Miracle-dz/UniFAR-FTUs huggingface dataset:
A Work Project, presented as part of the requirements for the Award of a Master ́s Degree in Economics from the NOVA – School of Business and Economics PRACTICE VARIATIONS IN THE PRODUCTION OF HEALTH

This study investigates three questions related to medical practice variation. First, it tests whether average length of stay across Portuguese National Health Service hospitals varies when controlling for differences in patients’ characteristics. Second, it looks at hospital-level characteristics in order to find out whether these are able to explain differences in average length of stay across hospitals. Finally, it proposes a best practice average length of stay for each of the six episodes of care analyzed. To perform the analysis, administrative data from the Diagnosis-Related groups’ data set for the year of 2012 was used. A replication of a hierarchical two-stage model with hospital fixed effects was carried out. The results show that after taking patients’ characteristics into account, variation in average length of stay across hospitals exists. This variation cannot be explained by hospital-level characteristics.
Epidemiology and molecular diagnosis of acute conjunctivitis in patients attending Hamadan, west Iran ophthalmology clinics 2016–2017

Background Viruses are considered the most common cause of infectious conjunctivitis. PCR has been approved as the best standard method to diagnose viral conjunctivitis. This study was conducted to investigate epidemiological patterns of conjunctivitis in Hamadan, west Iran. In addition, the frequency of the most important cause of infectious conjunctivitis diagnosed by PCR and its seasonal variations and association with certain socioeconomic and health factors were studied. Methods In this cross-sectional study, 125 patients with suspected viral conjunctivitis or keratoconjunctivitis in Hamadan, west Iran from July 2016 to June 2017 were examined for the presence of herpes simplex virus 1 (HSV1), HSV2, varicella-zoster virus (VZV), adenovirus. and Chlamydia trachomatis using multiplex real-time PCR. Results Adenoviruses were the most prevalent pathogens (94.4%). HSV1 was found in two (1.6%) patients. HSV2, VZV, and C. trachomatis were not seen in any patients. There was no difference in acquisition of conjunctivitis between men and women. A total of 55 (44%) patients attended the clinics in summer. Conclusion This study demonstrated that adenoviruses were a much more common viral cause of conjunctivitis in the studied region compared to findings in other regions. In addition, the acquisition rate of eye infection is expected to decrease dramatically in this region through control of adenoviruses. Demographic variables ie, age, sex, and income level, were not significantly associated with acquisition of viral infection.
PSEUDO-POLAR FOURIER TRANSFORM

Image registration is a systematic process to put the separated image in a frame, so the information of the image can be integrated or compared optimally. The estimation of rotation and translation to register image is done by using Pseduo-polar Fourier Transform (PPFT). The accuracy will be reached optimally if iteration on estimation by the limitation in the level of mistake according to treshold which is determined. The iteration process creates the complexity of registration less efficient. This research purposes to optimize the image registration by giving suggestion estimation of non interactive of image rotation by using PPFT. The optimum which is done by deleting a number of estimation of iterative image rotation with the PPFT becomes once of estimation process. The deletion of iteration value which is done by uniting the surround of estimation of rotation side as a new candidate. Furthermore, I1 is rotated with estimation of estimation side. The most accurate side is the side resulting in the calculation of the highest phase correlation value between I2 and rotation image I1, candidate estimation side. The try out shows that the iteration value which is deleted on registration of iterative image using PPTF is 3–11. The method pruposed has estimation on image of noise of gaussian noise having mean u=0 till variant 0 for 0,13.
A Hybrid Surf-Based Tracking Algorithm with Online Template Generation

Visual tracking is the most challenging fields in the computer vision scope. Occlusion full or partial remains to be a big mile stone to achieve . This paper deals with occlusion along with illumination change, pose variation, scaling, and unexpected camera motion. This algorithm is interest point based using SURF as detector descriptor algorithm. SURF based Mean-Shift algorithm is combined with Lukas-Kanade tracker. This solves the problem of generation of online templates. These two trackers over the time rectify each other, avoiding any tracking failure. Also, Unscented Kalman Filter is used to predict the location of target if target comes under the influence of any of the above mentioned challenges. This combination makes the algorithm robust and useful when required for long tenure of tracking. This is proven by the results obtained through experiments conducted on various data sets.
important phases of web usage mining are the reconstruction of user sessions by using heuristics techniques and discovering useful patterns from these sessions by using pattern discovery techniques like association rule mining , Apriori , etc [ 34 ]

