Miracle-dz/UniFAR-FTUs huggingface dataset:
Essays in empirical macroeconomics

This thesis contains three chapters. The first two chapters are essays on monetary economics. The last chapter is an essay on general equilibrium asset pricing. In chapter 1, I study the behavior of disaggregated prices in response to economic shocks. I suggest a production chain model with nominal rigidities to replicate some stylized facts about data. I argue, first, that the input-output linkages in production can create heterogeneity in the response of sectoral prices to aggregate shocks. Second, a realistic calibration of this multi-sector model to the US data can create 5 times more real rigidities in response to nominal shocks, compared to an equivalent homogeneous economy with intermediate inputs. Finally, the model implies that upstream industries would respond faster to aggregate shocks than downstream industries. In chapter 2, I study the effect of imperfect commitment of a central bank on inflationary outcomes. I present a model in which monetary authority is a committee with churning of members who have finite terms. Older and younger generations of Monetary Policy Committee (MPC) members decide on policy by engaging in a bargaining process. I show that this set-up gives rise to a continuous measure of the degree of monetary authority's commitment. The model suggests that lowering the churning rate or increasing the tenure time improves welfare. Chapter 3 (joint work with Aytek Malkhozov) focuses on the asset pricing implications of a real-business-cycle model with recursive preferences and a general shock structure that allows for news shocks. We show that introducing recursive preferences and anticipated shocks into a canonical DSGE model can produce large premia and low risk-free rates without compromising the model's ability to fit the key macroeconomic variables. We illustrate how this class of dynamic stochastic general equilibrium (DSGE) models can be solved using higher order perturbation methods.
Active DNA unwinding dynamics during processive DNA replication

Duplication of double-stranded DNA (dsDNA) requires a fine-tuned coordination between the DNA replication and unwinding reactions. Using optical tweezers, we probed the coupling dynamics between these two activities when they are simultaneously carried out by individual Phi29 DNA polymerase molecules replicating a dsDNA hairpin. We used the wild-type and an unwinding deficient polymerase variant and found that mechanical tension applied on the DNA and the DNA sequence modulate in different ways the replication, unwinding rates, and pause kinetics of each polymerase. However, incorporation of pause kinetics in a model to quantify the unwinding reaction reveals that both polymerases destabilize the fork with the same active mechanism and offers insights into the topological strategies that could be used by the Phi29 DNA polymerase and other DNA replication systems to couple unwinding and replication reactions.
A novel multivalent, single-domain antibody targeting TcdA and TcdB prevents fulminant Clostridium difficile infection in mice.

The incidence of Clostridium difficile infection (CDI) and associated mortality have increased rapidly worldwide in recent years. Therefore, it is critical to develop new therapies for CDI. In this study, we generated a novel, potently neutralizing, tetravalent, and bispecific antibody composed of 2 heavy-chain-only VH (VHH) binding domains against both TcdA and TcdB (designated "ABA") that reverses fulminant CDI in mice infected with an epidemic 027 strain after a single injection of the antibody. We demonstrated that ABA bound to both toxins simultaneously and displayed a significantly enhanced neutralizing activity both in vitro and in vivo. Additionally, ABA was able to broadly neutralize toxins from clinical C. difficile isolates that express both TcdA and TcdB but failed to neutralize the toxin from TcdA(-)TcdB(+) C. difficile strains. This study thus provides a rationale for the development of multivalent VHHs that target both toxins and are broadly neutralizing for treating severe CDI.
AKT Inhibitors Promote Cell Death in Cervical Cancer through Disruption of mTOR Signaling and Glucose Uptake

