Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding changes in social cohesion in Bolivia

This paper attempts to measure and explain the changes in “social cohesion” that took place in Bolivia during the first term of presidency of Evo Morales Ayma - Bolivia’s first indigenous president. Following Maxwell (2006), we define social cohesion as a distribution of beliefs, values and modes of thinking that make people feel they are members of the same community, engaged in common enterprises, and facing shared challenges. Accordingly, we measure the lack of social cohesion as the observed deviation from cooperative equilibrium in experimental games of trust with monetary rewards conducted in a sample of undergraduates. We find that social cohesion has declined significantly, despite ethnic fractionalization measures have remain constant and economic and political heterogeneity measures have declined. This results declines in social cohesion despite declining trends in social divisions, are at odds with what would be expected; since, traditionally, the lack of social cohesion has been associated and measured as the extent of ethnic, income and political divisions observed in a society (e.g. Esterly, Ritzan and Woolcock (2006)). Therefore, we argue that social cohesion is not only related to the extent of ethnic, economic and political divisions within a society, within-group identification, but also and even more importantly, to the degree of between-group alienation observed between ethnic, economic and political groups. Furthermore, we show that our measure of lack of social cohesion, the average deviation from cooperative equilibrium observed in the trust game, is equivalent to Esteban and Ray (1994) polarization measure where within-group identification is measured by group size and between-group alienation is measured as the average lack of cooperation between-groups. Using this measure, we argue that the decline of social cohesion in Bolivia can be explained by an increase in alienation between ethnic and political groups motivated mainly by the institutional reforms implemented during Morales’ administration.
Three‐dimensional modelling identifies novel genetic dependencies associated with breast cancer progression in the isogenic MCF10 model

The initiation and progression of breast cancer from the transformation of the normal epithelium to ductal carcinoma in situ (DCIS) and invasive disease is a complex process involving the acquisition of genetic alterations and changes in gene expression, alongside microenvironmental and recognized histological alterations. Here, we sought to comprehensively characterise the genomic and transcriptomic features of the MCF10 isogenic model of breast cancer progression, and to functionally validate potential driver alterations in three‐dimensional (3D) spheroids that may provide insights into breast cancer progression, and identify targetable alterations in conditions more similar to those encountered in vivo. We performed whole genome, exome and RNA sequencing of the MCF10 progression series to catalogue the copy number and mutational and transcriptomic landscapes associated with progression. We identified a number of predicted driver mutations (including PIK3CA and TP53) that were acquired during transformation of non‐malignant MCF10A cells to their malignant counterparts that are also present in analysed primary breast cancers from The Cancer Genome Atlas (TCGA). Acquisition of genomic alterations identified MYC amplification and previously undescribed RAB3GAP1–HRAS and UBA2–PDCD2L expressed in‐frame fusion genes in malignant cells. Comparison of pathway aberrations associated with progression showed that, when cells are grown as 3D spheroids, they show perturbations of cancer‐relevant pathways. Functional interrogation of the dependency on predicted driver events identified alterations in HRAS, PIK3CA and TP53 that selectively decreased cell growth and were associated with progression from preinvasive to invasive disease only when cells were grown as spheroids. Our results have identified changes in the genomic repertoire in cell lines representative of the stages of breast cancer progression, and demonstrate that genetic dependencies can be uncovered when cells are grown in conditions more like those in vivo. The MCF10 progression series therefore represents a good model with which to dissect potential biomarkers and to evaluate therapeutic targets involved in the progression of breast cancer. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
UTA DLNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation

In this paper, we propose a deep neural network based natural language processing sys-tem for semantic textual similarity prediction. We leverage multi-layer bidirectional LSTM to learn sentence representation. After that, we construct matching features followed by High-way Multilayer Perceptron to make predictions. Experimental results demonstrate that this approach can’t get better results on standard evaluation datasets.
Estrogen Receptor Status Could Modulate the Genomic Pattern in Familial and Sporadic Breast Cancer

Purpose: Familial breast cancer represents 5% to 10% of all breast tumors. Mutations in the two known major breast cancer susceptibility genes, BRCA1 and BRCA2, account for a minority of familial breast cancer, whereas families without mutations in these genes (BRCAX group) account for 70% of familial breast cancer cases. Experimental Design: To better characterize and define the genomic differences between the three classes of familial tumors and sporadic malignancies, we have analyzed 19 BRCA1, 24 BRCA2, and 31 BRCAX samples from familial breast cancer patients and 19 sporadic breast tumors using a 1-Mb resolution bacterial artificial chromosome array-based comparative genomic hybridization. Results: We found that BRCA1/2 tumors showed a higher genomic instability than BRCAX and sporadic cancers. There were common genomic alterations present in all breast cancer groups, such as gains of 1q and 16p or losses of 8ptel-p12 and 16q. We found that the presence/absence of the estrogen receptor (ER) may play a crucial role in driving tumor development through distinct genomic pathways independently of the tumor type (sporadic or familial) and mutation status (BRCA1 or BRCA2). ER− tumors presented higher genomic instability and different altered regions than ER+ ones. Conclusions: According to our results, the BRCA gene mutation status (mainly BRCA1) would contribute to the genomic profile of abnormalities by increasing or modulating the genome instability.
Integrating Fixed Priority and Static Scheduling to Maintain External Consistency

