VictorJuiz/thesis huggingface dataset:
An examination of some problems of the language of St. Matthew's Gospel
Keywords: Bible
Matthew's Gospel
New Testament
language

In the first chapter of this work the language of St. Matthew's gospel is set in the context of general New Testament linguistic study in this century. The differing emphases of Semitists such as Torrey, Burney, Dalman and Black on the extent of Semitic influence on New Testament Greek are set side by side with the work of Hellenists such as Moulton and Deissmann in placing the New Testament language with the spoken Greek of its period. Account is taken of the contributions to this debate made by Lars Rydbeck in his isolation of a group of technical prose writers of the 1st century A.D. with linguistic affinities to the New Testament writers and by Klaus Beyer in examining New Testament Greek syntax on the basis of possible and impossible methods of expression in Aramaic and Hebrew.
The problem of finding Aramaic contemporary in time and place to the New Testament writings is considered and the different kinds of Aramaic used by various scholars as source material for an Aramaic approach are assessed. The Aramaic discoveries from Qumran, in particular the Genesis Apocryphon, and the material from Murabba’at are regarded in this thesis as the Aramaic closest to that employed by Jesus and his followers, while the use of later Targumic material, especially in a confirmatory rôle, is not excluded. Among the various Targums used in this work the contribution to the Aramaic approach made by the discovery of Codex Neofiti I of a Palestinian Pentateuch Targum is regarded as important. The extent to which Hebrew and Greek were known in 1st century A.D. Palestine is also discussed and a tri-lingual situation is favoured on the basis of the latest archaeological discoveries.
Continued in thesis ...
Political fictions and fictional politics: a comparative study of the political unconscious in the Turkish and Kurdish novel
Keywords: modern Turkish literature
Orhan Pamuk
politics of language
Mehmet Uzun
politics of history
Ereb Shemo
modern Kurdish literature
Kemal Tahir
Esat Mahmut Karakurt
Fredric Jameson
Hesene Mete
politics of religion
politics of love
the political unconscious

This thesis presents a comparative and interdisciplinary investigation into the relationship between politics and the Turkish and Kurdish novels, which are treated not only as artistic constructions but also as socio-cultural and historical artefacts. The primary objective of this investigation is to understand the principle social, political, and historical reasons and root causes behind the close relationship between politics and literatures in Turkey and the principle socio-political and literary ramifications of such strong relationship. Towards this end, the thesis focuses on four main themes: language, love, religion, and history. Besides being the most common novelistic themes in the Turkish and Kurdish literary institutions, these are inherently heavily politicised and ethno-nationalistically charged themes—thus especially suitable for such inquiry.
In line with this politico-historical and literary vein, the thesis also discusses some of the main political questions in Turkey, viz., the reasons behind the failure of Turkish democracy, its maladies and the resultant deadlock on some of the most important issues of the modern history of the country such as the Kurdish imbroglio and the conflict of secularisation and Islam. As the discussions on politics of love, language, religion, and history show, profound ideological competitions and antagonisms do not necessarily mean divergent political and literary structures. As such, the strong links between the Turkish and Kurdish literary institutions, as well as the ordeal of the Kurdish question and democratisation in Turkey, is as much caused by rival nationalisms, hostile ideological positions, and the like as by congruity, parallel political visions, and similar power structures. The main argument of the thesis, thus, is that the Kurdish and Turkish literary, political, and intellectual actors could not contribute towards the solution of the persistent political and literary questions in Turkey because of their failure in adopting a transformative politics and developing fully autonomous literatures. The future of the two literatures, as was in the past, this thesis argues, will remain intrinsically bound to the political structures and developments and the future of democracy in Turkey.
Essays on macro-labour and uncertainty
Keywords: migration
brain-drain
uncertainty
macro-labour