Background PI3K/AKT pathway alterations are associated with incomplete response to chemoradiation in human cervical cancer. This study was performed to test for mutations in the PI3K pathway and to evaluate the effects of AKT inhibitors on glucose uptake and cell viability. Experimental Design Mutational analysis of DNA from 140 pretreatment tumor biopsies and 8 human cervical cancer cell lines was performed. C33A cells (PIK3CAR88Q and PTENR233*) were treated with increasing concentrations of two allosteric AKT inhibitors (SC-66 and MK-2206) with or without the glucose analogue 2-deoxyglucose (2-DG). Cell viability and activation status of the AKT/mTOR pathway were determined in response to the treatment. Glucose uptake was evaluated by incubation with 18F-fluorodeoxyglucose (FDG). Cell migration was assessed by scratch assay. Results Activating PIK3CA (E545K, E542K) and inactivating PTEN (R233*) mutations were identified in human cervical cancer. SC-66 effectively inhibited AKT, mTOR and mTOR substrates in C33A cells. SC-66 inhibited glucose uptake via reduced delivery of Glut1 and Glut4 to the cell membrane. SC-66 (1 µg/ml-56%) and MK-2206 (30 µM-49%) treatment decreased cell viability through a non-apoptotic mechanism. Decreases in cell viability were enhanced when AKT inhibitors were combined with 2-DG. The scratch assay showed a substantial reduction in cell migration upon SC-66 treatment. Conclusions The mutational spectrum of the PI3K/AKT pathway in cervical cancer is complex. AKT inhibitors effectively block mTORC1/2, decrease glucose uptake, glycolysis, and decrease cell viability in vitro. These results suggest that AKT inhibitors may improve response to chemoradiation in cervical cancer.
Biological Species Are Universal across Life’s Domains

Delineation of species is fundamental to organizing and understanding biological diversity. The most widely applied criterion for distinguishing species is the Biological Species Concept (BSC), which defines species as groups of interbreeding individuals that remain reproductively isolated from other such groups. The BSC has broad appeal; however, many organisms, most notably asexual lineages, cannot be classified according to the BSC. Despite their exclusively asexual mode of reproduction, Bacteria and Archaea can transfer and exchange genes though homologous recombination. Here we show that barriers to homologous gene exchange define biological species in prokaryotes with the same efficacy as in sexual eukaryotes. By analyzing the impact of recombination on the polymorphisms in thousands of genome sequences, we find that over half of named bacterial species undergo continuous recombination among sequenced constituents, indicative of true biological species. However, nearly a quarter of named bacterial species show sharp discontinuities and comprise multiple biological species. These interruptions of gene flow are not a simple function of genome identity, indicating that bacterial speciation does not uniformly proceed by the gradual divergence of genome sequences. The same genomic approach based on recombinant polymorphisms retrieves known species boundaries in sexually reproducing eukaryotes. Thus, a single biological species definition based on gene flow, once thought to be limited only to sexually reproducing organisms, is applicable to all cellular lifeforms.
Automated regulatory information extraction from building codes leveraging syntactic and semantic information

Manual regulatory compliance checking of construction projects is usually timeconsuming and error-prone. There have been efforts both in academia and industry to automate this process. However, none of them achieved full automation. Specifically, the extraction of rules from regulatory text (e.g. building code) and its representation in a computer-processable format is still conducted manually or semi-automatically. Natural language processing (NLP) aims at enabling computers to process natural language text in a human-like manner. It provides basic concepts and methods for text processing and analysis, such as part of speech (POS) tagging, tokenization, sentence splitting, named entity recognition, and semantic role labeling, etc. This paper is intended to explore the effectiveness of utilizing syntactic (i.e. grammatical) and semantic (i.e. meaning descriptive) features of the text (using NLP tools and techniques) to automatically extract regulatory information from building codes. An automated information extraction (IE) approach – involving the use of IE rules – is proposed. Chapter 12 of the 2006 International Building Code was used to develop the IE rules, while Chapter 12 of the 2009 International Fire Code was used to test the approach. An overall F-measure of 0.94 shows the potential of the proposed approach. Based on the experimental results and their analysis, we conclude the paper by pinpointing possible ways for improving the proposed approach.
The Yen, The US dollar and The Speculative Attacks Against The Thailand Baht