Now a day the World Wide Web becomes very popular and interactive for transferring of information. It is massive repository of web pages & links. It provides information about vast area for the internet user. The web is huge, diverse and active and thus increasing the scalability, multimedia data & temporal matters. The growth of the web has outcome in a huge amount of information that is now freely offered for user access. Since due to tremendous usage, the log files are growing at a faster rate and the size is becoming huge. Web page access and usage information, providing rich source for data mining. Natural Language Processing plays a vital role in efficient mining process as log data is normally noisy and indistinct. Data Mining is a process of analyzing large amounts of data and picking out the relevant information. It refers to extracting or mining knowledge from large amounts of data. Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data CURE (Clustering usage Representatives) method find clusters from a large database that is more robust to outliers, and identifies clusters having non-spherical shapes and wide variances in size.
A News Framing of Campaign Declaration President and Vice President Jokowi - Makruf and Prabowo-Sandy Presidential Election 2019 at kompas.com and republika.com

The purpose of this research is to see the tendency of reporting in the mass media, about the presidential and vice presidential candidates for the 2019-2024 Period, Joko Widodo-Ma'ruf Amin and Prabowo Subianto -Sandiaga Uno. The researcher chosed digital mass media, kompas.com and republica.com as the subject of this study. The reason for choosing republika.com digital mass media is media ownership. The President Commissioner of PT Mahaka Media Tbk, the legal entity that houses republica.com, is Erick Thohir who is the Chairperson of Jokowi-Ma'ruf Amin TKN ( National Winning Team). That condition is published an assumption that Erick Tohir accessed to influence editorial policies, related to the reporting of the 2019 presidential election. For the kompas.com digital media, it was chosen because that corporate has always been considered professional and independent. Kompas' daily ( the up line of kompas.com ) track record gives a strong indication of how the national media truly presents an impartial press in its reporting. This study uses framing analysis of Zhongdang Pan and Gerald M. Kosicki models. The results showed that both online media republica.com and kompas.com quantitatively contained more news for candidate number 01 (Joko Widodo-Ma’ruf Amin), than candidate number 02 (Prabowo-Sandiaga). Whereas qualitatively, both online media still contained neutral or impartial content and did not tend to one of candidates pair.
$1,000 Cash Back: The Pass-Through of Auto Manufacturer Promotions

Automobile manufacturers frequently use promotions involving cash incentives. While payments are nominally directed to either customers or dealers, the ultimate beneficiary of the promotion depends on the outcome of price negotiation. We use program evaluation methods to compare the incidence of these two types of promotions. Customers obtain 70 to 90 percent of a customer rebate, but only 30 to 40 percent of a dealer discount promotion, a $500 difference for a typical promotion. Our leading hypothesis is that pass-through rates differ because of information asymmetries: customer rebates are well-publicized to customers, while dealer discount promotions are not. (JEL D82, L11, L15, L62, L81, M31)
SEA2009 DRAFT NOT FOR GENERAL DISTRIBUTION Specifying, Simulating, and Estimating Multivariate Extreme Value (GEV) Discrete Choice Models in Fisheries 1

In this paper, we explore estimable Generalized Extreme Value (GEV) spatial discrete choice models. In the statistics literature, GEV models are termed multivariate extreme value (MEV). Interestingly, most of the discrete choice literature aside from GEV models develops choice probabilities by focusing on the underlying error structure and then integrating to arrive at the choice probabilities. However, it seems fair to characterize the GEV literature as proceeding largely from the position of establishing how functions of random variables are consistent with the GEV requirements and then derives choice probabilities using a basic probability-generating relationship. We believe that understanding random component based interpretations of GEV models yields productive insights into the structure of the models just as it has in other discrete choice contexts such as with the mixed logit and the multinomial probit model. To accomplish this, we first provide the standard treatment of GEV models, then discuss a cross-nested version of these models and relate them to earlier statistical work. This method of conceptualizing the GEV discrete choice problem opens up avenues of incorporating spatial correlation that are better adapted to modeling spatial choice in economic activities such as fishing location choice. We explore various random effects structures that provide for correlation in zonal discrete choice models. These include pair-wise correlation models that are part of the cross-nested family, and new models that interact inter-zonal distances with the positive alpha-stable scale components, thus inducing correlated zonal utilities (profits) in an economical manner. In coming work, the model will be applied to the Bering Sea pollock fishery.
Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title Modeling individual differences in socioeconomic game playing Permalink

