Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELIGIOUS ROOTS OF FOREIGN POLICY EXCEPTIONALISM

One core element of American exceptionalism has always been public support for a “special” American role in the world. This view has religious underpinnings, but scholars have variously stressed the influence of religious affiliation, of certain beliefs or behavior, or of generalized “civil religion”; empirical research has been lacking to clarify the specific ways that religion shapes foreign policy exceptionalism. An original empirical analysis drawing on the 2008 University of Akron National Survey of Religion and Politics shows numerous effects of religion. For instance, exceptionalist views are most common among Mormons and evangelicals, and are also related to factors such as theological traditionalism and strong religious commitment. America exceptionalism provides greater latitude for what Eugene Wittkopf labeled “militant internationalism. ”
Smallholder Technical Efficiency: Controlling for Environmental Production Conditions

Smallholder agricultural production depends heavily on environmental production conditions that are largely exogenously determined. Yet few data sets collect necessary, detailed information on environmental production conditions. This oversight raises the spectre of likely omitted variables bias because farmers' input choices typically respond in part to environmental conditions. Moreover, because environmental production conditions are rarely symmetrically distributed, the omission also generally leads to upward bias in estimated technical inefficiency and to biased estimates of the correlates of estimated technical inefficiency as well. Using panel data from 464 traditional rice plots in Cote d'Ivoire, we show that controlling for heterogeneous environmental production conditions significantly changes inferences, perhaps especially with respect to smallholder rice farmers' estimated technical inefficiency.
Towards autonomous bootstrapping for life-long learning categorization tasks

We present an exemplar-based learning approach for incremental and life-long learning of visual categories. The basic concept of the proposed learning method is to subdivide the learning process into two phases. In the first phase we utilize supervised learning to generate an appropriate category seed, while in the second phase this seed is used to autonomously bootstrap the visual representation. This second learning phase is especially useful for assistive systems like a mobile robot, because the visual knowledge can be enhanced even if no tutor is present. Although for this autonomous bootstrapping no category labels are provided, we argue that contextual information is beneficial for this process. Finally we investigate the effect of the proposed second learning phase with respect to the overall categorization performance.
Moviéndose con la mente y el cuerpo: entendiendo la diferencia entre planear y realizar rutas en el espacio construido

This paper is concerned with route behavior in people. Specifically, it aims to better understand whether people follow routes planned in advance, and whether these routes are identical irrespective of the direction of travel. A total of 42 participants (27 belonging to UTFSM and 15 from outside) were asked to trace routed between a pair of points in a map of the campus. After that, they were brought to these places and asked to physically navigate these routes. The main results showed that planned routes were not necessarily employed in real-world scenarios, and that people often changed routes depending on the direction of travel. These results suggest that route choice criteria are somehow dependant on contextual information.
Pupil Identity and Differentiation in British Public Schools

Abstract A considerable amount of social research has addressed the issue of ‘working class’ pupil sub‐cultures. This paper shifts the focus to consider the nature and significance of patterns of differentiation within contemporary public schools. The analysis draws on the life‐histories of a number of people who attended a range of public schools in the 1980s. A context specific understanding of the concept ‘sub‐culture’ is shown to provide a means of reaching beyond the impression of a homogeneous entity to reveal the importance of group distinction and closure. Membership of, or exclusion from, sub‐groups is seen to be bound up with background and cultural priorities. It is argued that an awareness of internal differentiation and its social origins offers a route to understanding the varying experiences and (social and occupational) consequences of public school attendance.
How can we successfully measure well-being through measuring happiness?

This thesis is an investigation into how successfully we can measure wellbeing through measuring happiness. We care about our well-being – how well our lives are going for us. And we often treat happiness as a proxy for well-being in our practical lives. It is no surprise, therefore, that there is a burgeoning field of social science that aims to measure well-being through measuring happiness. There is no consensus in this field, however, over what well-being and happiness are, and how successfully we can measure the former through measuring the latter. It is these issues that I aim to address in this thesis. I will argue in favour of the Indicator View, according to which we should treat happiness as an indicator of local changes in well-being. I will further argue that some of the local changes in well-being indicated by happiness constitute an important aspect of our well-being (what I will call our local well-being). The upshot is that we can measure an important aspect of well-being –namely changes in local well-being – through measuring happiness. This conclusion is directly relevant to the empirical study of well-being for two reasons. First, I will employ an account of happiness that is similar to one of the main constructs used by social scientists in the measurement of wellbeing. Second, my conclusion rests on an understanding of well-being that is consistent with all plausible substantive theories of well-being.
Some reactions of Japanese university students to persuasive communications