Early constructions of a single crisis index known as the exchange market pressure (EMP) index have largely been based on the fluctuations of the real or nominal exchange rate of a currency against the US dollar ---the most commonly accepted anchor currency in the global market. Hardly any studies have however tested the sensitivity of this crisis index to the choice of Â“the anchorÂ” currency. To address this pertinent issue, our study considers the case of Thailand for the period of 1985 to 2003. The test results indicate that the EMP index of the baht / the US dollar rate reported substantially less number of speculative attacks against the baht than that reported by the EMP index of the baht / the Japanese yen rate.
A Fast 2-D AR Parameter Estimation Algorithm Based on Functional Schur Coefficients

This paper presents an algorithm for the estimation of the 2-D AR parameters. This new method is based on the functional Schur coefficients recently introduced by the authors. The algorithm is efficient in terms of computation and preserves in the 2-D case the advantages of the 1-D Schur algorithm vs 1-D Levinson algorithm. This approach is illustrated on several numerical examples.
FDA’s Nozzle Numerical Simulation Challenge: Non-Newtonian Fluid Effects and Blood Damage

Data from FDA’s nozzle challenge–a study to assess the suitability of simulating fluid flow in an idealized medical device–is used to validate the simulations obtained from a numerical, finite-differences code. Various physiological indicators are computed and compared with experimental data from three different laboratories, getting a very good agreement. Special care is taken with the derivation of blood damage (hemolysis). The paper is focused on the laminar regime, in order to investigate non-Newtonian effects (non-constant fluid viscosity). The code can deal with these effects with just a small extra computational cost, improving Newtonian estimations up to a ten percent. The relevance of non-Newtonian effects for hemolysis parameters is discussed.
3,5,3′-Triiodo-L-Thyronine- and 3,5-Diiodo-L-Thyronine- Affected Metabolic Pathways in Liver of LDL Receptor Deficient Mice

3,5,3′-triiodo-L-thyronine (T3) and 3,5-diiodo-L-thyronine (T2), when administered to a model of familial hypercholesterolemia, i.e., low density lipoprotein receptor (LDLr)-knockout (Ldlr−/−) mice fed with a Western type diet (WTD), dramatically reduce circulating total and very low-density lipoprotein/LDL cholesterol with decreased liver apolipoprotein B (ApoB) production. The aim of the study was to highlight putative molecular mechanisms to manage cholesterol levels in the absence of LDLr. A comprehensive comparative profiling of changes in expression of soluble proteins in livers from Ldlr−/− mice treated with either T3 or T2 was performed. From a total proteome of 450 liver proteins, 25 identified proteins were affected by both T2 and T3, 18 only by T3 and 9 only by T2. Using in silico analyses, an overlap was observed with 11/14 pathways common to both iodothyronines, with T2 and T3 preferentially altering sub-networks centered around hepatocyte nuclear factor 4 α (HNF4α) and peroxisome proliferator-activated receptor α (PPARα), respectively. Both T2 and T3 administration significantly reduced nuclear HNF4α protein content, while T2, but not T3, decreased the expression levels of the HNFα transcriptional coactivator PGC-1α. Lower PPARα levels were found only following T3 treatment while both T3 and T2 lowered liver X receptor α (LXRα) nuclear content. Overall, this study, although it was not meant to investigate the use of T2 and T3 as a therapeutic agent, provides novel insights into the regulation of hepatic metabolic pathways involved in T3- and T2-driven cholesterol reduction in Ldlr−/− mice.
A Note on the Estimation of Linear Regression Models with Heteroskedastic Measurement Errors

I consider the estimation of linear regression models when the independent variables are measured with errors whose variances differ across observations, a situation that arises, for example, when the explanatory variables in a regression model are estimates of population parameters based on samples of varying sizes. Replacing the error variance that is assumed common to all observations in the standard errors-in-variables estimator by the mean measurement error variance yields a consistent estimator in the case of measurement error heteroskedasticity. However, another estimator, which I call the Heteroskedastic Errors in Variables Estimator (HEIV), is, under standard assumptions, asymptotically more efficient. Simulations show that the efficiency gains are likely to appreciable in practice. In addition, the HEIV estimator, which is equal to the ordinary least squares regression of the dependent variable on the best linear predictor of the true independent variables, is simple to compute with standard regression software.
Efficacy of intermittent preventive treatment versus chloroquine prophylaxis to prevent malaria during pregnancy in Benin.

