Gap in Prevalence?

Objective: A significant decline in the prevalence of neural tube defects (NTD) through food fortification has been reported. Questions remain, however, about the effectiveness of this intervention in reducing the gap in prevalence across socioeconomic status (SES). Study Design: Using health number and through record linkage, children born in Ontario hospitals between 1994 and 2009 were followed for the diagnosis of congenital anomalies. SES quintiles were assigned to each child using census information at the time of birth. Adjusted rates and multivariate models were used to compare trends among children born in different SES groups. Results: Children born in low SES areas had significantly higher rates of NTDs (RR = 1.25, CI: 1.14–1.37). Prevalence of NTDs among children born in low and high SES areas declined since food fortification began in 1999 although has started rising again since 2006. While the crude decline was greater in low SES areas, after adjustment for maternal age, the slope of decline and SES gap in prevalence rates remained unchanged overtime. Conclusions: While food fortification is successful in reducing the prevalence of NTDs, it was not associated with removing the gap between high and low SES groups.
Reevesioside A, a Cardenolide Glycoside, Induces Anticancer Activity against Human Hormone-Refractory Prostate Cancers through Suppression of c-myc Expression and Induction of G1 Arrest of the Cell Cycle

In the past decade, there has been a profound increase in the number of studies revealing that cardenolide glycosides display inhibitory activity on the growth of human cancer cells. The use of potential cardenolide glycosides may be a worthwhile approach in anticancer research. Reevesioside A, a cardenolide glycoside isolated from the root of Reevesia formosana, displayed potent anti-proliferative activity against human hormone-refractory prostate cancers. A good correlation (r2 = 0.98) between the expression of Na+/K+-ATPase α3 subunit and anti-proliferative activity suggested the critical role of the α3 subunit. Reevesioside A induced G1 arrest of the cell cycle and subsequent apoptosis in a thymidine block-mediated synchronization model. The data were supported by the down-regulation of several related cell cycle regulators, including cyclin D1, cyclin E and CDC25A. Reevesioside A also caused a profound decrease of RB phosphorylation, leading to an increased association between RB and E2F1 and the subsequent suppression of E2F1 activity. The protein and mRNA levels of c-myc, which can activate expression of many downstream cell cycle regulators, were dramatically inhibited by reevesioside A. Transient transfection of c-myc inhibited the down-regulation of both cyclin D1 and cyclin E protein expression to reevesioside A action, suggesting that c-myc functioned as an upstream regulator. Flow cytometric analysis of JC-1 staining demonstrated that reevesioside A also induced the significant loss of mitochondrial membrane potential. In summary, the data suggest that reevesioside A inhibits c-myc expression and down-regulates the expression of CDC25A, cyclin D1 and cyclin E, leading to a profound decrease of RB phosphorylation. G1 arrest is, therefore, induced through E2F1 suppression. Consequently, reevesioside A causes mitochondrial damage and an ultimate apoptosis in human hormone-refractory prostate cancer cells.
The role of context in media architecture

In this paper, we investigate the contextual characteristics of media architecture -- parameters that impact its integration in the existing social fabric -- from a socio-demographic (environment), technical (content) and architectural (carrier) perspective. Our analysis draws upon four real-world examples of media architecture, which have been specifically chosen to demonstrate a prototypical range of context-related symptoms, including a deliberate case of vandalism, the disconnection of a building-wide lighting installation, or the inappropriate integration of a screen on an existing architectural facade. In spite of its intrinsic 'dynamic' character, we conclude that media architecture seems not well prepared to adequately respond to changes in its context over time. As a result, we propose a set of guidelines that target all relevant stakeholders, ranging from architectural designers to content managers and public authorities, in an aim to improve media architecture's acceptance and credibility, towards its long-term sustainability in our urban fabric.
Design and evaluation of the Bi-directional Clutched Parallel Elastic Actuator (BIC-PEA)