In October 1960, television viewers in Japan-and shortly thereafter in the United States as well-were shocked witnesses to the assassination of the chairman of the Japan Socialist Party by a fanatical right-wing student. Earlier in that year, demonstrations involving students, professors, labor unionists, and others had forced the government to ask the American ambassador for a postponement of an imminent visit by President Eisenhower. From that turbulent period to the present, Japanese students have been actively, but less dramatically, involved in a number of political issues. They have snake-danced in protest against proposed visits by American nuclear-powered submarines to Japanese ports and have demonstrated in response to military actions by the United States in Vietnam. By the time this report appears, other and newer causes cel~bres may have captured their attention. Despite some similar activities by American students in recent months, the real problems on American campuses, according to at least one qualified observer (Williamson, 1965), are the students who don’t riot-or do anything else. The principal trait of the American student is seen not as unruliness, but as apathy. Are students in the two countries really so different, and is the Japanese student actually as committed on matters of international dispute as his behavior seems to indicate? The research to be described here was designed to provide data bearing
Molecular Mechanisms for Vascular Development and Secondary Cell Wall Formation

Vascular tissues are important for transporting water and nutrients throughout the plant and as physical support of upright growth. The primary constituents of vascular tissues, xylem, and phloem, are derived from the meristematic vascular procambium and cambium. Xylem cells develop secondary cell walls (SCWs) that form the largest part of plant lignocellulosic biomass that serve as a renewable feedstock for biofuel production. For the last decade, research on vascular development and SCW biosynthesis has seen rapid progress due to the importance of these processes to plant biology and to the biofuel industry. Plant hormones, transcriptional regulators and peptide signaling regulate procambium/cambium proliferation, vascular patterning, and xylem differentiation. Transcriptional regulatory pathways play a pivot role in SCW biosynthesis. Although most of these discoveries are derived from research in Arabidopsis, many genes have shown conserved functions in biofuel feedstock species. Here, we review the recent advances in our understanding of vascular development and SCW formation and discuss potential biotechnological uses.
Spontaneous trichoepithelioma in a laboratory mouse: gross, microscopic and immunohistochemical findings

A spontaneous trichoepithelioma occurred in a Swiss OF1 outbred, four-month-old, intact, nulliparous female mouse from a breeding colony. At necropsy, the tumour was a single, well-delineated mass measuring 4.2 cm in major diameter, located in the thoracic region and had an intact haired surface. The regional lymph nodes were not enlarged and no other abnormalities were found. Microscopically, it was composed of a random admixture of budding epithelial islands and cystic structures variable in size. The epithelial islands were composed of basaloid cells. The cystic structures were lined by squamous epithelium with or without a granular cell layer and contained lamellar or amorphous keratin, as well as wide areas of matrical keratinization (ghost cells) with or without a peripheral layer of basaloid cells and calcified contents. Mitotic activity of basaloid cells was moderate to high, but nuclear or mitotic atypia were not observed. High and low molecular weight cytokeratins, profilaggrin and involucrin expression were observed in the tumour. The immunohistochemical profile of this rare type of tumour of the skin of mice, which includes a first-time description of involucrin expression, confirms the histological evidence of differentiation towards more than one segment of follicular epithelium.
Frequency Response Matrix Estimation From Partially Missing Data—for Periodic Inputs

Multivariate nonparametric frequency response estimation is important in engineering. It allows one to get a quick insight into the dynamics of the system from input-output measurements. Sometimes, measurements can be missing due to faulty sensors or communication links. In this paper, we develop a method that estimates the frequency response matrix together with the missing samples from partially known data. In addition, the method can estimate the level of nonlinear (NL) contribution and the additive noise level of weakly NL systems when excited by a periodic excitation. Several special cases can be handled if the reference input is known, like samples missing at the inputs, noisy inputs, and identification in feedback.
Polarimetric SAR Interferometry for Forest Aboveground Biomass Estimation

