Miracle-dz/UniFAR-FTUs huggingface dataset:
Human capital accumulation and growth with heterogeneous skills

We extend the Lucas’ 1988 model introducing two classes of agents with heterogeneous skills, discount factors and initial human capital endowments. We consider two regimes according to the planner’s political constraints. In the first regime, that we call meritocracy, the planner faces individual constraints. In the second regime the planner faces an aggregate constraint, redistributing. We find that heterogeneity matters, particularly with redistribution. In the meritocracy regime the optimal solution coincides with the BGP found by Lucas (1988) for the representative agent’s case. In contrast, in the redistribution case the solution for time devoted to capital accumulation is never interior for both agents. Either the less talented agents do not accumulate human capital or the more skilled agents do not work. Moreover utility under the redistribution regime is always higher than under meritocracy and it is optimal to exploit existing differences. Finally we find that inequality in human capital distribution increases in time and that in the long run inequality always promotes growth.
GLOBALIZATION, POVERTY, AND ECONOMIC GROWTH: THE CASE OF SOUTH AFRICA By: T. O. Akinbobola and C. A. Isike

This paper takes a cursory look at the empirical relationship between the inflow of capital, globalization (as proxied by the degree of openness), poverty, and economic growth in South Africa. The vector autoregressive modeling technique was used in determining the relationship between these variables. It was found that variation in economic growth in South Africa was explained by factors beyond foreign capital inflow and economic openness in the short run; however, it is of little consideration in the long run. Capital inflow explains a significant change noticed in the human development index as the inflow of capital and economic openness had positive impact on poverty reduction. In essence, trade liberalization has not substantially impacted on the growth rate of the South African economy. This implies that fluctuations in real economic growth in this country should be seen beyond the external shock from the capital inflows or trade flows. Accordingly, the paper recommends that policy focus should be on areas that will encourage job creation and these include, for instance, investments in real sector rather than portfolio investment, which has been the case.
Computation of synthetic seismogram in real earth model by eigen function expansion

The method of eigen function expansion has been used in the present study to compute synthetic or theoretical seismogram in layered elastic half-space of real earth model. Simple dislocation source model has been considered. The transverse (SH) or radial and vertical (P-SV) components of displacement field have been computed as summed modes and compared by using both exact and numerical techniques. The methods used in the study, include exact evaluation by propagator matrix approach using Reflection-Transmission coefficients as well as numerical computations using Runge-Kutta method of order 4. The specialty of the present study is to evaluate approximate displacement field for the earth models with homogeneous and / or inhomogeneous layers. The normalization technique has been used in the study to control the overflow errors. The study has an advantage to get an idea of earth structure or source model by an inverse iterative technique.
Monitoring of ECG Signals by using Neural Network

: Cardiac arrhythmias are classified by abnormal activities in the heart. These abnormalities can be analyzed by an electrocardiogram (ECG). Details from this electrical signal can be used to classify what type of arrhythmia, if any, the patient has by analyzing the PQRST wave properties. Multiple data samples of normal ECG characteristics also were read by an artificial neural network (ANN) and analyzed for the differences between a normal signal and an irregular signal. The data was extracted from the MIT-BIH Arrhythmia database. A typical method used to analyze cardiac arrhythmias is to take the Fast Fourier Transform (FFT) of the signal. In this study, an alternate method is used to predict cardiac arrhythmias. A neural network is designed and programmed with this data and then tested to validate the data set. The pattern recognition tool in MATLAB is then used to analyze and predict the data. The program results were tested to validate the data set. The ANN achieved 98.6% accuracy on the test data. The findings and outcome probabilities from this study are more accurate than some current methods of analysis used today. When neural networks are further used to analyze and test medical data samples, the medical community and patients will experience improvements in the diagnosis of heart abnormalities and early detection of debilitating medical conditions.
Forecasting Corporate Bankruptcy: Applying Feature Selection Techniques to the Pre-and Post-Global Financial Crisis Environments

