Miracle-dz/UniFAR-FTUs huggingface dataset:
Kommunikative Partizipation und Integrationserleben hörgeschädigter Schülerinnen und Schüler an einer Schwerpunktschule

Schwerpunktschulen, die von einer groseren Anzahl von horgeschadigten Schulerinnen und Schulern besucht werden, stellen in Bezug auf die psychosoziale Entwicklung horgeschadigter Kinder eine in den letzten Jahren vermehrt in die Diskussion gebrachte alternative Bildungsoption zur Einzelinklusion dar. In der vorliegenden Fragebogenstudie wurden 35 Schulerinnen und Schuler einer Schwerpunktschule in Bezug auf ihre erlebte Partizipation im Unterricht, ihr Integrationserleben sowie auf Verhaltensauffalligkeiten und Lebensqualitat untersucht. Die Ergebnisse zeigen insgesamt eine positive Entwicklung in allen uberpruften Bereichen mit behinderungsspezifischen Besonderheiten, die in der padagogischen Begleitung horgeschadigter Kinder beachtet werden mussen. Vergleiche zu Daten aus anderen Studien mit einzelintegrierten horgeschadigten Kindern ergeben keine Unterschiede. Padagogische Konsequenzen sowie Herausforderungen fur weiterfuhrende Studien werden diskutiert. (DIPF/Orig.) Regular schools with the focus to include not only one deaf or hard of hearing (DHH) child but a significant number of DHH students on their campus, provide an alternative educational option regarding the psychosocial development for DHH students which is discussed increasingly for some years. In the present questionnaire study 35 students attending such a school were investigated in terms of their classroom participation, their experiences regarding inclusion as well as regarding behavioral problems and quality of life. The results reveal an overall positive development in all tested domains but also show some deaf related characteristics that must be considered in the promotion of DHH children. Compared to data from other studies with single included DHH children there are no significant differences to note. Educational implications and challenges for future studies are discussed. (DIPF/Orig.)
Prediksi Kepribadian Big 5 Pengguna Twitter dengan Support Vector Regression

Informasi biografi dan tweets dari pengguna Twitter dapat dimanfaatkan untuk menggambarkan kepribadian Big 5, yang terdiri dari openness, conscientiousness, extraversion, agreeableness, dan neuroticism . Makalah ini membahas penggunaan infomasi pengguna Twitter untuk membentuk suatu model pembelajaran prediksi kepribadian Big 5. Fitur yang digunakan sebagai eksperimen terdiri dari dua fitur utama, yaitu fitur perilaku sosial dan linguistik. Fitur linguistik yang digunakan terbagi atas 2 bagian besar, yaitu fitur kategori kata dari kamus yang dibangun secara manual dan fitur yang diekstrak langsung dari data pada Twitter. Dari eksperimen dan pengujian yang dilakukan dengan metode Support Vector Regression (SVR), didapatkan bahwa secara keseluruhan model pembelajaran yang paling baik dalam memprediksi kepribadian pengguna Twitter adalah model yang menggunakan gabungan fitur perilaku sosial dan linguistik bigram. Model tersebut menghasilkan nilai Mean Absolute Error (MAE) terkecil 0.2739, sedangkan nilai Pearson- correlation terbesar 0.8559 didapatkan untuk kepribadian Extraversion. Kata Kunci fitur perilaku sosial, fitur linguistik, kepribadian Big 5, SVR, twitter.
Inhibition of SRC family kinases reduces myeloid‐derived suppressor cells in head and neck cancer

SRC family kinases (SFKs), a group of nonreceptor tyrosine kinases, modulate multiple cellular functions, such as cell proliferation, differentiation and metabolism. SFKs display aberrant activity in progressive stages of human cancers. However, the precise role of SFKs in the head and neck squamous cell carcinoma (HNSCC) signaling network is far from clear. In this study, we found that the inhibition of SFKs activity by dasatinib effectively reduced the tumor size and population of MDSCs in the HNSCC mouse model. Molecular analysis indicates that phosphorylation of LYN, rather than SRC, was inhibited by dasatinib treatment. Next, we analyzed LYN expression by immunostaining and found that it was overexpressed in the human HNSCC specimens. Moreover, LYN expression in stromal cells positively correlated with myeloid‐derived suppressor cells (MDSCs) makers CD11b and CD33 in human HNSCC. The dual positive expression of LYN in epithelial and stromal cells (EPI+ SRT+) was associated with unfavorable overall survival of HNSCC patients. These findings indicate that SFKs may be a potential target for an effective immunotherapy of HNSCC by decreasing MDSCs and moreover, LYN will have an impact on such therapeutic strategy.
Fast blind deconvolution and blind demixing via nonconvex optimization