DISCLAIMER This document describes work undertaken as part of a programme of study at the Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, The Netherlands. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute. ABSTRACT The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is therefore necessary to have robust techniques for speedy assessment of forest biophysical parameters at landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. The estimation of biomass is also crucial to understanding the amount of carbon present globally and the changes that are taking place in the carbon cycle. The advantage of SAR remote sensing in assessing biophysical forest parameters is its ability to penetrate the canopy and cloud cover. The current research work focuses on the retrieval of forest biophysical parameters of the Barkot Forest area, using fully polarimetric C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. The Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. Coherence amplitude has also been used for tree height estimation. Previous research has studied the overestimation in volume scattering caused by polarization orientation angle shift and how deorientaion has helped to compensate for it. Polarization orientation angle shift has been compensated for in this research work. The accuracy assessment for modeled height and AGB has been carried out using field data. The field measured height ranges from 14.3 m to 33 m. The SV ranges from 17.5 to 51.57(m 3 ha −1) and the field measured AGB ranges from 112.58 to 356.06 (t ha −1). The modeled vegetation height values range from 15.95 to 26.93 m and the modelled AGB values range from 158.08 to 515.47(í µí±¡ í µí±í µí± −1). The í µí± 2 value of 0.5, a RMSE of 62.73(í µí±¡ í µí±í µí± −1) and a percent accuracy of 51% were obtained for the modeled biomass. The modeled field height has a í µí± 2 value of …
Deep Understanding of Financial Knowledge through Unsupervised Learning

In this project, a universal information extraction method was implemented and applied to financial area, which supports aggregation and self analysis of complex information from massive correlated sources. In order to extract domain-independent relations between entities, open information extraction algorithm is used. Firstly, we actively label dataset using unsupervised learning algorithm by leveraging semantic analysis techniques based on features such as grammatical structure, semantic roles, etc. The labeled training set will then be used to train extractor model, which will be further utilized to extract relations from any text efficiently and effectively. Finally, the extracted relations will be stored in database for future query. We compared and analyzed results of different models, measured the importance of features using feature selection and also built a simple UI tool to illustrate our methods. Index Terms — relation based search, supervised and unsupervised learning
The Assessment of Proteus mirabilis Susceptibility to Ceftazidime and Ciprofloxacin and the Impact of These Antibiotics at Subinhibitory Concentrations on Proteus mirabilis Biofilms

Rods of the Proteus genus are commonly isolated from patients, especially from the urinary tracts of the catheterised patients. The infections associated with biomaterials are crucial therapeutic obstacles, due to the bactericidal resistance of the biofilm. The aim of this study was to assess the susceptibility of P. mirabilis planktonic forms to ciprofloxacin and ceftazidime, the ability to form biofilm, and the impact of chosen sub-MIC concentrations of these antibiotics on biofilm at different stages of its formation. The research included 50 P. mirabilis strains isolated from wounds and the urinary tracts from patients of the University Hospital No. 1 in Bydgoszcz. The assessment of susceptibility to ciprofloxacin and ceftazidime was conducted using micromethods. The impact of sub-MIC concentrations of the chosen antibiotics on the biofilm was measured using the TTC method. The resistance to ciprofloxacin was confirmed for 20 strains (40.0%) while to ceftazidime for 32 (64.0%) of the tested P. mirabilis strains. All of the tested strains formed biofilm: 24.0% weakly, 26.0% moderately, and 50.0% strongly. It was determined that ciprofloxacin and ceftazidime caused eradication of the biofilm. Moreover, the connection between origin of the strains, biofilm maturity level, and resistance to antibiotics was proved.
A personalized products selection assistance based on e-commerce machine learning

The prosperity of electronic commerce has changed the traditional trading behaviors. More and more people are willing to perform Internet shopping. At the same time, consumers experience information overload and look for help in selecting from an overwhelming array of products. In order to overcome such a problem one option is to develop a personalized online assistance to retrieve product information that really matters for the customers. In this paper, we present a method that combines the genetic algorithm and k nearest neighbor technology to reason about the customer's personal preferences from his/her profile and then provide the most appropriate products to meet his/her needs. Our experimental results are showing that our systems have a bright future.
Factors in the Psychoanalytic Treatment of Narcissistic Personalities

N THIS PAPER I shall discuss the etiology, diagnosis, prognosis, and some factors in the treatment of patients with narcissistic I personality structure. I do not expect to treat the subject exhaustively, but I hope to shed new light on certain areas. This paper deals mainly with the clinical problem of narcissism, and such metapsychological considerations as will be presented shortly have to do only with the etiology of pathological narcissism and not with the broader issue of the theory of narcissism in psychoanalysis. I suggested in an earlier paper (8) that narcissistic as a descriptive term has been both abused and overused, but that there does exist a group of patients in whom the main problem appears to be the disturbance of their self-regard in connection with specific disturbances in their object relationships, and whom we might consider almost a pure culture of pathological development of narcissism, It is for these patients that I would reserve the term narcissistic personalities. On the surface, these patients may not present seriously disturbed behavior; some of them may function socially very well, and they usually have much better impulse control than the infantile personality.
Mitochondrial Cyclophilin D in Vascular Oxidative Stress and Hypertension