I investigate the use of feature selection techniques to forecast corporate bankruptcy in the years before, during and after the global financial crisis. Feature selection is the process of selecting a subset of relevant features for use in model construction. While other empirical bankruptcy studies apply similar techniques, I focus specifically on the effect of the 2007-2009 global financial crisis. I conclude that the set of bankruptcy predictors shifts from accounting variables before the financial crisis to market variables during and after the financial crisis for one-year-ahead forecasts. These findings provide insight into the development of stricter lending standards in the financial markets that occurred as a result of the crisis. My analysis applies the Least Absolute Shrinkage and Selection Operator (LASSO) method as a variable selection technique and Principal Components Analysis (PCA) as a dimensionality reduction technique. In comparing each of these methods, I conclude that LASSO outperforms PCA in terms of prediction accuracy and offers more interpretable results. My findings shed light on the implications of stricter lending requirements affecting corporate bankruptcy forecasting.
Longitudinal Baseline Study to Support Emergency Response Management using 911 Calls Data

Any emergency event distributed over an area and affecting people living in the United States is controlled and registered by the regional emergency operations center. This regional operations center then handles the event based on its severity and type of operation required for that particular emergency event. There are many important decisions that are made when an incident like this occurs. The information in hand for the person in charge is not always adequate to make decisions in the limited time allowed. In this paper, we have analyzed previous ten years of data obtained from Monroe county public safety department. A longitudinal baseline study has been performed on this data set to look into trends around event frequencies, call durations and some more. The analysis performed and the results obtained from the same is aimed to assist emergency event officer in charge for future decision making. Individual monthly analysis integrated together for better performance has been done and discussed in this paper. Although the models selected for the predictive analysis and the solution obtained from classification techniques is performed on the entire dataset, there are few instances where some attributes could not be mapped to numeric values. Due to which there was a considerable amount of prepossessing and data preparation performed. In this paper, we have focused on analyzing emergency response system pertaining to a specific region.
University of Birmingham Online Ensemble Learning of Data Streams with Gradually Evolved Classes

— Class evolution, the phenomenon of class emergence and disappearance, is an important research topic for data stream mining. All previous studies implicitly regard class evolution as a transient change, which is not true for many real-world problems. This paper concerns the scenario where classes emerge or disappear gradually. A class-based ensemble approach, namely Class-Based ensemble for Class Evolution (CBCE), is proposed. By maintaining a base learner for each class and dynamically updating the base learners with new data, CBCE can rapidly adjust to class evolution. A novel under-sampling method for the base learners is also proposed to handle the dynamic class-imbalance problem caused by the gradual evolution of classes. Empirical studies demonstrate the effectiveness of CBCE in various class evolution scenarios in comparison to existing class evolution adaptation methods.
Medical Selfies: Emotional Impacts and Practical Challenges

Medical images taken with mobile phones by patients, i.e. medical selfies, allow screening, monitoring and diagnosis of skin lesions. While mobile teledermatology can provide good diagnostic accuracy for skin tumours, there is little research about emotional and physical aspects when taking medical selfies of body parts. We conducted a survey with 100 participants and a qualitative study with twelve participants, in which they took images of eight body parts including intimate areas. Participants had difficulties taking medical selfies of their shoulder blades and buttocks. For the genitals, they prefer to visit a doctor rather than sending images. Taking the images triggered privacy concerns, memories of past experiences with body parts and raised awareness of the bodily medical state. We present recommendations for the design of mobile apps to address the usability and emotional impacts of taking medical selfies.
Evaluation of water resource carrying capacity of Qitai Oasis in Xinjiang by entropy method: Evaluation of water resource carrying capacity of Qitai Oasis in Xinjiang by entropy method

The reality is that there today exists not only an increasing scarcity of water resources, but also worsening ecology of the Qitai Oasis in Xinjiang. It is thus urgent to build an index system of water resources carrying capacity. So, in this paper, principal component and entropy analyses were used to select and empower the main indexes of water resources carrying capacity in the oasis region. Water resources carrying capacity of Qitai Oasis was analyzed and evaluated to facilitate not only rational use of water resources in the oasis region but also sustainable development of the oasis ecology. The results showed that water resources carrying capacity in the oasis region was 0.83 and 0.75 in 1993 and 1998, respectively. It dropped to the lowest value of 0.66 in 2005. The trend of decline in water resources carrying capacity accelerated with time. The rate of decline in 2003 to 2005 was 47.96 times as much as that in 1993 to 1998 and 8.93 times that in 1999 to 2002. Qitai Oasis water resources carrying capacity was mainly driven by five main factors, including economic and ecological factor, population factor, agricultural water use factor, climatic factor, and other water uses factor. The accumulated contribution rate of the three former factors was 73.58%. This was a solid reflection of the negative effects of rapid economic development, increasing population and agricultural irrigation, and worsening ecological environment on the availability of water resources and the increasing potential for further water saving in the oasis region.
Computation of Acoustic Sources for the Landing Gear During the Take-Off and Landing

