Miracle-dz/UniFAR-FTUs huggingface dataset:
Model Estimation for LongitudinalBone Growth Based on Age in Male and Female Commercial Broiler Chickens

Longitudinal bone growth is essential to support rapid body growth in commercial broiler chickens. The present study aimed to determine which simple mathematic model is best suitable for explaining the absolute and the relative bone growth in length (expressed as a ratio of bone length to body weight) as a function of age in male and female commercial broiler chickens over the first 35 days of age. A total of 1,800 broiler chickens (900 males and 900 females) of Cobb 500, Ross 308, and Arbor Acres raised in standard commercial broiler houses were randomly selected for this study. Body weight and the lengths of backbones, third toe, shank bone, and keel bone were individually measured in all chickens at 1, 7, 14, 21, 28, and 35 days of age. Regression analysis (with 4 simple mathematical models including linear, logarithmic, inverse, and exponential) was used to find a suitable model for estimating the absolute and the relative bone growth in length. In addition, an adjusted R was used to assess the model fitting. The results indicated that the absolute bone growth in length linearly increased with age. The adjusted R values for the linear model were 0.973, 0.937, 0.950, and 0.974 for the lengths of the backbones, third toe, shank bone, and keel bone, respectively. However, the relative bone growth in length logarithmically decreased with age. The adjusted R values of the logarithmic model were 0.971, 0.952, 0.957, and 0.905 for the relative length of the backbones, third toe, shank bone, and keel bone, respectively.The present investigation suggests thata linear model is a suitable model for estimating the absolute bone growth in length, but a logarithmic model is a proper model for estimating the relative bone growth in length of commercial broiler chickens.
Alternatives to GMM : Properties of Minimum Divergence Estimators

This paper considers estimation and inference using Minimum Divergence (MD) techniques. MD estimators are obtained by minimizing a divergence between the empirical distribution and the distribution implied by moment restrictions. Methods that have received attention as possible alternatives to GMM, such as Empirical Likelihood, Exponential Tilting and Continuous Updating, are all special cases of Minimum Divergence estimators. The paper makes the following main contributions. First, it proves that there is a relationship between the Generalized Empirical Likelihood (GEL) class of estimators and the MD class that extends beyond the known cases. Second, a Bayesian interpretation of the weighting scheme through which the MD reweighs the observations is given. Third, it is shows that all the members of the MD class that have the same asymptotic bias of Empirical Likelihood are third-order e¢ cient. This result implies that higher order e¢ ciency is an inadequate criterion for prescribing which speci c estimator should be used in applied work. I argue that in selecting from the class of third order e¢ cient estimators, one should consider the boundedness of the inuence function. Monte Carlo simulations show that test statistics based on estimators that are third order e¢ cient and have a bounded inuence function have smaller size distortion in nite sample than tests based on third order e¢ cient estimators with unbounded inuence function. I thank my advisors Graham Elliott, Hal White, Eli Berman and Roger Gordon for their guidance and support. I am grateful to Francesca Mazzolari, Seth Pruitt and Barbara Rossi for comments.
Data-Driven , Bottom-up , Asynchronous Federated Learning

Federated learning (FL) is a distributed machine learning approach that can train a model on decentralized sets of data without the data ever leaving their host devices. The predominant FL model is the Google FL protocol (GFL), which is a topdown, synchronous and time-division resource allocation system. It faces several issues, such as increased bias in selecting data and inability to scale beyond a small number of devices. In this paper, we design and investigate an alternative FL architecture to address the challenges of GFL. Our system is a bottom-up, data-driven, asynchronous resource allocation system, that maximizes key resources consisting of samples, computation, and bandwidth. The performance of our system is evaluated with the MNIST dataset on a networked prototype system. The experimental results show that our system improves fairness and scalability without compromising convergence efficiency.
The protective effect of catalpol on respiratory syncytial virus infection

