Miracle-dz/UniFAR-FTUs huggingface dataset:
The Value of Information in War : Some Experimentel Findings

A common assumption is that what matters in combat outcome is information superiority . The absolute level of uncertainty about the situation in the battlespace is seen as unimportant. Is that true? Results obtained with a dynamic, chessbased wargame indicate that the answer to this question is no the absolute level of uncertainty is important. More specifically the results show that as the absolute level of uncertainty increases, the value of having information superiority as well as the value of having superior strength decreases, whereas the value of having tempo superiority remains unaffected. Two conclusions are drawn. The first is that information superiority may be best created at lower levels of command where uncertainty is at its lowest. The second is that because uncertainty probably will continue to be a problem in war, tempo superiority may be a more viable alternative than information superiority or superior strength for winning. 1 Information superiority is defined as knowing more than the adversary about the situation in the battlespace.
Entrepreneurship in South African township tourism: the impact of interracial social capital

ABSTRACT Ethnic entrepreneurship scholarship has demonstrated the importance of social capital for “minority” entrepreneurs, but these studies presume that social capital is co-ethnic. I complicate this assumption by investigating entrepreneurial black women and interracial social capital in South African township tourism, a niche market within the nation’s growing tourism industry. Drawing from ethnographic fieldwork conducted in two black townships in Cape Town, I spotlight black women who have established home-based bed and breakfasts and formed connections with white Europeans and South Africans during their entrepreneurial journeys. Employing Bourdieu’s theory of capital, I discuss how these entrepreneurs develop ties with whites to acquire social, economic, cultural, and symbolic forms of capital that have been systemically denied to them as black South African women. The interracial transference of these resources underscores the deep inequalities between blacks and whites, but also the agency of marginalized entrepreneurs to attain assets within constricting social structures.
Brains as optimal emergent Turing Machines

The theory and experiments outlined in Weng 2015 [1] modeled brains as naturally emerging Turing Machines (TMs) inside Developmental Networks (DNs) - a new class of brain inspired neural networks. However, TMs originally proposed by Alan Turing 1936 [2] were deterministic. If they involved probability to handle uncertainty, the probability was in the mind of the human programmer for a specific task. Although the task-specific program will run on a Universal TM - a model of the popular Von Neumann Computers - the Universal TM itself had no imbedded probability. Yet, each brain samples from infinitely many stimuli and actions through the real word, unlike a TM that deals with only tape-symbols from a finite and static alphabet. Computationally, is a brain optimal? If the answer is yes, in what sense? This theoretical work reports the overall brain optimality. It shows that a biological brain, modeled by the DN, is optimal in the sense of maximum likelihood, conditioned on (1) the genome program - the Developmental Program (DP) that regulates the development of body, sensors, effectors and the limited computational resource (e.g., brain size and types of neural transmitters), and (2) the incremental lifetime experience - including teaching from the environments and self exploration and discovery through the real world.
Brain white-matter volume loss and glucose hypometabolism precede the clinical symptoms of Huntington's disease.

UNLABELLED We studied the anatomic and functional changes in various brain areas during the course of Huntington's disease (HD) in a large cohort of mutation-positive individuals (n = 71) encompassing the complete range of disability (presymptomatic through stage V), and in healthy controls, for the purpose of defining both degenerative and dysfunctional brain changes in the same subjects. METHODS We used an MRI and unsupervised multiparametric segmentation procedure based on a relaxometric approach to measure in vivo brain volumes in 71 subjects with presymptomatic to advanced HD. The same population was evaluated by 18F-FDG PET to assess variations in brain glucose metabolism. To predict age at onset in unaffected mutation carriers, we considered the estimated number of years from each subject's age to manifested HD symptoms, for a given expanded triplet number. RESULTS Age-adjusted analyses confirmed that the 71 subjects as a group, as well as the subgroup of 24 unaffected presymptomatic subjects at risk for HD, had significantly smaller gray-matter and white-matter volumes and larger cerebrospinal fluid volumes than did controls (P < 0.0001). In the 24 presymptomatic subjects, we observed a significant inverse linear correlation between white-matter volume reduction and the estimated time to symptom onset (r2= 0.39; P = 0.0011). Both clinically unaffected subjects at risk for HD and symptomatic patients had significantly decreased glucose uptake in the cortex (frontal and temporal lobes) and striatum (caudate and putamen). HD subjects who were followed up longitudinally showed progressive white-matter reduction in the preclinical subjects (n = 10) and decreased glucose uptake in the cortex and striatum in affected (n = 21) and preclinical (n = 10) subjects. CONCLUSION White-matter volume loss may precede gray-matter atrophy and may be associated with neuronal dysfunction in early disease.
Demand system estimation with individual heterogeneity: an analysis using panel data on households *