Data in hard real-time databases has not only to be logically onsistent but has also to be fresh enough in order to be used as an acceptable app roximation of associated real-world values. Such external consistency c an be achieved, if we use transactions to repeatedly generate new values before t he previous ones get out of date. A so-called age constraint is imposed on these tr ansactions. While deadline monotonic scheduling is a usually choice for sched uling subject to age constraints, we propose a static (cyclic) scheduler and sho w its quality, analytically and by performance evaluation. We continue showing h ow the received cyclic schedule – which we prefer for time-triggered traffic – can be integrated into overall deadline monotonic scheduling – which is advis able for the eventtriggered part of the database traffic.
Neural circuitries and neurobiological mechanisms relevant to stress resilience

3 I. Abstract Stress is ubiquitous in modern life and the inability to successfully cope with it may lead to psychological disorders. Resilience refers to the ability of people to successfully cope with stressful situations, maintaining psychological well-being in the face of adversity. Every individual experiences stressful life events, but shows a high degree of heterogeneity of responses. For some individuals, exposure to chronic or severe stress leads to a pathologically excessive response (also called "allostatic load"), and ultimately results in psychopathology such as depression or posttraumatic stress disorder (PTSD). Fortunately, the vast majority of stress-exposed individuals is able to overcome crisis and maintains normal neuropsychological functioning, which is a condition termed " allostasis ". Although why some individuals flourish and others perish under similar stressful conditions remains one of the conundrums in stress research, it is broadly accepted that building or enhancing resilience is crucial to achieving and maintaining good mental health. This concept also calls for resilience as an important target of treatment and prevention of stress-related psychopathology. However, the neural circuitries and neurobiological mechanisms that mediate resilience to the deleterious effects of stress remain poorly understood. Thus, the long-term goal of this study is to identify the neural circuitries and neurobiological mechanisms underlying stress resilience and determine whether the resilience-enhancing interventions may have the potential to attenuate or prevent the occurrence of stress-related psychopathology. In the first year of this project, we used an experimental model of auditory fear conditioning to address this issue. Fear conditioning in animals has been used extensively to model clinical anxiety disorders. While individual animal exhibit marked differences in their propensity to undergo fear conditioning, the physiologically relevant mediators have not yet been fully characterized. We found that C57BL/6 inbred mouse strain subjected to chronic social defeat training (CSDT) can be separated into susceptible and resistant subpopulations that display different levels of fear responses in an auditory fear conditioning paradigm. Susceptible mice had significantly more c-Fos protein expression in neurons of the basolateral amygdala (BLA) following CSDT and showed exaggerated conditioned fear responses, while there were no significant differences between groups in innate anxiety-and depressive-like behaviors. Through the use of conditional brain-derived neurotrophic factor (BDNF) knockout strategies, we show that elevated BLA BDNF level following fear conditioning training is a key mediator contributing to determine the levels of conditioned fear responses. Our combined behavioral, autonomic, and neuroendocrine approaches reveal that relative to …
A Joint Model for Chinese Microblog Sentiment Analysis

Topic-based sentiment analysis for Chinese microblog aims to identify the user attitude on specified topics. In this paper, we propose a joint model by incorporating Support Vector Machines (SVM) and deep neural network to improve the performance of sentiment analysis. Firstly, a SVM Classifier is constructed using N-gram, NPOS and sentiment lexicons features. Meanwhile, a convolutional neural network is applied to learn paragraph representation features as the input of another SVM classifier. The classification results outputted by these two classifiers are merged as the final classification results. The evaluations on the SIGHAN-8 Topic-based Chinese microblog sentiment analysis task show that our proposed approach achieves the second rank on micro average F1 and the fourth rank on macro average F1 among a total of 13 submitted systems.
Help Seeking Behavior of Women with Self-Discovered Breast Cancer Symptoms: A Meta-Ethnographic Synthesis of Patient Delay