The sound which is generated from the aircraft during the take-off and landing is one of the main problems for the people who live in the areas near the airport. It is very important to allocate and accurately calculate acoustic sources generated from turbulent flow produced by the aerodynamics components of the aircraft. This is done in order to calculate inhomogeneous term of Helmholtz equation which serves as a prediction tool of sound propagation in the domain. It is used subgrid-scale stabilized (SGS) finite element method for solving incompressible Navier-Stokes equation which simulate turbulent flow. Afterwards is done double divergence of Litghill’s tensor in order to calculate acoustics sources. Further, the transformation from time domain to frequency domain is used with Direct Fourier Transform which leads to smaller memory usage and computational cost. The aim of the article is to show that previously mention method lead to better and richer representation of the spectrum of frequencies obtained from turbulent flow. Good representation of spectrum will give better inhomogeneous term of Helmholtz equation. Better prediction and calculation of acoustics sources will lead to reduction of sound generation through design of aerodynamics components on the aircraft.
Bid-Ask Spreads: Measuring Trade Execution Costs in Financial Markets

Bid-Ask spreads, which measure trade execution costs, and reflect the price concessions necessary to complete transactions quickly, are important as indicators of market quality and in determining traders’ actual investment results. Execution costs arise because it is costly to provide liquidity, and can be estimated based on comparisons of trade prices to proxies for underlying security value, with the most common proxy being the quote midpoint. Comparisons can be of trade prices to midpoints at or before the time of the trade, as in effective spread measures, or to midpoints after the trade, as in realized spread measures. Recent research indicates that trade execution costs have declined in U.S. markets in recent years, and documents substantial variation in average trading costs across international equity markets.
Tricks for exit times and exit probabilities

For one-dimensional diffusion processes, there are some nice tricks, and even closed-form solutions, for exit probabilities and expected exit times from intervals (see Section 1 of these notes), but also for densities (Section 3). These methods are especially useful when we have to determine if a diffusion whose volatility converges to zero at a boundary will ever hit that boundary (see Section 2). As far as I know, no equivalent results are available for multidimensional processes; however, some PDEs still hold, which can be exploited computationally (see Section 4). The notes mainly build on ideas laid out in the paper by Helland (1996), but try to bring them to a level that is accessible to mere mortals. The closed-form solutions for densities are taken from Luttmer’s (2007) beautiful paper on firm dynamics.
1 A Comparative Study of Light Emitting Diodes based on All-Inorganic Perovskite 1 Nanoparticles ( CsPbBr 3 ) Synthesized at Room Temperature and by Hot Injection Method 2

Perovskite nanoparticles (PeNPs) have been extensively studied for optoelectronic 9 applications due to their extremely high photoluminescence quantum yield, tunable bandgap, 10 and exceptionally narrow emission spectra. Therefore, PeNPsare considered excellent 11 candidates for the development of high efficiency, low-cost, wide gamut and high purity color 12 displays. However, their synthesis typically involves multi-step cumbersome processes that 13 might hinder its commercial development. In this work, we reportgreen light-emitting diodes 14 (LEDs) prepared using all inorganic PeNPs CsPbBr3 synthesized at room temperature (RT) and 15 compare their performance with those prepared by a traditional hot injection (HI) method.We 16 provide insights into the morphology, optoelectronic properties of RT PeNPs via atomic force 17 and transmission electron microscopy and employing them in LEDs. 18 19
Partial Homomorphic Encryption Schemes and their applications

Homomorphic encryption schemes are being explored to be used in applications where highly sensitive data needs to be protected while maintaining the utility of the data to be computed in cloud applications. The efficient ElGamal scheme is studied for its partial homomorphic multiplication property. The multiplicative ElGamal scheme is used in a cryptographic protocol that hides users’ precise private location data as it is being computed on a cloud server. The modification to the ElGamal scheme transforms the multiplicative ElGamal scheme to an additive ElGamal scheme with addition and scalar multiplication capabilities. The additive ElGamal scheme is used in a secure comparison protocol. An open source framework, that implements homomorphic primitives, including the multiplicative and additive ElGamal schemes, is developed with C++ language and the FLINT number theory library, to ensure a high efficiency in carrying out homomorphic operations and supporting applications that use homomorphic operations.
SYNTHETIC FOCUSING TECHNIQUE FOR LOW-FREQUENCY GUIDED WAVES INSPECTION OF PIPELINES USED ANTENNA ARRAY