Vascular superoxide (O˙2-) and inflammation contribute to hypertension. The mitochondria are an important source of O˙2-; however, the regulation of mitochondrial O˙2- and the antihypertensive potential of targeting the mitochondria remain poorly defined. Angiotensin II and inflammatory cytokines, such as interleukin 17A and tumor necrosis factor-&agr; (TNF&agr;) significantly contribute to hypertension. We hypothesized that angiotensin II and cytokines co-operatively induce cyclophilin D (CypD)–dependent mitochondrial O˙2- production in hypertension. We tested whether CypD inhibition attenuates endothelial oxidative stress and reduces hypertension. CypD depletion in CypD−/− mice prevents overproduction of mitochondrial O˙2- in angiotensin II–infused mice, attenuates hypertension by 20 mm Hg, and improves vascular relaxation compared with wild-type C57Bl/6J mice. Treatment of hypertensive mice with the specific CypD inhibitor Sanglifehrin A reduces blood pressure by 28 mm Hg, inhibits production of mitochondrial O˙2- by 40%, and improves vascular relaxation. Angiotensin II–induced hypertension was associated with CypD redox activation by S-glutathionylation, and expression of the mitochondria-targeted H2O2 scavenger, catalase, abolished CypD S-glutathionylation, prevented stimulation mitochondrial O˙2-, and attenuated hypertension. The functional role of cytokine–angiotensin II interplay was confirmed by co-operative stimulation of mitochondrial O˙2- by 3-fold in cultured endothelial cells and impairment of aortic relaxation incubated with combination of angiotensin II, interleukin 17A, and tumor necrosis factor-&agr; which was prevented by CypD depletion or expression of mitochondria-targeted SOD2 and catalase. These data support a novel role of CypD in hypertension and demonstrate that targeting CypD decreases mitochondrial O˙2-, improves vascular relaxation, and reduces hypertension.
Robust brain MRI denoising and segmentation using enhanced non‐local means algorithm

Image denoising is an integral component of many practical medical systems. Non‐local means (NLM) is an effective method for image denoising which exploits the inherent structural redundancy present in images. Improved adaptive non‐local means (IANLM) is an improved variant of classical NLM based on a robust threshold criterion. In this paper, we have proposed an enhanced non‐local means (ENLM) algorithm, for application to brain MRI, by introducing several extensions to the IANLM algorithm. First, a Rician bias correction method is applied for adapting the IANLM algorithm to Rician noise in MR images. Second, a selective median filtering procedure based on fuzzy c‐means algorithm is proposed as a postprocessing step, in order to further improve the quality of IANLM‐filtered image. Third, different parameters of the proposed ENLM algorithm are optimized for application to brain MR images. Different variants of the proposed algorithm have been presented in order to investigate the influence of the proposed modifications. The proposed variants have been validated on both T1‐weighted (T1‐w) and T2‐weighted (T2‐w) simulated and real brain MRI. Compared with other denoising methods, superior quantitative and qualitative denoising results have been obtained for the proposed algorithm. Additionally, the proposed algorithm has been applied to T2‐weighted brain MRI with multiple sclerosis lesion to show its superior capability of preserving pathologically significant information. Finally, impact of the proposed algorithm has been tested on segmentation of brain MRI. Quantitative and qualitative segmentation results verify that the proposed algorithm based segmentation is better compared with segmentation produced by other contemporary techniques.
Fed batch enzymatic saccharification of food waste improves the sugar concentration in the hydrolysates and eventually the ethanol fermentation by Saccharomyces cerevisiae H058

The enzymatic hydrolysis of food waste by commercially available enzymes and the subsequent ethanol fermentation of the hydrolysates by Saccharomyces cerecisiae H058 were studied in this work. The optimum batch enzymatic conditions were found to be saccharification pH of 4.5, temperature of 55! , glucoamylase concentration of 120 u/g, α-amylase concentration of 10 u/g, solid-liquid ratio of 1: 0.75 (w/w). Fed batch hydrolysis process was started with a solid-liquid ratio of 1: 1 (w/w), with solid food waste added at time lapse of 2 h to get a final solid-liquid ratio of 1: 0.5 (w/w). After 4 h of reaction, the reducing sugar concentration reached 194.43 g/L with a enzymatic digestibility of 93.12%. Further fermentation of the batch and fed batch enzymatic hydrolysates, which contained reducing sugar concentration of 131.41 and 194.43 g/L respectively, was performed using Saccharomyces cerevisiae H058, 62.93 and 90.72 g/L ethanol was obtained within 48 h.