This dissertation consists of three self-contained chapters which discuss topics related to macro-labour and uncertainty. Chapter 1 examines the impact of cross-border migration on business cycle dynamics and focuses on the implications of brain-drain for origin countries. Through the lens of an open-economy DSGE model that features endogenous migration flows, trade linkages, search frictions, and skill heterogeneity, I study the quantitative impact of cyclical migration in Greece during the European Debt Crisis. I find that rather than stabilising the Greek business cycle, migration led to a deeper and more protracted recession, primarily due to the negative effects it had on the skill composition of the domestic workforce and investment. Chapter 2 explores the role of labour market frictions and specifically the role of endogenous job destruction for the propagation of uncertainty shocks. To address this topic, I build a DSGE model with search and matching frictions, price rigidities and time-varying stochastic volatility, and I calibrate the model to US data. I find that endogenous job separations play an important amplification role for uncertainty shocks. I also find that the introduction of endogenous match separations can challenge the widely-held perception that uncertainty shocks behave like negative aggregate demand shocks, as the behaviour of inflation hinges on the specification of the Taylor rule. Finally, Chapter 3 analyses the impact of uncertainty shocks on firm entry, trade and labour markets through the lens of a DSGE model with endogenous producer entry. I find that contrary to models with a fixed mass of producers, precautionary savings propagate uncertainty shocks through two distinct mechanisms. The first one is the aggregate demand mechanism which is at play in models without endogenous firm entry. The second channel however, arises from the interplay of precautionary behaviour and endogenous firm entry. Precautionary savings from households lead to higher entry of relatively less productive non-trading firms, driving down aggregate productivity and creating inflationary pressures.
A Riemannian perspective on matrix recovery and constrained optimization
Keywords: constrained optimization
nonlinear matrix recovery
Riemannian optimization
registration
nonconvex optimization
denoising

Nonlinear matrix recovery is an emerging paradigm in which specific classes of high-rank matrices can be recovered from an underdetermined linear system of measurements. In particular, we consider matrices whose columns, seen as data points, belong to an algebraic variety, namely, a set defined by finitely many polynomial equations. The nonlinear structure is exploited using an appropriately chosen feature map, which induces a low-rank structure in the feature space, thus allowing recovery of the original (high-rank) matrix. The same framework is applicable to matrices whose columns are divided in clusters, so that we can address clustering tasks with missing entries.
We formulate the rank minimization of the feature matrix as the minimization of a smooth cost function on a Riemannian manifold, which then allows us to employ the theoretically rigorous Riemannian optimization framework, that calls on differential geometry tools to construct feasible iterative algorithms on specific Riemannian manifolds. In particular, we show the potential benefits of using second-order algorithmic variants --- instead of first-order ones --- as they are able to achieve recovery of the original data with high accuracy. We additionally develop an alternating minimization method to solve the recovery problem, for which we give convergence and complexity guarantees.
Considering algebraic varieties also leads us to propose a new approach for the denoising of point clouds that approximately fit such structures, as well as for their registration, namely, the task of estimating a transformation which overlaps two point clouds representing the same shape in different coordinate systems.
Finally, we consider general optimization problems with smooth equality constraints. Due to the challenge of achieving feasibility for generic nonlinear equality constraints, we must depart from the Riemannian framework and we propose an infeasible algorithm which minimizes a smooth penalty function, known as Fletcher's augmented Lagrangian. We provide optimal worst-case bounds on the number of iterations that are required to find an approximate first- and second-order critical point.
Super-resolution microscopy with spatial modes of light
Keywords: quantum metrology
microscopy
super resolution
quantum optics
imaging

The resolution of imaging devices is ultimately limited by the diffraction of light. This limit can be circumvented by exploiting near-field phenomena, non-linearities of the sample or specific illumination schemes, which led to the recent explosion of optical super-resolution techniques. However, it would be desirable to reach the nanoscale in the most general way possible, with far-field linear imaging of uniformly illuminated samples.
In the last few years, the answer to that came with the field of quantum-inspired super-resolution (QISR), where quantum metrological techniques were used to find novel measurement schemes that, beyond the conventional direct imaging of light, would achieve higher precisions. Interestingly, these ideas would always in some way or another involve transverse spatial modes of light. This thesis presents our work on the subject, with novel theoretical and experimental results.
Firstly, we develop the traditional theory of QISR, with has mostly focused on either the estimation of separation of two point sources or on geometric moments of samples. Then, we introduce our own results on optical imaging of general distributions of point sources, in a step to take QISR from toy examples to real imaging scenarios.
Secondly, we apply all the concepts studied on a experimental, proof-of-principle implementation of a QISR scheme dubbed Hermite-Gaussian Microscopy (HGM), which uses heterodyne detection with several Hermite-Gaussian modes as local oscillator in order to reconstruct the object sample and achieve super-resolution. We report the techniques necessary for the manipulation of spatial modes of light, as well as our results, where we demonstrated 2D imaging with twofold resolution enhancement beyond the diffraction limit.
Approximate message passing for compressed sensing magnetic resonance imaging
Keywords: approximate message passing
magnetic resonance imaging
image reconstruction
compressed sensing