BACKGROUND In West Africa, treatment for the prevention of malaria during pregnancy has recently changed from chloroquine (CQ) prophylaxis to intermittent preventive treatment (IPTp). We assessed the benefits of IPTp with respect to those of CQ, using a before-after study. METHODS CQ efficacy was evaluated during a cross-sectional survey conducted in Benin between April 2004 and April 2005. IPTp efficacy was assessed using data from an ongoing clinical trial to compare sulfadoxine-pyrimethamine with mefloquine that began in the same maternity clinics during July 2005; the present analysis is limited to women who delivered between November 2005 and November 2006. Treatment assignments were not unblinded. We compared the efficacy of the 2 strategies against low birth weight and placental infection by performing multiple logistic regressions. RESULTS A total of 1699 women (1090 in the CQ group and 609 in the IPTp group) who delivered live singletons were analyzed. Characteristics of women in the CQ group were similar to those of women in the IPTp group. We showed that women in the IPTp group had a significantly decreased risk of delivering an infant with a low birth weight (adjusted odds ratio [aOR], 0.54; 95% confidence interval [CI], 0.38-0.78) and placental infection (aOR, 0.15; 95% CI, 0.09-0.24). CONCLUSION We clearly evidenced that IPTp is substantially more beneficial than CQ for the prevention of malaria during pregnancy.
Non-deterministic computation and the Jayne-Rogers Theorem

We provide a simple proof of a computable analogue to the Jayne Rogers Theorem from descriptive set theory. The difficulty of the proof is delegated to a simulation result pertaining to non-deterministic type-2 machines. Thus, we demonstrate that developments in computational models can have applications in fields thought to be far removed from it.
Costs and Benefits of an Anti-Inflationary Policy: Questions and Issues

This paper analyses how the output or unemployment cost of achieving a sustainable reduction in the rate of inflation depends on the structure of the wage-price process and how the "sacrifice ratio" can be minimized. In models where the natural rate is invariant under the anti-inflationary policies, price level inertia is not sufficient for a positive sacrifice ratio. Without sluggishness in the core inflation rate, a zero sacrifice ratio can be achieved simply through intelligent demand management. With sluggish core inflation, the sacrifice ratio is positive unless intelligent demand management is complemented by cost-reducing fiscal measures o reffective incomes policy. Letting the exchange rate float does not reduce the sacrifice ratio. If core inflation is partly backward-looking and partly forward-looking, current core inflation may be a function of current and past expectations of future recessions. Conventional sacrifice ratio calculations ignore forward-looking aspects of behaviour and may therefore underestimate the true cost of disinflation. If there is hysteresis in the natural rate (e.g. through a gradual adjustment of the natural rate towards the actual rate) and if there is sluggish core inflation, the sacrifice ratio will become infinite.Whenever sluggish core inflation is present, credibility of the anti-inflationary (monetary) policy alone cannot obviate a positive sacrifice ratio.
Protective action of dopamine against glutamate neurotoxicity in the retina.

PURPOSE The electrophysiologic study using patch-clamp techniques demonstrated that NMDA-induced currents had properties similar to those recorded in the brain. METHODS Primary cultures obtained from the fetal rat retina (gestation days 16 to 19) were used for the experiment. Immunocytochemical and electrophysiologic studies were done to identify the cultured cells. The neurotoxic effects of glutamate or N-methyl-D-aspartate (NMDA) on the retinal cultures were quantitatively assessed using the trypan blue exclusion method. RESULTS The immunocytochemical study revealed that the major component of the rat retinal cultures was neurons including amacrine cells. The electrophysiologic study using patch-clamp techniques demonstrated that exposure to NMDA-induced currents with properties characteristic of those recorded in the brain. Brief exposure of these neurons to glutamate or NMDA induced delayed cell death. Glutamate neurotoxicity was prevented by the application of dopamine and forskolin. The protective action of dopamine was antagonized by a D1 receptor antagonist (SCH 23390) but not by D2 receptor antagonists (domperidone and sulpiride). A D1 receptor agonist (SKF 38393) protected glutamate-induced neurotoxicity in a concentration-dependent manner, whereas a D2 receptor agonist (quinpirole) did not affect it. CONCLUSIONS These findings demonstrate that dopamine protects retinal neuronal cells against NMDA receptor-mediated glutamate neurotoxicity via D1 receptors.
Time-Varying Versus Fixed Weights in Exchange-Market Pressure Indices: Evidence From Tests Using Latin American Data