Introduction In recently years more and more are raising the application of Low-frequency guided wave (GW) testing, as more preferred and more cost effective method for thickness testing of pipelines. With application is developed post processing technique of acquisition data from equipment with antenna array [1 and 2], as wall application of active focusing technique [3]. Application of GW for pipe inspection together with active focusing technique and post-processing tool requires significant knowledge for generated ultrasonic beam in pipeline and there interaction with different type and position discontinuities. The purpose of the work: to determine the effect of antenna array and pipeline properties to reflected signal from pipeline end when used post-processing technique with unfocused and active focusing technique.
The Importance of Biopsy and FNAC as A Diagnostic Tool in Cervical Lymphadenopathy Cases

Original Research Article Objective: In this study our main goal is to evaluate the importance of biopsy and FNAC as a diagnostic tool in cervical lymphadenopathy cases. Method: This cross-sectional analytical study was done Total 260 patients with cervical lymphadenopathy, persisting for >2 weeks either localized or generalized attending inpatient and outpatient department (particularly surgical, medical, pediatrics, ENT, dermatology) of Dhaka Medical College Hospital, from June 2014 to July 2015. Results: The peak age incidence of cervical lymphadenopathy was observed between 2 nd and 3 rd decade of life (25.4% in 10 – 20 years and 25% in 20 – 30 years). Another peak was found in 50 years or above. The median age was 28 years and the lowest and highest ages were 5 and 66 years respectively.54% of patients were diagnosed clinically as having tubercular lymphadenitis, 27.7% metastatic carcinoma, 12.7% lymphoma and 5.0% non-specific reactive hyperplasia (NSRH). Conclusion: From our result, we can conclude that, diagnosis of lymphadenopathy is a team effort of the physician surgeon and the pathologist. If there is no regression in size or size increases, open biopsy can used for diagnosis in cervical lymphadenopathy cases.
S TABILIZER : Enforcing Predictable and Analyzable Performance

Modern architectures have made program behavior brittle and unpredictable, making software performance highly dependent on its execution environment. Even apparently innocuous changes, such as changing the size of an unused environment variable, can—by altering memory layout and alignment—degrade performance by 33% to 300%. This unpredictability makes it difﬁcult for programmers to debug or understand application performance. It also greatly complicates the evaluation of performance optimizations, since slight changes in the execution environment can have a greater impact on performance than a typical optimization. We present S TABILIZER , a compiler and runtime system that enforces reliable performance. By comprehensively randomizing the placement of functions, stack frames, and heap objects in memory, S TABILIZER provides predictable performance with high probability. Random placement makes bad layouts unlikely, and re-randomization ensures they are short-lived when they do occur. We demonstrate that S TABILIZER effectively eliminates measurement bias with minimal overhead, allowing it to be used in deployment to ensure predictable performance. In addition, S TABILIZER enables statistically rigorous performance evaluation. We demonstrate its use by testing the effectiveness of standard optimizations used in the LLVM compiler; we ﬁnd that, across the SPEC CPU2000 and CPU2006 benchmark suites, the effect of the -O3 optimization level is indistinguishable from noise.
Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations

We present Chirpy Cardinal, an open-domain dialogue agent, as a research platform for the 2019 Alexa Prize competition. Building an open-domain socialbot that talks to real people is challenging - such a system must meet multiple user expectations such as broad world knowledge, conversational style, and emotional connection. Our socialbot engages users on their terms - prioritizing their interests, feelings and autonomy. As a result, our socialbot provides a responsive, personalized user experience, capable of talking knowledgeably about a wide variety of topics, as well as chatting empathetically about ordinary life. Neural generation plays a key role in achieving these goals, providing the backbone for our conversational and emotional tone. At the end of the competition, Chirpy Cardinal progressed to the finals with an average rating of 3.6/5.0, a median conversation duration of 2 minutes 16 seconds, and a 90th percentile duration of over 12 minutes.