Magnetic Resonance Imaging (MRI) is a non-invasive, non-ionising imaging modality with unrivalled soft tissue contrast. A key consideration for MRI is data acquisition time, which is limited by inherent technological and physiological constraints. Compressed sensing is a relatively recent framework that can reduce the MRI acquisition time by undersampling randomly and exploiting presumed redundancies in the data.
The Approximate Message Passing (AMP) algorithm is an iterative compressed sensing method that efficiently reconstructs signals that have been sampled with i.i.d. sub-Gaussian sensing matrices. However, when Fourier coefficients of a signal with non-uniform spectral density are sampled, such as in MRI, AMP performs poorly in practice.
In response, this thesis proposes the Variable Density Approximate Message Passing (VDAMP) algorithm for undersampled MRI data. We present three versions of VDAMP: single-coil VDAMP, where receiver coil sensitivities are ignored, Parallel-VDAMP (P-VDAMP), which includes coil sensitivities, and Denoising-P-VDAMP (D-P-VDAMP), which incorporates the statistical modelling capabilities of neural networks. Central to VDAMP is a property that we term "coloured state evolution", where the difference between the intermediate image estimate at a given iteration and the ground truth is distributed according to a zero-mean Gaussian with known covariance. We demonstrate that coloured state evolution can be leveraged to yield an algorithm that converges rapidly, and to a competitive reconstruction quality, without the need to hand-tune model parameters.
Taste and see: real presence as revelation in Heideggerian perspective
Keywords: phenomenology
real presence
Eucharist
revelation
Heidegger

This project addresses the Christian of doctrine of revelation by asking how Christians are able to translate an ontological expression of divine self-communication (i.e., the Incarnation of Jesus Christ) into intellectual faith statements in a way that retains something essential of that ontological revelation. The argument of this project is that such incarnational revelation must be understood through encounter, so that the Eucharist—as the site of Christ’s attested real presence—becomes the natural site in which to explore such encounter as the ground of Christian speech. What follows is a theological experiment in which the Eucharist is evaluated in terms of its capacity to reveal the person of Jesus Christ in a post-metaphysical milieu and to shape the understanding of Christians who encounter Christ therein.
In order to establish this constructive argument, this project consults the work of Martin Heidegger. Heidegger’s notion of Being-in-the-world opens up a new definition of understanding, where what is primary is praxis in the form of worldly involvement, so that understanding in the form of habits, mood, and know-how becomes foundational for any knowledge of the beings with which we interact. Language is then linked up with this pre-reflective understanding, first as discourse and then later as poetry, both of which disclose a fundamental world-orientation to language.
As the sacrament where Christ is attested as really present, the material event of the Eucharist becomes a world in the Heideggerian sense, in which Christian participants come to understanding through dynamic involvement. Rather than rooting Christian hermeneutics in mental processes disengaged from embodiment, then, Heidegger helps us relocate the root of Christian understanding in the material reality that is, in the Incarnation and continued in Christ’s real sacramental presence, the very stuff of divine revelation.
Generative modelling for supervised, unsupervised and private learning
Keywords: imputation
knockoffs
generative modelling
GANs
differential privacy
treatment effect estimation

In this thesis we develop several state-of-the-art generative modelling-based approaches for a variety of supervised, unsupervised and private learning problems. In the (almost) supervised domain, we tackle the problems of treatment effect estimation, imputation and feature selection. For treatment effect estimation we begin by developing a GAN-based approach that generates the
missing'' counterfactuals, which enables learning a fully supervised model. In SCIGAN, we then go on to adapt this method to the continuous-intervention setting, introducing novel generator and discriminator architectures to handle the continuous nature of the treatments. For imputation, we introduce GAIN, a GAN-based imputation approach that maximally leverages both the adversarial and generative nature of GANs to learn to impute missing data according to the ground truth distribution while simultaneously allowing for multiple imputation to improve reliability and robustness of the imputed data. Finally, for feature selection, we introduce KnockoffGAN, a GAN-based knockoff generation procedure which again leverages the adversarial nature of GANs to learn the appropriate
knockoff'' distribution. In using a GAN, we are able to learn to generate knockoff non-parametrically and thus reliable performance on non-Gaussian data.
In the domain of private learning we address the problem of private synthetic data generation. This challenge has three key components: (1) generating faithful synthetic data; (2) ensuring privacy; and (3) measuring the quality of the generated data. In PATEGAN, we tackle all 3 of these problems by proposing a GAN-based approach to generating differentially private synthetic data. In addition, we introduce a new synthetic data metric, the Synthetic Ranking Agreement, which measures how well machine learning research on the synthetic data represents the same research on the real data. In the final paper presented, we present a new differential privacy building block - a differentially private classification/prediction algorithm, that builds upon the subsample-and-aggregate paradigm. The new method affords better privacy and utility than subsample-and-aggregate and can be used in place of PATE in the PATEGAN framework.
Learning physical intuition for robotic manipulation
Keywords: artificial curiosity
visuomotor control
structured latent space
physical intuition

