Miracle-dz/UniFAR-FTUs huggingface dataset:
Strain-Dependent Differences in Sensitivity to Myopia-Inducing Stimuli in Guinea Pigs and Role of Choroid

Purpose To investigate differences in sensitivity to myopia-inducing stimuli of two strains of pigmented guinea pigs. Methods Eleven-day-old animals (New Zealand [NZ], n = 24 and Elm Hill strains [EH], n = 26) wore either a +2 or −2 diopter (D) lens over one eye and a plano lens over the fellow eye for 5 days; other 10-day-old EH (n = 9) and 7-day-old NZ (n = 9) animals were monocularly form-deprived (FD) for 28 days. Choroidal thickness and axial length were measured using A-scan ultrasonography at baseline and after 1 and 5 days for optical defocus treatments, and at baseline and after 28 days for the FD treatment. Refractive errors were measured by retinoscopy. Choroids of untreated animals were also evaluated using spectral-domain optical coherence tomography. Results One day of optical defocus induced bidirectional (optical sign-dependent) choroidal responses in EH animals only (P < 0.01). Similar responses were detected in NZ animals after 5 days (P < 0.01), with concordant spherical equivalent refraction changes (P < 0.01). Compared with NZ animals, EH animals developed minimal myopia with FD after 28 days (−4.58 ± 0.97 vs. −0.69 ± 0.75 D for NZ versus EH, P < 0.001). Yet, EH animals showed paradoxical choroidal thickening, 20 ± 9 vs. −8 ± 8 μm for EH versus NZ, P < 0.001. Untreated EH animals also had significantly thicker choroids than NZ animals (147 ± 19 vs. 132 ± 16 μm, P < 0.05), with well-defined layering. Conclusions As previously reported in chicks, guinea pigs show strain-related differences in response to myopia-inducing stimuli. The finding of a thicker, multilayered choroid in the strain showing decreased sensitivity to FD is provocative, suggesting a possible protective role of the choroid.
4-Methylumbelliferyl glucuronide contributes to hyaluronan synthesis inhibition

4-Methylumbelliferone (4-MU) inhibits hyaluronan (HA) synthesis and is an approved drug used for managing biliary spasm. However, rapid and efficient glucuronidation is thought to limit its utility for systemically inhibiting HA synthesis. In particular, 4-MU in mice has a short half-life, causing most of the drug to be present as the metabolite 4-methylumbelliferyl glucuronide (4-MUG), which makes it remarkable that 4-MU is effective at all. We report here that 4-MUG contributes to HA synthesis inhibition. We observed that oral administration of 4-MUG to mice inhibits HA synthesis, promotes FoxP3+ regulatory T-cell expansion, and prevents autoimmune diabetes. Mice fed either 4-MUG or 4-MU had equivalent 4-MU:4-MUG ratios in serum, liver, and pancreas, indicating that 4-MU and 4-MUG reach an equilibrium in these tissues. LC–tandem MS experiments revealed that 4-MUG is hydrolyzed to 4-MU in serum, thereby greatly increasing the effective bioavailability of 4-MU. Moreover, using intravital 2-photon microscopy, we found that 4-MUG (a nonfluorescent molecule) undergoes conversion into 4-MU (a fluorescent molecule) and that 4-MU is extensively tissue bound in the liver, fat, muscle, and pancreas of treated mice. 4-MUG also suppressed HA synthesis independently of its conversion into 4-MU and without depletion of the HA precursor UDP-glucuronic acid (GlcUA). Together, these results indicate that 4-MUG both directly and indirectly inhibits HA synthesis and that the effective bioavailability of 4-MU is higher than previously thought. These findings greatly alter the experimental and therapeutic possibilities for HA synthesis inhibition.
The evolution of life-history theory: a bibliometric analysis of an interdisciplinary research area