Respiratory syncytial virus (RSV) infection can cause severe bronchiolitis, pneumonia or even death in infants, or induce childhood asthma. Currently no specific drug is available for RSV infection. With multiple pathology roles, catalpol has significant roles in anti-oxidation and anti-infection, but has not been studied in RSV infection. This study aimed to investigate the effects and mechanism of catalpol on RSV infection via establishing a mouse RSV infection model, further illustrating the effect of catalpol on RSV infection and providing evidences for clinical treatment. BALB/c mice were used to generate a RSV infection model using intranasal drops of viral solutions, and mice were then treated with 5 mM or 10 mM catalpol. Real-time fluorescent quantitative PCR was used to measure RSV load in mouse pulmonary tissues, while ELISA was used to quantify expression of inflammatory factors including TNF-α and IL-1β. Real-time PCR and Western blot were used to test cellular expression of NF-κB (p65) mRNA and protein expression. ROS and SOD activity in all cells were analyzed. Compared to the control group, RSV infected mice had higher RSV load in pulmonary tissues, elevated serum TNF-α and IL-1β levels, expression of NF-κB mRNA and protein, higher ROS contents and lower SOD activity (p < 0.05). Catalpol can decrease RSV load and ROS contents, elevate SOD activity, decrease NF-κB mRNA and protein expressions, and suppress TNF-α and IL-1β levels (p < 0.05 compared to model group) in a dose-dependent manner. Catalpol can exert anti-RSV infection roles via modulating oxidation/anti-oxidation balance and inhibiting inflammation progression.
The Benefits of Commitment to a Currency Peg : Lessons from the National Banking System

The experience of the U.S. in the late nineteenth century indicates that eliminating speculation about a government’s commitment to a currency peg can have significant effects on bank balance sheets and the real economy. In particular, the resolution of uncertainty about the commitment of the U.S. government to the gold standard was associated with a large and permanent increase in the leverage of National Banks, as well as with a sharp reduction in its volatility. The defeat of the anti-gold candidate in the 1896 presidential election provided a cleanly identified positive shock to commitment to gold, in which gains were most pronounced among banks located in states where agents were more likely to have access to gold denominated assets. We use the election to identify the importance of commitment throughout the period in a structural factor analysis. We find that, in the last decade of the nineteenth century, full commitment to the currency peg could have reduced the volatility of real activity significantly and substantially reduced the depression starting in 1893. JEL classification: E42, E44, F33, G01
Parallelization of Velvet , “ a de novo genome sequence assembler ”

Genome assembly is one of the most complex and computationally intensive tasks of genome sequence analysis. There are various parallel and serial tools available for genome assembly. Some parallel tools require as much as 2 days to assemble human genome. Serial tools are incapable of achieving this milestone even on a powerful machine with 256 GB of memory. Velvet is one such serial tool which requires 14 GB of memory even for a small bacteria genome, therefore memory is a major limitation of Velvet. In this paper we present our work on parallelization of VelvetH (the primer part of Velvet). As a demonstration of the capability of our parallel-VelvetH, we hashed the human genome in as low as 1 hour 30 minutes.
Patterns of genetic diversity in African forest elephants living in a human‐modified landscape in southwest Gabon

We investigated the patterns of genetic diversity and structure of African forest elephants in a human‐modified landscape in the Gamba complex of protected areas (GCPA), a tropical wilderness area along the southwest coast of Gabon. We collected 298 elephant fecal samples from four sites (Sette Cama, Gamba area, Vera Plains, and Mayonami), along approximately 80 km of coastline from north to south. We used microsatellites and mitochondrial DNA (mtDNA) to successfully genotype 295 of the 298 fecal samples, and identified 213 individuals. Using sex markers, we identified 84 males and 118 females; we could not determine the sex of the remaining 11 individuals. We also characterized the sex, group size, and social status of crop‐raiding elephants and did not find characteristics distinguishing them from nonraiders. Overall, our mtDNA and microsatellite markers revealed that elephants in the research area maintain high levels of genetic variation and low levels of subdivision. Gene flow appears to be mostly mediated by male dispersal away from natal herds. Our structure analysis revealed two highly admixed genetic clusters, attributable to high connectivity among the protected areas. However, forest areas within the GCPA have become increasingly fragmented by human‐induced habitat modification. We detected a pattern of isolation by distance, accentuated by the presence of the town of Gamba between Sette‐Cama and Mayonami. We found a high degree of connectivity among sampling locations within the GCPA. This supports the importance of establishing agricultural best practices to reduce habitat loss that may sever gene exchange and to maintain connectivity, as well as to avoid human–elephant conflict that can result in retaliatory killing of elephants in this area. This study emphasizes the importance of conducting baseline monitoring of demographic data, genetic diversity, and structure to enable future comparisons to assess the long‐term impact of human‐induced habitat fragmentation.
Aspectos anestésicos do grande obeso Anesthetic aspects of the very obese

The obese population is increasing worlwide and the knowledge on morbid obesity repercussions has been significantly extended. Surgical intervention for its treatment is increasingly being performed and because of this new situation it has become important to clearly know the risk factors to which these patients are submitted. Morbid obesity is a systemic disease affecting different organs and systems, mainly the cardiovascular and respiratory systems, including also the upper respiratory airways becoming as it is quite important to the anesthesiologist. The farmacology of drugs is also envolved and will be focused particularly in this paper. We will provide major information on the alterations in different organs and systems that lead to risk factors and their possible influence on anesthesia, allowing the anesthesiologist to plan a more safe and specific type of anesthesia.
Large‐Amplitude Quasi‐10‐Day Waves in the Middle Atmosphere During Final Warmings