Years after the 2008 Global Financial Crisis, currencies worldwide are still susceptible to spillovers not only from foreign currency markets, but also from shocks to stock or commodity prices. Understanding these spillovers is essential for policymakers to respond properly, yet defining ? crisis? periods can often be difficult. This paper proposes two alternative weighting schemes that can be used in the creation of an index of ? exchange market pressure? (EMP), constructing them, as well as a more traditional index, for five Latin American nations and three other emerging markets. Vector Autoregressive (VAR) analysis shows that the two new indices are less likely to find evidence of currency spillovers. We therefore conclude that these differences among measures make the new indices less likely to replace the baseline measure in econometric studies.
A Comparative Analysis of Productivity Growth, Catch-Up, and Convergence in Transition Economies

The paper examines the macroeconomic performance of 25 transition economies using a comparable data set. In order to see whether transition to a market-based economy increased economic efficiency, technical progress, and total factor productivity (TFP), we estimate efficiency measures for Eastern European and Baltic countries and the republics of the former Soviet Union using stochastic frontier analysis (SFA) and data envelopment analysis as a confirmatory analysis. According to the SFA estimates, the average annual efficiency level for the 25 transition economies is 0.548, and the average annual rate of growth in technical efficiency is 1.8 percent for the 1991-2000 period. The average annual technical change in transition economies is -4.3 percent for the period examined. That is, there is no technological progress, but over the period there has been a technological regress. The sum of the rate of change in technical efficiency and technical change implies a 2.5 percent decline in the average annual TFP. These results suggest that, on average, change in technical efficiency is outweighed by the technical regress.
Dynamic Perfect Hashing: Upper and Lower Bounds

The dynamic dictionary problem is considered: provide an algorithm for storing a dynamic set, allowing the operations insert, delete, and lookup. A dynamic perfect hashing strategy is given: a randomized algorithm for the dynamic dictionary problem that takes $O(1)$ worst-case time for lookups and $O(1)$ amortized expected time for insertions and deletions; it uses space proportional to the size of the set stored. Furthermore, lower bounds for the time complexity of a class of deterministic algorithms for the dictionary problem are proved. This class encompasses realistic hashing-based schemes that use linear space. Such algorithms have amortized worst-case time complexity $\Omega(\log n)$ for a sequence of $n$ insertions and lookups; if the worst-case lookup time is restricted to $k$, then the lower bound becomes $\Omega(k\cdot n^{1/k})$.
Title : 3 D Euclidean Reconstruction from Multiple Uncalibrated Views using Particle Swarm Optimization Candidate :

Given a set of images of a set of 3D points, with known correspondence among them, we would like to reconstruct the coordinates of the 3D points and discover the projection matrices associated with the cameras used to capture these images. Once this information is obtained, we would be able to compute any novel view of these 3D points from a virtual camera placed at any position and orientation. We solve this problem as an optimization problem using the Particle Swarm Optimization (PSO) algorithm.
Classical and modular approaches to exponential Diophantine equations II. The Lebesgue–Nagell equation

This is the second in a series of papers where we combine the classical approach to exponential Diophantine equations (linear forms in logarithms, Thue equations, etc.) with a modular approach based on some of the ideas of the proof of Fermat's Last Theorem. In this paper we use a general and powerful new lower bound for linear forms in three logarithms, together with a combination of classical, elementary and substantially improved modular methods to solve completely the Lebesgue–Nagell equation x2 + D = yn, x, y integers, $n\geq 3$, for D in the range $1 \leq D \leq 100$.