Life history theory developed as a branch of formal evolutionary theory concerned with the fitness consequences of allocating energy to reproduction, growth and self-maintenance across the life course. More recently, researchers have advocated its relevance to many psychological and social-science questions. As a scientific paradigm expands its range, its parts can become conceptually isolated from one another, so that in the end it is no longer held together by a common core of shared ideas. Here, we investigate the life history theory literature using quantitative bibliometric methods based on patterns of citation. We found that the literature up to and including 2010 was relatively coherent: it drew on a shared body of core references, and had only weak cluster divisions running along taxonomic lines. The post-2010 literature is more fragmented: it has more marked cluster boundaries, including boundaries within the literature on humans. Specifically, there are two clusters of human literature based around the idea of a fast-slow continuum of individual differences in behaviour that are bibliometrically isolated from the rest of the literature. We also find some evidence suggesting a relative decline in formal mathematical modelling. We point out that the human fast-slow continuum literature is conceptually closer to the non-human ‘pace of life’ literature than to the non-human literature usually referred to as ‘life history theory’.
Identification of Conduit Countries and Community Structures in the Withholding Tax Networks

Due to economic globalization, each country's economic law, including tax laws and tax treaties, has been forced to work as a single network. However, each jurisdiction (country or region) has not made its economic law under the assumption that its law functions as an element of one network, so it has brought unexpected results. We thought that the results are exactly international tax avoidance. To contribute to the solution of international tax avoidance, we tried to investigate which part of the network is vulnerable. Specifically, focusing on treaty shopping, which is one of international tax avoidance methods, we attempt to identified which jurisdiction are likely to be used for treaty shopping from tax liabilities and the relationship between jurisdictions which are likely to be used for treaty shopping and others. For that purpose, based on withholding tax rates imposed on dividends, interest, and royalties by jurisdictions, we produced weighted multiple directed graphs, computed the centralities and detected the communities. As a result, we clarified the jurisdictions that are likely to be used for treaty shopping and pointed out that there are community structures. The results of this study suggested that fewer jurisdictions need to introduce more regulations for prevention of treaty abuse worldwide.
Optimal sequential treatment allocation

In treatment allocation problems the individuals to be treated often arrive sequentially. We study a problem in which the policy maker is not only interested in the expected cumulative welfare but is also concerned about the uncertainty/risk of the treatment outcomes. At the outset, the total number of treatment assignments to be made may even be unknown. A sequential treatment policy which attains the minimax optimal regret is proposed. We also demonstrate that the expected number of suboptimal treatments only grows slowly in the number of treatments. Finally, we study a setting where outcomes are only observed with delay.
On the choice of instruments in mixed frequency specification tests

Abstract Time averaging has been the traditional approach to handle mixed sampling frequencies. However, it ignores information possibly embedded in high frequency. Mixed data sampling (MIDAS) regression models provide a concise way to utilize the additional information in high-frequency variables. In this paper, we propose a specification test to choose between time averaging and MIDAS models, based on a Durbin-Wu-Hausman test. In particular, a set of instrumental variables is proposed and theoretically validated when the frequency ratio is large. As a result, our method tends to be more powerful than existing methods, as reconfirmed through the simulations.
SERMAYE-YOĞUN MAL İHRACATINDA REKABET GÜCÜNÜN BELİRLEYİCİLERİ: TÜRKİYE İÇİN YAPISAL KIRILMALI BİR ANALİZ

Balassa (1965) tarafindan ortaya konulan Aciklanmis Karsilastirmali Ustunlukler (RCA), uluslararasi ticaret rekabet gucu analizlerinde yaygin olarak kullanilmaktadir. RCA, bir ulke veya bolgenin bir sektor icin ya da ekonominin geneli icin uluslararasi rekabet gucune sahip olup olmamasini arastirmaktadir. Ancak literature bakildiginda RCA ile elde edilen rekabet gucunu belirleyen faktorler pek incelenmemistir. Bu calismanin amaci ise, aciklanmis karsilastirmali ustunlukler (RCA) ile elde edilen Turkiye’nin sermaye yogun mallardaki rekabet gucunu etkileyen faktorleri zaman serileri analizi ile arastirmaktir. 1989-2017 donemini kapsayan calismada Zivot ve Andrews (1992) yapisal kirilmali birim kok testi, Gregory ve Hansen (1996) yapisal kirilmali esbutunlesme testi ve FMOLS katsayi tahmin yontemi kullanilmistir. Yapilan analizler sonucunda modele dâhil edilen makroekonomik gostergelerle sermaye yogun mallarin rekabet gucu arasinda uzun donemli iliski oldugu gorulmustur. Katsayi tahmin sonuclarina gore GSYIH, doviz kuru ve dogrudan yabanci sermaye yatirimlarinin sermaye yogun mallarin uluslararasi rekabet gucunu pozitif etkiledigi fakat patentlerin negatif etkiledigi sonucu elde edilmistir.
Every city needs a Klinika: The struggle for autonomy in the post-political city