Geopotential height measurements from the Aura Microwave Limb Sounder between 9‐ and 97‐km altitudes during 2004–2018 are used to examine long‐period (3–20 days) wave activity during the Northern Hemisphere winter and spring, with the primary focus on the response of normal mode Rossby waves in the middle atmosphere to sudden stratospheric warmings (SSWs). Unusually large westward propagating waves with Zonal Wave Number 1 and period ∼10 days are observed at 55° latitude at the stratopause height (∼48 km) and above following final warmings of 2016, 2015, and 2005. In each case, large‐amplitude waves are observed for the duration of two to three wave cycles. Characteristics of the waves are in conformity with the second antisymmetric Rossby normal mode of Zonal Wave Number 1, or the quasi‐10‐day wave. The growth rate of the waves is significantly greater than the classical normal mode in the upper stratosphere (approximately 30–50 km) where instability conditions are met, indicating the amplification or excitation of the waves in that region. The response of the quasi‐10‐day wave during midwinter SSWs, and also during the spring transition without an SSW, is not as obvious as the wave response during final warmings. The results suggest that not only the occurrence of SSW but also the seasonal timing of SSW is an important factor for the transient variability of the quasi‐10‐day wave in the middle atmosphere.
Special Economic Zones

The thesis deals with special economic zones (SEZs). The first part, chapter 2-5, explains them as a phenomenon. Their history and features/incentives are spelled out, as are their underlying rationale – the advantages the host can achieve through them (chapter 4.1). These possible advantages include increased employment; cluster effects; technology transfer and training; partial policy reforms; laboratory simulations of economic policy and being a means of regional policies. An important way SEZs can achieve this is to attract foreign direct investments. Also the possible costs of zones are presented (chapter 4.2) as well as their alternative cost (chapter 4.3). To complete this part of the analysis chapter 5 presents the point of view of the firms, i.e. the investors SEZs are supposed to lure. The second part of the thesis, chapter 6-7, applies the first part on the case of India. This results in some specific advice, implications, for the SEZ policy of India. These include using SEZs as laboratories to find beneficial general economic policies and SEZ policies; to include the Indian diaspora to a greater extent to achieve the chapter 4.1 advantages; the promotion of cluster effects; as well as others. The rapid change in the Indian economy increases the uncertainty, but the main recommendations should be robust in all likely scenarios.
The Causes of Sudden Windstorm Inducing a Deadly Threat to Coastal Safety: A Case Study for the Fishing Boat Overturning on February 28, 2018

Kim, H. ; An, H. -Y. , Jeong, J.-H. , Kang, Y. -H. , Song, S. -K. , and Kim, Y. -K. , 2019. The causes of sudden windstorm inducing a deadly threat to coastal safety: A case study for the fishing boat overturning on February 28, 2018. In: Lee, J.L. ; Yoon, J.-S. ; Cho, W.C. ; Muin, M. , and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 61-65. Coconut Creek (Florida), ISSN 0749-0208.The incidence of overturning fishing vessels was approximately 2.7% of the total number of incidents involving fishing vessels in 2017, which is much smaller than that of engine failures or collisions, but it cannot be overlooked easily considering the damage scale (property and human life). In particular, after the sinking of the MV Sewol, also referred to as the Sewol Ferry Disaster, in 2014, the ship incident along with the casualties has been a great shock and trauma to the Korean people so far. On the afternoon of February 28, 2018, the fishing boat, Keun-Ryong, overturned in the open sea in front of Wando Island, causing seven casualties (two deaths and five missing persons) that also caused the shockwaves through the social community in Korea. According to media reports, the national coast guard deduced that the fishing vessel faced an unexpected condition and the crews could not press the distress signal button. In addition, bad weather condition due to wind gusts was considered the main cause. The instantaneous maximum wind speed in the shore near the accident area reached 20.7 m/s, but the quantitative wind speed at the accident spot was not known due to the absence of weather observations. To determine if a strong wind gust can overturn a fishing boat and to overcome the limitation due to the absence of weather observations in the open sea, high-resolution modelling was carried out using the WRF model in this study. A range of observation data were used to verify the model prediction as well as performance and to analyze the atmospheric instability between the upper and lower levels. Efforts need to be made prevent such accidents from recurring by predicting when similar weather conditions occur in the future.
Synthetic geomechanical logs and distributions for marcellus shale