The main goal of this paper is to assess the importance of controlling individual unobservable effects and measurement errors when analysing demand patterns at the microeconomic level. We provide empirical evidence on the demand for non-durable goods using a panel of households from the Spanish Continuous Family Expenditure Survey. The functional form we adopt is based upon the Almost Ideal Model. We describe how heterogeneity among consumers and measurement errors affect inferences on expenditure and price effects. We cannot reject the presence of correlated unobserved heterogeneity that could bias pooled estimates. In general, income effects show a downward bias and price effects an upward bias. We also describe specific patterns for the bias derived from each source of error, by using suitable instruments.
Director Shareownership and Corporate Performance in South Africa

This paper investigates the relationship between director shareownership and corporate performance in South Africa using a sample of 169 listed firms from 2002 to 2007. Our results suggest a statistically significant and positive association between director shareownership and corporate performance. By contrast, we find no evidence of a non-linear effect of director shareownership on corporate performance. Our findings are robust across a raft of econometric models that control for different types of endogeneity problems and corporate performance proxies. Overall, our results provide support for agency theory, which suggests that director shareownership can reduce agency problems by aligning more closely the interests of shareholders and corporate executives, and thereby improving corporate performance.
Relationship Difficulties In Social Anxiety Disorder

Little is known about the quality of socially anxious individuals’ romantic relationships. Because social anxiety is associated with negative perceptual biases toward one’s own interpersonal interactions, research on this topic needs to move beyond self-report. The present research was aimed at better understanding of the romantic relationships of the socially anxious, with a focus on social support and perceived criticism as assessed from multiple perspectives. In Chapter 1, we examined longitudinal associations between social anxiety, social support, and relationship dissolution and compared levels of support behavior between couples high and low in social anxiety during a laboratory-based interaction. Men’s social anxiety and low perceived, but not received, support predicted higher rates of break-up one year later. Although individuals high in social anxiety reported lower levels of support during the interaction task than those low in social anxiety, the two groups did not differ on partneror observer-rated measures of support. In Chapter 2, we examined associations between social anxiety, perceived and expressed criticism, and reactions to criticism. Social anxiety was unrelated to perceived criticism, but was associated with greater self-reported global expressed criticism of one’s partner. Among women social anxiety was related to being more upset when criticized by a partner. High and low social anxiety couples did not differ in criticism during a laboratory-based problemsolving task, though high social anxiety participants tended to be more upset by criticism. In Chapter 3, we compared levels of perceived and expressed criticism and reactions to criticism among individuals with social anxiety disorder, with other anxiety disorders, and with no psychiatric disorder. Individuals with anxiety disorders showed elevated levels of interaction-specific perceived criticism, expressed criticism, and upset and stress due to criticism relative to normal controls; however, the two anxious groups did not differ on any measures. Upset due to criticism mediated the association between diagnosis and relationship satisfaction. Collectively, results suggest that social anxiety is associated with difficulties even in established romantic relationships and point to perceptions of social support and criticism as fruitful targets for intervention in this population. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Psychology First Advisor Dianne L. Chambless
Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity

The brain enables animals to behaviorally adapt in order to survive in a complex and dynamic environment, but how reward-oriented behaviors are achieved and computed by its underlying neural circuitry is an open question. To address this concern, we have developed a spiking model of the basal ganglia (BG) that learns to dis-inhibit the action leading to a reward despite ongoing changes in the reward schedule. The architecture of the network features the two pathways commonly described in BG, the direct (denoted D1) and the indirect (denoted D2) pathway, as well as a loop involving striatum and the dopaminergic system. The activity of these dopaminergic neurons conveys the reward prediction error (RPE), which determines the magnitude of synaptic plasticity within the different pathways. All plastic connections implement a versatile four-factor learning rule derived from Bayesian inference that depends upon pre- and post-synaptic activity, receptor type, and dopamine level. Synaptic weight updates occur in the D1 or D2 pathways depending on the sign of the RPE, and an efference copy informs upstream nuclei about the action selected. We demonstrate successful performance of the system in a multiple-choice learning task with a transiently changing reward schedule. We simulate lesioning of the various pathways and show that a condition without the D2 pathway fares worse than one without D1. Additionally, we simulate the degeneration observed in Parkinson's disease (PD) by decreasing the number of dopaminergic neurons during learning. The results suggest that the D1 pathway impairment in PD might have been overlooked. Furthermore, an analysis of the alterations in the synaptic weights shows that using the absolute reward value instead of the RPE leads to a larger change in D1.
Neurite outgrowth and protein synthesis by PC12 cells as a function of substratum and nerve growth factor