We study the question of reconstructing a sequence of {f<inf>i</inf>, g<inf>i</inf>}<inf>i=1</inf><sup>s</sup> from the sum of their convolution, i.e., y = ∑<inf>i=1</inf><sup>s</sup> f<inf>i</inf> * g<inf>i</inf>. This problem is closely related to both blind deconvolution and blind demixing problem. Our goal is to find all {f<inf>i</inf>, g<inf>i</inf>}<inf>i=1</inf><sup>s</sup> by jointly demixing each component f<inf>i</inf> * g<inf>i</inf> and performing deconvolution procedure. While the convex program is able to solve this problem effectively and robustly under certain conditions, the main obstacle towards real-time deployment is to find a provably convergent, efficient and robust algorithm. We present an efficient numerical algorithm which guarantees the exact recovery of the solutions despite its notorious non-convexity. The proposed two-step algorithm converges to the global minima linearly and is also robust to the noise. Though the derived performance bound is suboptimal in terms of the information-theoretic limit, numerical simulations show the remarkable performance even if the number of measurements is close to the degree of freedom.
Axiomatic Scalable Neurocontroller Analysis via the Shapley Value

One of the major challenges in the field of neurally driven evolved autonomous agents is deciphering the neural mechanisms underlying their behavior. Aiming at this goal, we have developed the multi-perturbation Shapley value analysis (MSA)the first axiomatic and rigorous method for deducing causal function localization from multiple-perturbation data, substantially improving on earlier approaches. Based on fundamental concepts from game theory, the MSA provides a formal way of defining and quantifying the contributions of network elements, as well as the functional interactions between them. The previously presented versions of the MSA require full knowledge (or at least an approximation) of the network's performance under all possible multiple perturbations, limiting their applicability to systems with a small number of elements. This article focuses on presenting new scalable MSA variants, allowing for the analysis of large complex networks in an efficient manner, including large-scale neurocontrollers. The successful operation of the MSA along with the new variants is demonstrated in the analysis of several neurocontrollers solving a food foraging task, consisting of up to 100 neural elements.
Characterizing the European Sub-Arctic Winter Climate since 1500 Using Ice, Temperature, and Atmospheric Circulation Time Series

Abstract This study describes winter climate during the last 500 yr for the greater Baltic Sea region through an examination of well-documented time series of ice cover, sea level pressure, and winter surface air temperatures. These time series have been the focus of previous studies, but here their covariation over different time scales is analyzed based on two modern descriptive statistical techniques, matching pursuit and wavelet analysis. Independently, 15 time periods were found during the last 500 yr with different climatic signatures with respect to winter severity, circulation patterns, and interannual variability. The onsets of these periods are presumably caused largely by perturbations within the system, although correspondences with solar and volcanic activity can be identified for certain of the periods. The Baltic region climate has changes on both centennial and decadal time scales, often with rapid transitions. Major warmer periods were the first half of the eighteenth century and the twen.
Springs and Constraints for 3D Drawing

In this paper we present examples of haptic sculpting mediated by a physical model or constraint. Most current work in haptic drawing and sculpting focuses on interacting with a static model and properly simulating contact forces. Our work proposes dynamic models for the creative process. These are based on physical models, but present physically impossible scenarios which allow new forms of expression. By focusing on models not realizable in the real world we show an expansion of the creative process through haptic feedback. As example applications we present two prototypes. Dynasculpt allows 3D sculpting by attaching a sprung virtual mass to the Phantom position and creating a ribbon or tube along the path taken by the mass through space. Griddraw is used for constrained 3D drawing – a uniform 3D grid of detents is haptically superimposed over 3D space, allowing the easy production of straight lines and right angles. Both focus on dynamics as intrinsic to the creative process. Our initial reflections and observations indicate that this paradigm is a fruitful one for haptically enhanced creation of static models. The standard problem of users comparing their experience to the superior real-world experience is circumvented in this work by presenting novel experiences impossible to feel or construct in the physical world. By presenting ourselves and naive users with simple target tasks, we have informally analyzed the controllability of each tool. Our two prototypes seem to lie on extremes in a continuum of expressivity/controllability – Dynasculpt can become difficult to control – often at the edge of chaos, while Griddraw can be overly constraining. Active force feedback in both cases can serve to stabilize unstable or chaotic models.
Review of image compression techniques

Demand of multimedia growth, contributes to insufficient bandwidth of network and memory storage device. Therefore data compression is more required for reducing data redundancy to save more hardware space and transmission bandwidth. Image compression is one of the main research in the field of image processing. Many techniques are given for image compression. Some of which are discussed in this paper. This paper discusses k-means clustering, 2D-DWT and fuzzy logic based image compression.
Junctional Adhesion Molecule-1 Is Upregulated in Spontaneously Hypertensive Rats: Evidence for a Prohypertensive Role Within the Brain Stem