ABSTRACT The article uses the struggle for an autonomous social centre in Prague to examine the concept of post-politicization in the post-socialist city. Using the case of the squatted social centre Klinika, it discusses different kinds of prefiguration and argues that the struggle for this space has the ability to re-politicize the post-political city. The case of Klinika demonstrates that post-politics is not a one-way process – but re-politicization is not either. These processes may therefore be understood as something akin to a ping-pong interaction between the post-political forces of order and the re-politicizing action of radical opponents of the status quo.
Colorectal cancer diagnosis from histology images: A comparative study

Computer-aided diagnosis (CAD) based on histopathological imaging has progressed rapidly in recent years with the rise of machine learning based methodologies. Traditional approaches consist of training a classification model using features extracted from the images, based on textures or morphological properties. Recently, deep-learning based methods have been applied directly to the raw (unprocessed) data. However, their usability is impacted by the paucity of annotated data in the biomedical sector. In order to leverage the learning capabilities of deep Convolutional Neural Nets (CNNs) within the confines of limited labelled data, in this study we shall investigate the transfer learning approaches that aim to apply the knowledge gained from solving a source (e.g., non-medical) problem, to learn better predictive models for the target (e.g., biomedical) task. As an alternative, we shall further propose a new adaptive and compact CNN based architecture that can be trained from scratch even on scarce and low-resolution data. Moreover, we conduct quantitative comparative evaluations among the traditional methods, transfer learning-based methods and the proposed adaptive approach for the particular task of cancer detection and identification from scarce and low-resolution histology images. Over the largest benchmark dataset formed for this purpose, the proposed adaptive approach achieved a higher cancer detection accuracy with a significant gap, whereas the deep CNNs with transfer learning achieved a superior cancer identification.
Probability Density Functionals in Perturbation Theory within the QFT in-in Formalism

We delve into the in-in formalism and derive general expressions for the computation of n-point functions for a self-interacting scalar field by means of a probability density functional (PDF). Even though in typical situations these formulae are not simpler than the standard approaches to Quantum Field Theory (QFT), we find that in specific situations, such as a first-order computation with a non-trivial potential, they can significantly reduce the effort needed to evaluate quantities of interest. The presented formulae may be readily generalized to other types of fields (e.g., fermionic Dirac fields), and to interacting theories that contain various types of fields. An analogous result for the in-out formalism is presented using the previously employed strategies. Finally, we apply the obtained results to first-order computations and work out specific examples where we explore their limitations and possible prospects for future computations.
On the Non-Asymptotic Properties of Regularized M-Estimators

We propose a general framework for regularization in M-estimation problems under time dependent (absolutely regular-mixing) data which encompasses many of the existing estimators. We derive non-asymptotic concentration bounds for the regularized M-estimator. Our results exhibit a variance-bias trade-off, with the variance term being governed by a novel measure of the complexity of the parameter set. We also show that the mixing structure affect the variance term by scaling the number of observations; depending on the decay rate of the mixing coefficients, this scaling can even affect the asymptotic behavior. Finally, we propose a data-driven method for choosing the tuning parameters of the regularized estimator which yield the same (up to constants) concentration bound as one that optimally balances the (squared) bias and variance terms. We illustrate the results with several canonical examples.
Cancer‐ and Chemotherapy‐Induced Musculoskeletal Degradation