Game theory has been useful for understanding risk-taking and cooperative behavior. In the present study, subjects played the Hawk-Dove game with simulated and embodied (robotic) neural agents which used a neurobiologically plausible model of action selection and adaptive behaviors. Subjects had their serotonin levels temporarily altered through acute tryptophan depletion (ATD). The traditional assumption for subject data from Game-theory-ATD or human robot interaction (HRI) studies is that all participants come from the same underlying distribution or same group. We used probabilistic graphical models in order to determine potential sub-group affiliations based on the subjects’ responses while playing the Hawk-Dove game. The results from the models indicate sub-groups within a subject population exist. We find that two-group, one that tends toward cooperation and the other that tends toward aggression, best describes the effect of subject behavior in response to ATD and embodiment.
Early life and its implications for astrobiology : a case study from Bitter Springs Chert, Australia

Early life research faces additional challenges than those of the study of later life forms. Due to the de-materialization of the earliest rocks, valuable information about the early Earth is forever lost. Furthermore, early life was small and morphologically basic, effectuating abiotic pseudofossils to infiltrate the fossil record. A central theme is the close connection early life research share with astrobiology, manifested by the notion that early terre-strial life research should be conducted with as much vigilance as potential fossil findings from a remote planet. Both fields benefit from a broad-minded approach as the basic building blocks of life, previously thought to be pre-sent in all life forms, might have room for interchangability. Therefore, the biomarkers traditionally searched for might not reveal the full story of life. Petrography, XRF, SEM and FTIR was applied to rocks from Bitter Springs Formation, Australia, in hope to detect biogenic material. Hydrocarbons were detected in one of the samples thro-ugh FTIR analysis, which is a strong indicator for biogenicity. Many structures were found that are most probably bacterial fossils and oncoid structures.
Volatility forecasting of carbon prices using factor models

This article develops a forecasting exercise of the volatility of EUA spot, EUA futures, and CER futures carbon prices (modeled after an AR(1)-GARCH(1,1)) using two dynamic factors as exogenous regressors that were extracted from a Factor Augmented VAR model (Bernanke et al. (2005)). The dataset includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 through January 25, 2010 totalling 463 observations that capture the strong uncertainties emerging on the carbon market. The main result shows that the best forecasting performance for the volatility of carbon prices is achieved for the model including the dynamic factors as exogenous regressors, which can be useful to inform hedging or speculative trading strategies by energy utilities, financial market players and risk managers.
Chapter 7 Niobium in Cast Irons

This work reviews the effect of niobium on different cast irons. This alloying element has a high affinity by carbon forming carbides of the type MC; therefore, the main effect is to strengthen the matrix of the alloys due to a hard-phase dispersion mechanism. Even at low levels of niobium (<0.2%), MC carbides are found. The presence of such carbides increases hardness, yield and tensile strength in ductile irons, but the most important role is to increase wear resistance. Therefore, the use of niobium has been focussed mainly in alloyed white irons for wear resistance applications and in mottled cast iron used for rolls in hot rolling mills.
ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

Abstract. Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.
Is the Endangered Species Act Endangering Species?

We develop theory and present a suite of theoretically consistent empirical measures to explore the extent to which market intervention inadvertently alters resource allocation in a sequentialmove principal/agent game. We showcase our approach empirically by exploring the extent to which the U.S. Endangered Species Act has altered land development patterns. We report evidence indicating significant acceleration of development directly after each of several events deemed likely to raise fears among owners of habitat land. Our preferred estimate suggests an overall acceleration of land development by roughly one year. We also find from complementary hedonic regression models that habitat parcels declined in value when the habitat map was published, which is consistent with our estimates of the degree of preemption. These results have clear implications for policymakers, who continue to discuss alternative regulatory frameworks for species preservation. More generally, our modeling strategies can be widely applied -- from any particular economic environment that has a sequential-move nature to the narrower case of the political economy of regulation.
Reprogramming of DNA methylation at NEUROD2-bound sequences during cortical neuron differentiation