Parallel elastic actuators (PEAs) have shown the ability to reduce the energy consumption of robots. The problem with regular PEAs is that it is not possible to freely choose at which instant or configuration to store or release energy. This paper introduces the concept and the design of the Bi-directional Clutched Parallel Elastic Actuator (BIC-PEA*), which reduces the energy consumption of robots by loading and unloading the parallel spring in a controlled manner. The concept of the BIC-PEA consists of a spring that is mounted between the two outgoing axes of a differential mechanism. Those axes can also be locked to the ground by two locking mechanisms. At any position, the BIC-PEA can store the kinetic energy of a joint in the spring such that the joint is decelerated to zero velocity. The spring energy can then be released, accelerating the joint in any desired direction. In our prototype of 202 g, the energy that can be stored in the spring is 0.77 J. When disengaged, the friction that the mechanism adds is negligible. The current maximum over-all efficiency is 62 %, which is about 55% more than what generally can be achieved by recapturing the energy electrically. Its relatively high efficiency and controllability make the BIC-PEA a promising concept for reducing the energy consumption of robots.
Interactive calibration of a multi-projector system in a video-wall multi-touch environment

Wall-sized interactive displays gain more and more attention as a valuable tool for multiuser applications, but typically require the adoption of projectors tiles. Projectors tend to display deformed images, due to lens distortion and/or imperfection, and because they are almost never perfectly aligned to the projection surface. Multi-projector video-walls are typically bounded to the video architecture and to the specific application to be displayed. This makes it harder to develop interactive applications, in which a fine grained control of the coordinate transformations (to and from user space and model space) is required. This paper presents a solution to such issues: implementing the blending functionalities at an application level allows seamless development of multi-display interactive applications with multi-touch capabilities. The description of the multi-touch interaction, guaranteed by an array of cameras on the baseline of the wall, is beyond the scope of this work which focuses on calibration.
Adaptive sampling with Renyi entropy in Monte Carlo path tracing

Adaptive sampling is an interesting tool to lower noise, which is one of the main problems of Monte Carlo global illumination algorithms such as the famous and baseline Monte Carlo path tracing. The classic information measure, namely, Shannon entropy has been applied successfully for adaptive sampling in Monte Carlo path tracing. In this paper we investigate the generalized Renyi entropy to establish the refinement criteria to guide both pixel super sampling and pixel subdivision adaptively. Implementation results show that the adaptive sampling based on Renyi entropy outperforms the counterpart based on Shannon entropy consistently
mplementing large-scale and long-term functional biodiversity research : he Biodiversity

mplementing large-scale and long-term functional biodiversity research: he Biodiversity Exploratories arkus Fischera,b,∗, Oliver Bossdorfa, Sonja Gockelc, Falk Hänselb, Andreas Hempb, ominik Hessenmöllerd, Gunnar Korteb, Jens Nieschulzed, Simone Pfeifferb, Daniel Pratia, wen Rennere, Ingo Schöningc, Uta Schumacherb, Konstans Wellse, François Buscotf, lisabeth K.V. Kalkoe, Karl Eduard Linsenmairg, Ernst-Detlef Schulzed, Wolfgang W. Weisserc
Predicting Spectral and Prosodic Parameters for Unit Selection in Speech Synthesis

We usually build a prosody model to predict the prosodic parameters, which will be used as part of the criteria for unit selection. Spectral appropriateness of units is usually ensured by using identities of context units, which are linguistic symbols. With looking into the spectral properties of the actual signal, the spectral mismatches are often perceived in the synthetic speech. In this paper, we propose to use MFCC as spectral parameters in addition to the prosodic parameters. By introducing the spectral parameters into the criteria for unit selection, the appropriateness of units can determined by statistical models. Thus the possibility of abnormal spectral mismatches between the concatenated units can be reduced. Experiments show that the approach helps to improve the quality of synthetic speech.
Dispersion-Free and Tunable Nonreciprocities in Composite Right-/Left-Handed Metamaterials and Their Applications to Beam Squint Reduction in Leaky-Wave Antennas

In this paper, the enhancement of bandwidth for beam squint reduction in leaky-wave antennas has been numerically and experimentally demonstrated based on the pseudo-traveling-wave resonance by using nonreciprocal composite right-/left-handed metamaterial lines with almost dispersion-free phase-shifting nonreciprocities. We consider two different types of metamaterials governed by the edge-guided mode propagation in normally magnetized ferrite microstrip lines and operating at frequencies far above or below the magnetic resonance. Both metamaterials are separately designed and implemented in leaky-wave antennas based on the pseudo-traveling-wave resonance. The numerical simulation and measurement results verify the beam squint reduction for both cases with the enhanced bandwidths of 6%–10%.
An Efficient Comparison-Based Deterministic Algorithm to Solve the Closest Pair Problem