Synthetic Geomechanical Logs and Distributions for Marcellus Shale Mohammad O. Eshkalak The intent of this study is to generate synthetic Geomechanical Logs for a specific Marcellus Shale asset using Artificial Intelligence and Data mining Technology. Geomechanical Distributions (Map and Volume) for the entire Marcellus Shale asset was completed. In order to accomplish the objectives, conventional well logs such as Gamma Ray and Bulk Density are used to build Data-Driven models. The Data-Driven technique used in this study is applicable to other shale reservoirs. Successful recovery of hydrocarbons from the reservoirs, notably shale, is attributed to realizing the key fundamentals of reservoir rock properties. Having adequate and sufficient information regarding the variable lithology and mineralogy is crucial in order to identify the “right” pay-zone intervals for shale gas production. In addition, contribution of mechanical properties (Principal stress profiles) of shale to hydraulic fracturing strategies is a wellunderstood concept. It may also contribute to better, more accurate simulation models of production from shale gas reservoirs. In this study, synthetic Geomechanical logs (Including following properties: Poisson’s Ratio, Total Minimum Horizontal Stress, Bulk and Shear Modulus, etc.) are developed for more than 50 Marcellus Shale wells. Using Artificial Intelligence and Data Mining (AI&DM), datadriven models are developed that are capable of generating synthetic Geomechanical logs from conventional logs such as Gamma Ray and Density Porosity. The data-driven models are validated using wells with actual Geomechanical logs that have been removed from the database to serve as blind validation wells. In addition, having access to necessary data to building Geomechanical distributions (Map and Volume) model can assist in understanding the rock mechanical behavior and consequently creating effective hydraulic fractures that is considered an essential step in economically development of Shale assets. Moreover, running Geomechanical logs on a subset of wells, but having the luxury of generating logs of similar quality for all the existing wells in a Shale asset can prove to be a sound reservoir management tool for better reservoir characterization, modeling and efficient production of Marcellus Shale reservoir.
Real-time coseismic deformations from adaptively tight integration of high-rate GNSS and strong motion records

In traditional tight integration of high-rate GNSS and strong motion sensors, an appropriate process variance is crucial for obtaining accurate broad-band coseismic deformations. In this paper, instead of using a subjectively empirical value, we present an approach for determining the process variance adaptively based on the adaptive Kalman filter for real-time use. The performance of the approach was validated by the colocated stations collected during the 2010 Mw 7.2 earthquake in El-Mayor, 2016 Mw 7.8 earthquake in New Zealand and 2016 Mw 6.5 earthquake in central Italy. The results show that this method complements the advantages of GNSS and strong motion accelerometers and can provide more accurate coseismic waveforms especially during the strong shaking period, due to the ability of the method to adjust the process variance in real time according to the actual status of the station. In addition, this method is also free from the influence of the baseline shift. Testing of the new method for the integration of strong motion and multi-GNSS indicates that multi-GNSS has an obvious improvement in the precision while single GPS has a poor observation condition.
The Effect of Height Increase Elevator Shoes Insole on Gait and Foot Pressure

Purpose: The purpose of this study was to investigate the effect of 0cm, 2.5cm, 5cm height increase elevator shoes insole on gait and foot pressure Methods: Fifteen young adult were recruited this study. Gait and foot was measured by Gait AnalyzerTM(Tech Storm Inc. korea). Statistical analysis was used one-way ANOVA to know difference between 0cm, 2.5cm insole and 5cm insole Results: There was no significantly difference on foot length, foot width, foot angle, step time during gait. But step length and step width was significantly difference during gait. There was no significantly difference on gait ratio during stance phase. There was significantly difference on forefoot pressure and rearfoot pressure ratio. Conclusion: These results indicate that height increase elevator shoes insole may be caused step length, step width decreaseed during gait. It caused forefoot pressure increased and rearfoot pressure decreased on foot.
Datos enlazados de información geográfica del Ecuador

Actualmente, la gran cantidad de información geográfica generada por diferentes instituciones exige que se propongan nuevas soluciones de gestión y publicación de estos datos. En Ecuador, la heterogeneidad de la información geográfica generada por diversos entes y publicada en la Web no es una excepción. Con el objetivo de dar solución a esta problemática, el proyecto Geo Linked Data Ecuador integra información geográfica proveniente de diversas fuentes y la publica en formato RDF bajo estándares y recomendaciones de la comunidad de la Web Semántica, creando así el repositorio de datos enlazados geográficos del Ecuador.
Updating estimates of low-streamflow statistics to account for possible trends

ABSTRACT Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7Q10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7Q10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7Q10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.