Numerous studies have implied that enhanced cell-substratum adhesion plays a role in neurite outgrowth by neuronal cells. Using an extracellular matrix (ECM) produced by cultured corneal endothelial cells, we have investigated attachment and de novo neurite outgrowth by the pheochromocytoma cell line, PC12. PC12 cells were found to attach more rapidly and efficiently to the ECM than to plastic or collagen- coated surfaces. An extensive but temporary (5- to 10-day) neurite outgrowth occurred in the absence of nerve growth factor (NGF) when cells were on the ECM. However, long term neurite survival and further elongation required NGF. Our findings are consistent with the hypothesis that protein(s) in the ECM has an important role in neurite outgrowth. Thus, NGF may not so much initiate neurite outgrowth as it stabilizes neurites. ECM and NGF also were found to modulate cellular protein synthesis by PC12 cells. On ECM, a decreased synthesis of many high molecular weight proteins (Mr greater than 85,000) was observed in comparison to that of cells on collagen-coated dishes. The presence of neurites (in the presence of absence of NGF) as associated with the induction of the synthesis of a cellular protein (Mr = 55,000 to 56,000 and pI of 5.6). NGF was found to increase markedly the synthesis of two secreted proteins, while it drastically reduced the synthesis of all others regardless of the substratum upon which the cells were maintained.
Bit-plane watermarking for zerotree-coded images

In this paper, we develop a robust bit-plane watermarking technique based on zerotree coding. A robust watermark is an imperceptible but indelible code that can be used for ownership identification. Zerotree-based encoders are popular owing to their high coding efficiency, low coding complexity, and the capability of generating scalable bitstreams. Efficient image compression and watermarking algorithms use similar techniques to reduce the introduced visual artifacts. In contrast to the conventional approaches where compression and watermarking are treated independently, the proposed method integrates these two operations. The watermark is inserted by directly modifying the output bitstream of the zerotree-based quantizer. Since the watermarking framework is tightly coupled with compression, we can avoid adding watermark information to the coefficients that would be susceptible to quantization errors. Furthermore, this compressed-domain watermarking framework may reduce the system's complexity since watermark embedding and retrieval may be performed directly in the compressed domain. Security of the system relies on the secure keys that determine the watermark signal and watermarking locations. Complete evaluation is conducted against both noise-type and geometric attacks. Experimental results show that our method survives the aforementioned attacks and the performance is competitive with or better than transform-domain approaches.
PENGARUH MODEL PEMBELAJARAN KOLABORATIF BERBASIS LESSON STUDY LEARNING COMMUNITY (LSLC)

This research to determine whether or not the influence of Collaborative Learning model Based on Lesson Study Learning Communiy (LSLC) on the results of students' learning grade VIII MTsN Samalanga. The population of this research is all students of grade VIII MTsN Samalanga. While to determine the sample used purposive sampling technique. So the sample of this research is class VIIIA which amounted to 31 people (experiment class) and class VIIIB which amounted to 31 people (control class). The method used is quasi experimental research method (quasi experimental). Data collection is done through documentation and tests. Based on the results of data analysis obtained t_hitung> t_tabel is 5.60> 1.67 then Ho is rejected. In the experimental class students do sharing task and jumping task, so that the collaboration and student learning outcomes increase. So it can be concluded that the lesson learning learning commuity (LSLC) collaborative learning model has an effect on the students' achievement of grade VIII MTsN Samalanga.
Cutting Plane MAP Inference for Markov Logic

In this work we present Cutting Plane Inference (CPI) for MAP inference in Markov Logic. CPI incrementally solves partial Ground Markov Networks, adding formulae only if they are violated in the current so-lution. We show dramatic improvements in terms of e(cid:30)ciency, and discuss scenarios where CPI is likely to be fast.
First-Generation Adenovirus Vectors Shorten Survival Time in a Murine Model of Sepsis1