A simple and efficient algorithm is proposed to solve the closest pair problem of points in k-dimensional space. The algorithm presorts the points according to their values of one dimension and then only computes the distances of point pairs which may be closer than the current closest pair. Empirical analysis shows that in the average case the number of distance computations performed is of O(1) and the number of comparisons performed, if not including those in the presorting, is of O(n).
Educational Peer E ff ects Quantile Regression Evidence from Denmark with PISA 2000 data by

We combine data from the first wave of the OECD PISA sample with register data for Denmark to estimate educational peer effects. These datasets combined provide an unusually large set of background variables that help alleviate the usual problems of omitted variables bias, prevalent in much of the empirical literature on peer effects. Quantile regression results show that there may be differential peer group effects at different points of the conditional test score distribution: The positive and significant peer level effect is strongest for weak students and is steadily decreasing over the conditional test score distribution. The effect from a heterogenous peer composition on test scores does affect weak learners positively, while the effect for good readers is negative, but at all estimated quantiles, the effect is not significantly different from zero. These results combined suggest that mixing of abilities is the optimal policy to maximize average reading skills in the student
Authenticated spectrum sharing for secondary users in cognitive radio networks

Cognitive Radio Networks (CRNs) deal with opportunistic spectrum access in order to fully utilize the scarce of spectrum resources, with the development of cognitive radio technologies to greater utilization of the spectrum. Now-a-days Cognitive Radio (CR) is a promising concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. In this paper we propose two approaches. At first we propose a trust aware model to authenticate the secondary users (SUs) in CRNs which provides a reliable technique to establish trust for CRNs. Secondly, we propose stochastic approach to show the free spectrum availability for SUs in CRNs. To evaluate the proposed approaches, we have modeled and analyzed steady state availability depending on Markov model for free spectrum by adopting QoS characteristics in cognitive radio networks.
Nonlinear Modeling and Analysis on Concurrent Amplification of Dual-Band Gaussian Signals

In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as interand cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA’s nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA’s output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dualband signals merely by conducting a one-tone test. key words: nonlinear power amplifier, spectral regrowth, ACPR, EVM, OFDM, complex Gaussian distribution, Flexible Wireless System, Volterra series expansion, general Wiener model
Visual tracking of small animals based on real-time Level Set Method with fast infra-red thermographic imaging

In this paper, we present a long-term monitoring of moving and high deformable objects with fast thermographic infrared imaging, in a process of developing an automated image analysis of laboratory animals' postures and activities. For this several days tracking, we tackle the object deformations with a model-based articulated body parts scheme and the two-stage tracking and segmentation technique is performed through a Kalman filtering associated to a level-set method. The latter is the main contribution of the paper (with also the contours classification of each body parts) since the proposed segmentation is robust to noise and heat places and can easily be parallelized and executed in real-time. Each body part is modelled with a set of geometrical descriptors with mutual interactions. The advantage of such method is not only to separate the dynamics of the whole object motion from those of body parts deformations but it also allows to extract apparent postural information to further produce a model of animal behaviour.
The quest for single trial correlations in multimodal EEG-fMRI data

In the past decade, technological advances have made it possible to reliably measure brain activity using simultaneous EEG-fMRI recordings inside an MR scanner. The main challenge then became to investigate the coupling between the EEG and fMRI signals in order to benefit from the simultaneously integrated temporal and spatial resolution. Although it is crucial to know when features in EEG and fMRI are expected to correlate with each other before the identification of common sources from multimodal data is possible, it is still a matter of debate. In this study, we address this question by analysing EEG and fMRI data separately from a face processing task. We show that we are able to reliably estimate single trial (ST) dynamics of face processing in EEG and fMRI data separately in four subjects. However, no correlation is found between the modalities. This implies that in this task modality-specific information is larger than the information that is shared by the modalities.
An automatic beautifier for drawings and illustrations

We describe a method for inferring constraints that are desirable for a given (rough) drawing and then modifying the drawing to satisfy the constraints wherever possible. The method has been implemented as part of an online graphics editor running under the UNIX™ operating system and it has undergone modifications in response to user input. Although the framework we discuss is general, the current implementation is polygon-oriented. The relations examined are: approximate equality of the slope or length of sides, collinearity of sides, and vertical and horizontal alignment of points.