The authors show that cortical neuron differentiation involves demethylation of a large number of NEUROD2 target sequences. The characteristics of DNA methylation changes that occur during neurogenesis in vivo remain unknown. We used whole-genome bisulfite sequencing to quantitate DNA cytosine modifications in differentiating neurons and their progenitors isolated from mouse brain at the peak of embryonic neurogenesis. Localized DNA hypomethylation was much more common than hypermethylation and often occurred at putative enhancers within genes that were upregulated in neurons and encoded proteins crucial for neuronal differentiation. The hypomethylated regions strongly overlapped with mapped binding sites of the key neuronal transcription factor NEUROD2. The 5-methylcytosine oxidase ten-eleven translocation 2 (TET2) interacted with NEUROD2, and its reaction product 5-hydroxymethylcytosine accumulated at the demethylated regions. NEUROD2-targeted differentially methylated regions retained higher methylation levels in Neurod2 knockout mice, and inducible expression of NEUROD2 caused TET2-associated demethylation at its in vivo binding sites. The data suggest that the reorganization of DNA methylation in developing neurons involves NEUROD2 and TET2-mediated DNA demethylation.
Subgraphs for Web Discovery

Recommendations are central to the utility of many popular e-commerce websites. Such sites typically contain a set of recommendations on every product page that enables visitors and crawlers to easily navigate the website. These recommendations are essentially universally present on all e-commerce websites. Choosing an appropriate set of recommendations at each page is a critical task performed by dedicated backend software systems. We formalize the concept of recommendations used for discovery as a natural graph optimization problem on a bipartite graph and propose three methods for solving the problem in increasing order of sophistication: a local random sampling algorithm, a greedy algorithm and a more involved partitioning based algorithm. We first theoretically analyze the performance of these three methods on random graph models and characterize when each method will yield a solution of sufficient quality and the parameter ranges when more sophistication is needed. We complement this by providing an empirical analysis of these algorithms on simulated and real-world production data from a retail website. Our results confirm that it is not always necessary to implement complicated algorithms in the real-world, and demonstrate that very good practical results can be obtained by using simple heuristics that are backed by the confidence of concrete theoretical guarantees.
Review on Text-to-Speech Systems and Speech Synthesizing Techniques

The most common, easy and feasible ways of communication is speech. Due to wide range of applications and physically disabled people requires an application to convert text to speech. Now a days Gujarati language is also widely used as a communication medium. Many systems has been developed so far to convert text to speech with one or more limitations. This review paper includes overview about text to speech systems developed for Gujarati language. The techniques to develop speech synthesizer are included. All individual technique is having limitations. So, to overcome these limitations, methodology is provided to develop a hybrid synthesizer for text to speech conversion for Gujarati Language. As a result, A good speech synthesizer achieves two quality measures of text to speech system: Naturalness and Intelligibility. The produced speech than pass through Super position algorithm developed using Formant Synthesizer and Timedomain Synthesizer to achieve more prosody on output and synthesized speech.
Migration, Remittances, Poverty and Inequality The Philippines

The paper looks into the effects of international migration and remittances on household incomes and well-being, poverty reduction, human capital investment, saving, and regional development in the home country. Remittances appear to raise average incomes for all income groups but more so for the richer households than for the poorer ones, a finding that is consistent with that in several Latin American countries. Such eyeballing of the data is supported by econometric analysis which further reveals that remittances enhance household savings, spending on education and health care, and help the poor move out of poverty. Analysis at the regional level shows that, ceteris paribus, remittances also appear to contribute importantly to regional development, although overall increases in regional incomes do not seem to benefit low income households as much as the upper income ones.
Pioneer interneurons instruct bilaterality in the Drosophila olfactory sensory map

An adhesion-based developmental mechanism triggers global brain circuit organization. Interhemispheric synaptic connections, a prominent feature in animal nervous systems for the rapid exchange and integration of neuronal information, can appear quite suddenly during brain evolution, raising the question about the underlying developmental mechanism. Here, we show in the Drosophila olfactory system that the induction of a bilateral sensory map, an evolutionary novelty in dipteran flies, is mediated by a unique type of commissural pioneer interneurons (cPINs) via the localized activity of the cell adhesion molecule Neuroglian. Differential Neuroglian signaling in cPINs not only prepatterns the olfactory contralateral tracts but also prevents the targeting of ingrowing sensory axons to their ipsilateral synaptic partners. These results identified a sensitive cellular interaction to switch the sequential assembly of diverse neuron types from a unilateral to a bilateral brain circuit organization.