Junctional adhesion molecule-1 (JAM-1) forms part of the tight junction between adjacent endothelial cells. Using microarray technology, we showed previously that JAM-1 was differentially expressed in the brain stem of spontaneously hypertensive rats compared with normotensive Wistar–Kyoto (WKY) rats. In this study, we quantified the expression of JAM-1 in the brain stem of spontaneously hypertensive rats and WKY rats and established whether any differential expression was confined to this region of the brain or was ubiquitous throughout the central nervous system and, indeed, the whole body. Because the nucleus tractus solitarii plays a pivotal role in arterial pressure regulation, we assessed whether JAM-1 in this region affects the chronic regulation of arterial pressure. Real time RT-PCR revealed that JAM-1 mRNA was upregulated in multiple regions of the brain and all of the peripheral vascular beds studied. In the nucleus tractus solitarii, the level of JAM-1 mRNA was significantly higher in both young (3-week–old, prehypertensive) and adult male spontaneously hypertensive rats (15 to 18 weeks old) than that of age-matched WKY rats (fold differences; prehypertensives: 1.01±0.06 versus 1.59±0.13; n=10; P<0.01; adult: 1.08±0.14 versus 2.86±0.57; n=10; P<0.01). After adenoviral-mediated expression of JAM-1 in the nucleus tractus solitarii of adult WKY rats (15 weeks old; n=6), systolic pressure was increased from 120±4 to 132±4 mm Hg (P<0.01). Our data suggest that JAM-1 expression in the spontaneously hypertensive rat is upregulated throughout the body compared with the WKY rat and that this is not secondary to the hypertension. When JAM-1 is expressed in the nucleus tractus solitarii, it raises arterial pressure, suggesting a novel prohypertensive role for this protein within the brain stem.
31 Electric Current Wound Healing

The authors review the existing physical modalities for treatment of chronic wounds and show the advantages of electric current and electromagnetic field stimulation. Direct currents, low frequency pulsed currents, monophasic high voltage pulses and pulsed electromagnetic fields are compared in respect of their efficiency. Wound healing quantification methods, wound healing dynamics and prognostic factors in the prediction of wound healing proposed by the authors represent significant contribution in understanding the mechanisms of electric wound healing.
Incorporating side-channel information into convolutional neural networks for robotic tasks

Convolutional neural networks (CNN) are a deep learning technique that has achieved state-of-the-art prediction performance in computer vision and robotics, but assume the input data can be formatted as an image or video (e.g. predicting a robot grasping location given RGB-D image input). This paper considers the problem of augmenting a traditional CNN for handling image-like input (called main-channel input) with additional, highly predictive, non-image-like input (called side-channel input). An example of such a task would be to predict whether a robot path is collision-free given an occupancy grid of the environment and the path's start and goal configurations; the occupancy grid is the main-channel and the start and goal are the side-channel. This paper presents several candidate network architectures for doing so. Empirical tests on robot collision prediction and control problems compare the proposed architectures in terms of learning speed, memory usage, learning capacity, and susceptibility to overfitting.
Visualizing Particle-Based Simulation Datasets on the Desktop

We present an approach to rendering large, time-varying particle-based simulation datasets using programmable graphics hardware on desktop computer systems. Particle methods are used to model a wide range of complex phenomena, and effective visualization of the resulting data requires communicating subtle changes in the three-dimensional structure, spatial organization, and qualitative trends within a simulation as it evolves, as well as allowing easier navigation and exploration of the data through interactivity. We highlight the critical components of our approach, and introduce an extension to the coherent hierarchical culling algorithm that often improves temporal coherence and leads to better average performance for time-varying datasets. Our approach performs competitively with current particle visualization systems based on interactive ray tracing that require tightly coupled supercomputers. Moreover, our system runs on hardware that is a fraction of the cost of these systems, making particle visualization and data exploration more accessible. We thus advance the current state-of-the-art by bringing visualization of particle-based simulation datasets to the desktop.
Mismatched pre- and postnatal nutrition leads to cardiovascular dysfunction and altered renal function in adulthood

The early life environment has long-term implications for the risk of developing cardiovascular (CV) disease in adulthood. Fetal responses to changes in maternal nutrition may be of immediate benefit to the fetus, but the long-term effects of these adaptations may prove detrimental if nutrition in postnatal life does not match that predicted by the fetus on the basis of its prenatal environment. We tested this predictive adaptive response hypothesis with respect to CV function in sheep. We observed that a mismatch between pre- and postnatal nutrient environments induced an altered CV function in adult male sheep that was not seen when environments were similar. Sheep that received postnatal undernutrition alone had altered growth, CV function, and basal hypothalamo–pituitary–adrenal axis activity in adulthood. Prenatal undernutrition induced greater weight gain by weaning compared with the prenatal control diet, which may provide a reserve in the face of a predicted poor diet in later life. In an adequate postnatal nutrient environment (i.e., relatively mismatched), these offspring exhibited cardiac hypertrophy and altered CV function in adulthood. These data support the concept that adult CV function can be determined by developmental responses to intrauterine nutrition made in expectation of the postnatal nutritional environment, and that if these predictions are not met, the adult may be maladapted and at greater risk of CV disease. Our findings have substantial implications for devising strategies to reduce the impact of a mismatch in nutrition levels in humans undergoing rapid socio-economic transitions in both developing and developed societies.
Violência e vida familiar: abordagens psicanalíticas e de gênero