Background and Objective Patient delay makes a critical contribution to late diagnosis and poor survival in cases of breast cancer. Identifying the factors that influence patient delay could provide information for adopting strategies that shorten this delay. The aim of this meta-ethnography was to synthesize existing qualitative evidence in order to gain a new understanding of help seeking behavior in women with self-discovered breast cancer symptoms and to determine the factors that influence patient delay. Methods The design was a meta-ethnography approach. A systematic search of the articles was performed in different databases including Elsevier, PubMed, ProQuest and SCOPUS. Qualitative studies with a focus on help seeking behaviors in women with self-discovered breast cancer symptoms and patient delay, published in the English language between 1990 and 2013 were included. The quality appraisal of the articles was carried out using the Critical Appraisal Skills Programme qualitative research checklist and 13 articles met the inclusion criteria. The synthesis was conducted according to Noblit and Hare’s meta-ethnographic approach (1988), through reciprocal translational analysis and lines-of-argument. Findings The synthesis led to identification of eight repeated key concepts including: symptom detection, initial symptom interpretation, symptom monitoring, social interaction, emotional reaction, priority of medical help, appraisal of health services and personal-environmental factors. Symptom interpretation is identified as the important step of the help seeking process and which changed across the process through active monitoring of their symptoms, social interactions and emotional reactions. The perceived seriousness of the situation, priority to receive medical attention, perceived inaccessibility and unacceptability of the health care system influenced women’s decision-making about utilizing health services. Conclusion Help seeking processes are influenced by multiple factors. Educational programs aimed at correcting misunderstandings, erroneous social beliefs and improving self-awareness could provide key strategies to improve health policy which would reduce patient delay.
Part One of a Series of Five Reports High School Reform in Chicago Public Schools : An Overview June 2009

The authors wish to acknowledge our partnership with the Chicago Public Schools in conducting this research, and particularly thank Bret Feranchak for his extensive assistance. In addition, we wish to thank Steve Cantrell and Ramona Thomas of the Bill & Melinda Gates Foundation for their guidance. The views, findings, and conclusions expressed herein are those of the authors and do not necessarily express the views of the foundation. Any formal endorsement by CCSR's Steering Committee, their organizations, or CCSR's directors should not be assumed.
A Hierarchical Task-Network Planner based on Symbolic Model Checking

Although several approaches have been developed for planning in nondeterministic domains, solving large planning problems is still quite difficult. In this work, we present a novel algorithm, called YoYo, for planning in nondeterministic domains under the assumption of full observability. This algorithm enables us to combine the power of search-control strategies as in Planning with Hierarchical Task Networks (HTNs) with techniques from the Planning via Symbolic Model-Checking (SMC). Our experimental evaluation confirms the potentialities of our approach, demonstrating that it combines the advantages of these paradigms.
Cultural and demic diffusion of first farmers, herders,and their innovations across Eurasia

Was the spread of agro-pastoralism from the Eurasian founder regions dominated by demic or by cultural diffusion? This study employs simulations that unfold a complex inter-regional and time varying pattern of demic and diffusive exchange processes during the Neolithisation, and thus supports from a modelling perspective the hypothesis that there is no simple or exclusive demic or cultural diffusion, but that in most regions of Eurasia a combination of demic and cultural processes were important.
We are condemned to learn: Higher education as a learning society.

As higher education faces challenges to adapt to changing social, political, and labour-force contexts this is an opportune time to examine these influences. Demands come from the economy, mediated by the neo-liberal state, to reform, attend to the interests of the job market, become less dependent on the state and have more inclusive access policies. The language and values of the economy insert themselves into the discourse, management and pedagogic practices of the university. The ideas of Jurgen Habermas are useful for understanding this dynamic and for plotting a way forward. His ideas on the relationship between the state, economy and civil society are utilised, as are his ideas on colonisation of the lifeworld, the demise of the public sphere and his ‘Theory of Communicative Action’. This paper moves towards rethinking the aims of higher education as a community of rational and democratic discourses within which democracy is learned and practised. It redefines democracy (and higher education) as a learning society.
In nite-dimensional and continuous-time moving average processes

This thesis consists of two parts both dealing with topics in time series analysis. In Chapter 2 we study necessary and su cient conditions for the existence of strictly stationary solutions of ARMA equations in a separable complex Banach space B of the form Yt − A1Yt−1 − . − ApYt−p = B0Zt + . +BqZt−q, t ∈ Z, where A1, . , Ap and B0, . , Bq are linear continuous operators in B with Ap 6= 0 and Bq 6= 0. First, we obtain conditions for ARMA(1,q) equations by excluding zero and the unit circle from the spectrum of the operator of the AR part, where we use a decomposition of A1 similar to the Jordan decomposition of matrices. We then extend this to ARMA(p,q) equations by using a state space representation of an ARMA(p,q) process as an ARMA(1,q) process. We also show that many ARMA processes in Banach spaces possess a moving average process representation of the form Yt = ∞ ∑ k=−∞ ψkZt−k, t ∈ Z, where the coe cients (ψk)k∈Z can be calculated as the coe cients of a Laurent series. Finally, we discuss various examples illustrating what may happen if one drops the assumptions we made. In Chapter 3 we study the asymptotic behaviour of the covariance estimator for a continuous-time moving average process with long memory. A continuous-time moving average is here a process (Xt)t∈R of the form Xt := ∫ ∞ −∞ f(t− s) dLs, t ∈ R, where f is a real function in L(R) and (Lt)t∈R is a two-sided Lévy process with E[L1] = 0 and Var(L1) <∞. We choose f to be decaying polynomially slowly at in nity such that (Xt)t∈R exhibits the long-memory property ∞ ∑ k=−∞ |γ(k)| =∞, where γ(h) := Cov(X0, Xh). We then show, depending on the speed of the polynomial decay of f and on the tail behaviour of L1, that the covariance estimator is asymptotically Rosenblatt, stable or normal distributed.
Instagram Virtual Network Addiction and Sleep Quality Among Students Pursuing a Speech and Hearing Course