Adverse immunological reactions to adenoviral vectors have significantly impacted the utility of this virus for treating genetic and environmentally induced diseases. In this study, we evaluate the effect of adenoviral vectors on an animal model of sepsis. Systemic delivery of first-generation adenoviral vectors to septic mice (cecal ligation and puncture) resulted in a shortened survival time. This effect was not observed with second-generation or inactivated first-generation vectors. The accelerated death was accompanied by a number of important changes in the disease. These changes included increased liver cell apoptosis (including Kupffer cells) and a marked increase in liver bacterial load. In the lung, the combination induced an increase in bacterial load, as well as greater lung injury. In the serum, the combination was associated with decreased TNF-α levels and an increase in bacterial load. Finally, a profound degree of lymphocyte apoptosis was observed in these animals. These observations suggest that prior exposure to first-generation adenovirus gene therapy vectors may worsen the outcome of some forms of sepsis.
Estimating the Burden of Malaria in Senegal: Bayesian Zero-Inflated Binomial Geostatistical Modeling of the MIS 2008 Data

The Research Center for Human Development in Dakar (CRDH) with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP) conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS), the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB) were developed to take into account the large number of zero-prevalence survey locations (70%) in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC) methods were used for inference. Several insecticide treated nets (ITN) coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08%) whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940). The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate in modeling sparse geostatistical survey data, expected to arise more frequently as malaria research is focused on elimination.
Autonomous mobile robot positioning using Unscented HybridSLAM

This paper addresses a novel approach to Simultaneous Localization and Mapping problem called Unscented HybridSLAM. Analyzing loop closing as one of the most important aspects of SLAM is the major interest of this study. Closing a loop by an autonomous mobile robot can be tricky even in the presence of a correct data association in the process, especially, when the loop is considerably large. The main challenge is to maintain a track of all correlations among landmarks and the mobile robot using Unscented HybridSLAM. The performance of proposed algorithm is evaluated with a loop closing scenario simulation, then, the results are discussed and compared with other algorithms.
Predictors of long-term survival in nonagenarians: the NonaSantfeliu study.

BACKGROUND few studies have prospectively evaluated long-term predictors of mortality in nonagenarians. OBJECTIVE to determine predictors of death in a nonagenarian cohort after 5 years of follow-up. DESIGN a prospective community-based study. SETTING a community-based study. SUBJECTS one hundred and eighty-six nonagenarians both living in the community and institutionalised. METHODS functional status was determined by the Lawton-Brody and Barthel Indexes (BI) and cognition by the Spanish version of the mental state examination (MEC). The Charlson Index was used to measure comorbidity. Nutritional status was evaluated by the short version of the Mini-Nutritional Assessment questionnaire. RESULTS mortality after 5 years was 75.53%. Patients who did not survive were significantly older, with lower cognitive and functional performance, with diminished visual acuity, higher comorbidity, high risk of malnutrition, higher number of drugs taken and a higher percentage of patients with the diagnosis of dyslipidaemia, heart failure or previous stroke. Cox regression analysis, identified the Charlson Index (hazard ratio 1.23, 95% CI 1.09-1.37) and MEC (hazard ratio 0.98, 95% CI 0.97-0.99) as independent predictors of mortality after 5 years. CONCLUSIONS better cognitive status and lesser comorbidity at baseline are the best predictors to identify which nonagenarians survived after a 5-year follow-up period.
An Insight into CLIL in the Canary Islands Autonomous Community: Key Aspects and Students’ Achievements

The intent of this preliminary research was to gain insights into the implementation of Content and Language Integrated Learning (CLIL) in The Canary Islands Autonomous Community, where since 2004-2005 many primary and secondary schools have been gradually adopting this methodology in the classroom. Hardly any research has focused attention on this context. This study attempts to fills this void in the literature by examining three different issues. Firstly, CLIL learners� performance in the English test in the University Admission Examination was compared with the performance of their non-CLIL counterparts; secondly, the variety of content-subjects taught through the medium of English was examined; and finally, attention was centered on the number of academic courses with any CLIL subject that the participants in the study had had. First year university learners from three different degrees who had been enrolled in English as a foreign language instruction (EFL) and CLIL completed a questionnaire designed ad hoc. These learners belonged to the first and second generation of CLIL instruction. The data gathered corroborate previous findings and identify some of the features of CLIL instruction in its first decade of existence in this region. The chapter concludes with several implications for research and practice.