We aim to examine the possibilities for an interdisciplinary dialogue between Psychoanalysis and gender theory, as expressed in studies about violence on Collective Health, to approach occurrences of aggression and abuse in family life and their possible impacts on health, with particular attention to the psychological impacts on children and women, as well as in the family group as a whole. Based on classical authors for both disciplinary contributions, we examine a concrete case taken from a family care situation. This examination consists of three interpretative dimensions: first, considerations on the individual case in its family context; second, the case seen from the perspective of cultural issues; and third, the relation between culture and its individualized expression in the case. We show the possibility of conducting an approach that integrates the intrapsychic dimension, which concerns the functioning of the inner world of the individuals involved, with the sociocultural and historical realities that constitute their context of life. With the aim of a comprehensive care of the cases, we highlight the practical importance of combining reflection and action of psychodynamic nature, a result of the examination of the intrapsychic impacts of violence from concepts such as trauma and terror, with recognition of cultural expressions in the individual and family realms, which strengthen normative acceptances of aggressions, victimizations, silencing, and trivialization of violence. The interdisciplinary dialogue makes possible to understand the development of culturally reinforced feelings and behaviors, such as fear and shame in the victims and repetition of violence in the aggressors.
Digital media and stress: the cost of caring 2.0

ABSTRACT This research explores the relationship between the use of digital media and stress. Based on the findings of a national, probability sample of adults in the United States, the use of digital media was not directly associated with higher levels of psychological stress. Some uses of digital media were associated with lower levels of perceived stress for women but not for men. However, the evidence suggests that, for men and women, digital media provides heightened awareness of network life events (AoNLE) in the lives of both close and more distant acquaintances. An awareness of undesirable, major life events in the lives of others can be a source of psychological stress; this is the cost of caring. Thus, the link between digital media and stress is indirect. We argue that the growth of digital media is related to changes in the structure of peoples’ personal communities that contribute to this trend. There has been a shift toward networks that offer persistent contact and pervasive awareness. Findings suggest that different mobile technologies, Internet technologies, and social media afford AoNLE for men and women, but women tend to report greater psychological stress than men, and they experience psychological stress from a wider range of AoNLE. We discuss explanations for the negative relationship between technology use and stress for women, as well as the implications of our findings for research on the use of digital media and psychological well-being, such as the relationship to social support, narcissism and empathy.
Infant death rates among the poor and nonpoor in Kentucky, 1982 to 1983.

The mortality rates of infants born in Kentucky during 1982 and 1983 were analyzed to determine whether there were differences between poor and nonpoor infants. We used computer matching with the Social Insurance Food Stamp files and with the Aid for Families With Dependent Children files to define poor and nonpoor Kentucky resident families. The crude death rate for poor infants was 13.7/1,000 births, and the nonpoor death rate was 10.8/1,000 births. After adjusting for several important variables, we found that the poor infant was at a significantly greater risk for death than the nonpoor infant but only during the postneonatal period (relative risk 2.04, P = .0003). Some differences by sex and race were noted. Sudden infant death syndrome and infections were largely responsible for the poor infants' higher postneonatal mortality risk.
Effects of Relational Aggression on Children's Social-psychological Adjustment

Objective:To explore effects of relational aggression on children's social-psychological adjustment.Methods:Class Play Inventory,Children's Lonelines Scale,Peer Nomination and Friend Nomination were used to examine 549 children.Results:①Girls had significantly more relational aggression than boys. ②Relational aggression had significant positive correlation with victimization,withdrawn and rejection,while no significant correlation with lonelines and number of mutual friends. ③Hierarchical regression indicated that relational aggression was an significant positive predictor of victimization,withdrawn and rejection after controlling overt aggression.Conclusion:Relational aggression is a powerful predictor of social-psychological adjustment.
Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support

In sequential pattern analysis, the frequency of patterns is evaluated by the support. While computed efficiently from large databases, we show that the support cannot be compared between different databases, since it is influenced by the actual sequence length distribution. Models for this sequence length distribution are surveyed. One of these models, the Good distribution, appears to be sufficiently flexible for practice. It is used to exemplify an approach for adjusting the relative support such that the resulting adjusted support values are better comparable between different databases. We illustrate our findings with texts from the bilingual FinDe corpus.