Mobility in advanced cancer patients is a major health care concern and is often lost in advanced metastatic cancers. Erosion of mobility is a major component in determining quality of life but also starts a process of loss of muscle and bone mass that further devastates patients. In addition, treatment options become limited in these advanced cancer patients. Loss of bone and muscle occurs concomitantly. Advanced cancers that are metastatic to bone often lead to bone loss (osteolytic lesions) but may also lead to abnormal deposition of new bone (osteoblastic lesions). However, in both cases there is a disruption to normal bone remodeling and radiologic evidence of bone loss. Many antitumor therapies can also lead to loss of bone in cancer survivors. Bone loss releases cytokines (TGFβ) stored in the mineralized matrix that can act on skeletal muscle and lead to weakness. Likewise, loss of skeletal muscle mass leads to reduced bone mass and quality via mechanical and endocrine signals. Collectively these interactions are termed bone‐muscle cross‐talk, which has garnered much attention recently as a prime target for musculoskeletal health. Pharmacological approaches as well as nutrition and exercise can improve muscle and bone but have fallen short in the context of advanced cancers and cachexia. This review highlights our current knowledge of these interventions and discusses the difficulties in treating severe musculoskeletal deficits with the emphasis on improving not only bone mass and muscle size but also functional outcomes. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
Quenched SU(2) adjoint scalar propagator in minimal Landau gauge

It is a long-standing question whether the confinement of matter fields in QCD has an imprint in the (gauge-dependent) correlation functions, especially the propagators. In particular in the quenched case a fundamental difference could be expected between adjoint and fundamental matter. In a preceding investigation the propagator of a fundamental scalar has been studied, showing no obvious sign of confinement. Here, complementary, the adjoint scalar propagator is investigated over a wide range of parameters in the minimal Landau gauge using lattice gauge theory. This study is performed in two, three, and four dimensions in quenched SU(2) Yang-Mills theory, both in momentum space and position space. No conclusive difference between both cases is found.
Dual regression

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution functions which, in its simplest form, is the dual program of a simultaneous estimator for linear location-scale models. We apply our general characterization to the specification and estimation of a flexible class of conditional distribution functions, and present asymptotic theory for the corresponding empirical dual regression process.
Some Large Sample Results for the Method of Regularized Estimators

We present a general framework for studying regularized estimators; i.e., estimation problems wherein "plug-in" type estimators are either ill-defined or ill-behaved. We derive primitive conditions that imply consistency and asymptotic linear representation for regularized estimators, allowing for slower than $\sqrt{n}$ estimators as well as infinite dimensional parameters. We also provide data-driven methods for choosing tuning parameters that, under some conditions, achieve the aforementioned results. We illustrate the scope of our approach by studying a wide range of applications, revisiting known results and deriving new ones.
An Intuitive Derivation of the Coherence Index Relation in Compressive Sensing

The existence and uniqueness conditions are a prerequisite for reliable reconstruction of sparse signals from reduced sets of measurements within the Compressive Sensing (CS) paradigm. However, despite their underpinning role for practical applications, existing uniqueness relations are either computationally prohibitive to implement (Restricted Isometry Property), or involve mathematical tools that are beyond the standard background of engineering graduates (Coherence Index). This can introduce conceptual and computational obstacles in the development of engineering intuition, the design of suboptimal practical solutions, or understanding of limitations. To this end, we introduce a simple but rigorous derivation of the coherence index condition, based on standard linear algebra, with the aim to empower signal processing practitioners with intuition in the design and ease in implementation of CS systems. Given that the coherence index is one of very few CS metrics that admits mathematically tractable and computationally feasible calculation, it is our hope that this work will help bridge the gap between the theory and applications of compressive sensing.
Pix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer

The long-coveted task of reconstructing 3D geometry from images is still a standing problem. In this paper, we build on the power of neural networks and introduce Pix2Vex, a network trained to convert camera-captured images into 3D geometry. We present a novel differentiable renderer ($DR$) as a forward validation means during training. Our key insight is that $DR$s produce images of a particular appearance, different from typical input images. Hence, we propose adding an image-to-image translation component, converting between these rendering styles. This translation closes the training loop, while allowing to use minimal supervision only, without needing any 3D model as ground truth. Unlike state-of-the-art methods, our $DR$ is $C^\infty$ smooth and thus does not display any discontinuities at occlusions or dis-occlusions. Through our novel training scheme, our network can train on different types of images, where previous work can typically only train on images of a similar appearance to those rendered by a $DR$.
Synthetic non-classical luminescence generation by enhanced silica nanophotonics based on nano-bio-FRET

Fluorescent silica nanoparticles (NPs–(SiO2–Fluo)) were synthesized based on the classical Störber method for cyanobacteria labelling. Modified mono-coloured SiO2 NPs with fluorescein (Fl) and rhodamine B (RhB) were obtained (NPs–(SiO2–Fl) and NPs–(SiO2–RhB)). Moreover, multi-coloured SiO2 NPs, via the incorporation of both emitters (NPs–(SiO2–RhB–Fl)), were tuned for optimal emissions and the biodetection of cyanobacteria. NPs–(SiO2–Fl) and NPs–(SiO2–RhB–Fl) were optimized for detection via laser fluorescence microscopy and in-flow cytometry with laser excitation and fluorescence detection. By TEM, homogeneous SiO2 NPs of 180.0 nm in diameter were recorded. These sizes were slightly increased due to the covalent linking incorporation of fluorescent dye emitters to 210.0 nm with mono-coloured fluorescent modified amine-organosilanes, and to 340.0 nm in diameter with multi-coloured dye incorporation. NPs–(SiO2–Fluo) showed variable emission depending on the dye emitter concentration, quantum yield and applied luminescent pathway. Thus, mono-coloured NPs–(SiO2–Fl) and NPs–(SiO2–RhB) showed diminished emissions in comparison to multi-coloured NPs–(SiO2–RhB–Fl). This enhancement was explained by fluorescence resonance energy transfer (FRET) between Fl as a fluorescent energy donor and RhB as an energy acceptor produced within the nanoarchitecture, produced only in the presence of both fluorophores with the appropriate laser excitation of the energy donor. The depositions of the nano-emitters on cyanobacteria by non-covalent interactions were observed by TEM and laser fluorescence microscopy. For multi-coloured NPs–(SiO2–RhB–Fl) labelling, bio-FRET was observed between the emission of the nano-labellers and the natural fluorophores from the cyanobacteria that quenched the emission of the whole nano-biostructure in comparison to mono-coloured NPs–(SiO2–Fl) labelling. This fact was explained and discussed in terms of different fluorescence energy transfer from the nanolabellers towards different natural chromophore coupling. In the presence of NPs–(SiO2–RhB–Fl) and NPs–(SiO2–RhB), the emission was coupled with lower quantum yield chromophores; while upon the application of NPs–(SiO2–Fl), it was coupled with higher quantum yield chromophores. In this manner, for enhanced luminescent nanoplatform tracking, the multi-coloured NPs–(SiO2–RhB–Fl) showed improved properties; but more highly luminescent bio-surfaces were generated with mono-coloured NPs–(SiO2–Fl) that permitted faster cyanobacteria detection and counting by laser fluorescence microscopy, and by in-flow cytometry with laser excitation and fluorescence detection.
Resource Abundance and Life Expectancy

This paper investigates the impacts of major natural resource discoveries since 1960 on life expectancy in the nations that they were resource poor prior to the discoveries. Previous literature explains the relation between nations wealth and life expectancy, but it has been silent about the impacts of resource discoveries on life expectancy. We attempt to fill this gap in this study. An important advantage of this study is that as the previous researchers argued resource discovery could be an exogenous variable. We use longitudinal data from 1960 to 2014 and we apply three modern empirical methods including Difference-in-Differences, Event studies, and Synthetic Control approach, to investigate the main question of the research which is 'how resource discoveries affect life expectancy? '. The findings show that resource discoveries in Ecuador, Yemen, Oman, and Equatorial Guinea have positive and significant impacts on life expectancy, but the effects for the European countries are mostly negative.