Background: Currently the social networking application Instagram has taken higher priority of usage over many other such social networking applications. Objectives: In the present study, an attempt was made to determine the relationship between Instagram addiction and sleep quality of students pursuing a speech and hearing course. Methods: The present study adopted a correlational research design. The sample consisted of 110 students, comprised of 18 male and 92 female students aged between 17 and 25 years old from Mysuru city. Students pursuing a speech and hearing course completed the test for Instagram addiction (TIA) developed by D’Souza, Samyukta and Bivera, and Pittsburgh sleep quality index (PSQI) during September to November, 2018. Test for Instagram addiction measured addiction by considering six factors, including lack of control, disengagement, escapism, health and interpersonal troubles, excessive use, and obsession. The PSQI measured global sleep quality. Pearson’s correlations were employed to find the relationship between dimensions of Instagram addiction and sleep quality. Stepwise multiple regression was employed to find the major predictors of sleep quality by factors of Instagram addiction. Results: The results revealed that among students pursuing speech and hearing selected for the study, only 0.9% were definitely addicts and 14.5% were ‘addicts prone’. The majority of the selected sample (60.9%) had healthy sleep quality. As addiction to Instagram increased, sleep quality of dental students decreased linearly and significantly (r = 0.536). ‘Escapism’ (29.8%) and ‘disengagement’ (2.5%) factors of test for Instagram addiction were found to be the major predictor (32.3%) of sleep quality. Conclusions: It was concluded that Instagram addiction affects sleep quality negatively
Processing of Natural Temporal Stimuli by Macaque Retinal Ganglion Cells

This study quantifies the performance of primate retinal ganglion cells in response to natural stimuli. Stimuli were confined to the temporal and chromatic domains and were derived from two contrasting environments, one typically northern European and the other a flower show. The performance of the cells was evaluated by investigating variability of cell responses to repeated stimulus presentations and by comparing measured to model responses. Both analyses yielded a quantity called the coherence rate (in bits per second), which is related to the information rate. Magnocellular (MC) cells yielded coherence rates of up to 100 bits/sec, rates of parvocellular (PC) cells were much lower, and short wavelength (S)-cone-driven ganglion cells yielded intermediate rates. The modeling approach showed that for MC cells, coherence rates were generated almost exclusively by the luminance content of the stimulus. Coherence rates of PC cells were also dominated by achromatic content. This is a consequence of the stimulus structure; luminance varied much more in the natural environment than chromaticity. Only approximately one-sixth of the coherence rate of the PC cells derived from chromatic content, and it was dominated by frequencies below 10 Hz. S-cone-driven ganglion cells also yielded coherence rates dominated by low frequencies. Below 2–3 Hz, PC cell signals contained more power than those of MC cells. Response variation between individual ganglion cells of a particular class was analyzed by constructing generic cells, the properties of which may be relevant for performance higher in the visual system. The approach used here helps define retinal modules useful for studies of higher visual processing of natural stimuli.
An efficient video object segmentation scheme

In this paper, two new algorithms have been proposed for performing video object segmentation. In both algorithms, a new method has been proposed for adaptive threshold estimation for the change detection process. The method is able to provide a reliable estimation of the threshold without knowing explicitly which data corresponds to the moving and non-moving elements in the video sequence. In addition, the use of new specially detected “moving” edgels and also a graph-based edge-linking method that employs both gradient-based and edge-based constraints have also been proposed in order to refine the object segmentation mask. The second algorithm further incorporates an initialisation phase to solve the problems of dis-occluded regions appearing as part of the segmented moving objects. The proposed work has shown a reasonably fast and good video object segmentation technique that operates in real-time and can be applied in applications such as MPEG-4's content-based video coding and home/office/warehouse security. Comparison with one of the MPEG-4 adopted video object segmentation techniques shows that our approach is very significantly faster and yet produces better results.