When we compare object manipulation capabilities in humans and contemporary robots, we observe an intriguing dichotomy: On one hand, robots have access to advanced compute capacity and precise models of physics, yet their object manipulation skills are comparatively narrow and brittle. On the other hand, the human understanding of physics is allegedly acquired from experience and exhibits many predictive shortcomings, yet their manipulation skills far exceed any contemporary robot’s. Motivated by this observation, this thesis studies the question how much robotic manipulation can benefit from embracing data-driven, approximate models of physics and poses the hypothesis that a tight integration of intuition and control can unlock sophisticated manipulation behaviour.
In particular, three aspects of physical intuition are investigated: (i) high-level intuitions for visual task assessment and their application in object stacking and tool use, (ii) low-level intuitions for rigid-body motions and their application in rearrangement planning and visuomotor control, (iii) the integration of dynamics approximation into control policy learning and its application in structured exploration of an environment.
In the first part, we demonstrate the effectiveness of a visual stability classifier in planning and constructing stable stacks of objects with varying geometries. We also employ a similar task classification technique in a goal-reaching task and show that the associated variational latent space induces an affordance manifold which can be traversed to synthesise suitable tools for a given task. In the second part, we demonstrate that the introduction of dynamics modelling into an object-centric latent space facilitates object disentanglement from raw visual training data and allows to generate physically plausible scenes and videos from scratch. Visual dynamics approximation is also used in our novel, goal-conditioned, visuomotor control architecture where it enables zero-shot transfer to unseen object rearrangement tasks. Finally, we integrate dynamics forecasting and control policy learning in the third part of this thesis and optimise both components using a curiosity objective. This setup leads to the unsupervised emergence of complex, human interpretable manipulation and locomotion behaviour and highlights the crucial importance of physical intuition in the learning process of sophisticated, embodied behaviour.
Ecology and conservation of critically endangered Leopard (Panthera pardus) in Southeast Asia
Keywords: IUCN status
Species distribution
Sampling design
Spatial capture-recapture (SCR)
Indochinese Leopard
Diet
Southeast Asia
Habitat use
Javan Leopard
Bayesian analysis
Density estimation
Threatened species monitoring
Population dynamics
Camera trapping
Occupancy model
Prey selection
Leopard ecology
Low-density populations

Although widely considered the epitome of adaptability, the Leopard (Panthera pardus) has experienced severe declines in distribution and numbers worldwide, yet its conservation status in several regions remains unknown. This is especially true for Southeast Asia where two understudied subspecies of Leopard occur: the Indochinese (P. pardus delacouri) and Javan (P. pardus melas) Leopard. The present study was conducted to gather information on the current status and ecology of these Leopard subspecies in Southeast Asia. Chapter 2 showed that the Indochinese Leopard now likely occurs in about 2-6% of its historical range, which led to its recent uplisting as Critically Endangered by the IUCN. Using data from the largest camera-trap study ever conducted for Leopard in the region, Chapter 3 revealed that densities within key populations in Cambodia, Thailand, Malaysia, and Indonesia were among the lowest ever reported for the species, suggesting the overall prognosis of the Leopard is becoming increasingly bleak in the region. Illegal human activities, which likely were influenced by religious beliefs, socio-economic status, and geographical location, affected the densities, habitat use and activity patterns of Leopard. Using Leopard as case study, Chapter 4 investigated the performance of spatially explicit capture-recapture (SCR) models in low-density populations surveyed with camera traps, and provided recommendations to facilitate the applicability of SCR methods under similar conditions for Leopard and other low-density species. By using DNA confirmed scats, Chapter 5 corroborated the dietary adaptability of Leopard, including the unexpected predation on Banteng (Bos javanicus; 600-800 kg), and showed that predation by this apex carnivore only had a relatively small impact on ungulate populations in eastern Cambodia. Using a novel approach, Chapter 6 investigated the long-term population dynamics of the Indochinese Leopard in a priority site in eastern Cambodia, and found that this unique population is under imminent risk of extirpation, likely due to increases in human-caused mortalities. Chapter 7 looked at the implications of the findings of this thesis and highlighted priorities for Leopard conservation in Southeast Asia. This thesis offers new insights and novel approaches to study Leopard using reliable and repeatable techniques, thus aiding future studies. Overall, this thesis improves the knowledge of the species in the region and provides baseline data for several globally important populations, thereby facilitating monitoring and guiding conservation efforts for Leopard in the extremely biodiversity rich but highly threatened ecosystems of Southeast Asia.