Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and equity with endogenous human capital: Taiwan's economic miracle revisited

This paper presents an endogenous growth model for a small open economy with a significant trade surplus and active government development strategies in order to reexamine the major determinants of economic growth and income distribution. This analysis provides a better interpretation for the intertwined relationship between growth and equity, an important economic issue that has not been fully addressed by the well-known models [5; 9; 20]. ' In traditional growth studies, economists have emphasized the role of two major factor inputs, physical capital and labor. Output growth is considered to depend merely on exogenous shifts in population and technology. Recently, Lucas points out that this conventional approach to studying economic growth may leave more than half of output growth unexplained [12]. In order to improve the understanding of the underlying endogenous forces promoting economic development, "new growth" theorists have proposed several alternatives to the conventional models, such as the endogenous fertility choice [4], the endogenous technological evolution [16], and the endogenous human capital accumulation or learning process [12; 13], to name but a few. These contributions have generated additional interests in, and rich implications for, empirical studies of public policy [6] and cross-country comparisons [3; 15]. Lucas's endogenous human capital formation model is particularly suitable for studying the
Grid Generation and Grid Conversion by Subdivision Schemes

In this paper we present new algorithms for optimal fitting with subdivision schemes. We use an iterative numerical scheme for solving the arising linear system for the least squares problem. This scheme avoids the explicit set up of the normal equations and the amount of work for one approximation step is proportional to the number of vertices of the subdivision surface. Together with this algorithms subdivision schemes can be used for modelling and grid generation in aeronautical projects. To make the schemes really usable for this purposes their rules have to be modified in such a way that the limit surfaces have the desired properties. Furthermore fast algorithms for evaluation and approximation of existing surfaces have to be developed.
The Impact of the Number of Participants on the Provision of a Public Good

Under constraints of Bayesian interim incentive compatibility and individual rationality, the paper characterizes second-best allocations for the provision of a public good. If benefit and cost functions do not depend on the number of participants, it is always beneficial to have more participants. As the number of participants becomes large, second-best of public-good provision converge in distribution to first-best levels if these levels are bounded. If public-good provision levels are potentially unbounded, with isoelastic benefit and cost functions, then, with positive probability, second-best provision levels become large in absolute terms, but, relative to first-best levels, they go to zero.
Blackboard content classification for lecture videos

In this paper, we propose a novel approach to understand the high level semantics of instructional video by identifying mid-level features from the lecture content. The lecture content in instructional videos can be divided into text, equations and figures. In unscripted lecture video, these visual contents can be useful visual cues to understand the high level semantics. For example, it could help us achieve efficient structuring and indexing of multimedia learning material. To understand the high level semantics from the content itself is however not a trivial task. To this end, we propose visual content classification system (VCCS) for multimedia lecture videos. We propose hybrid approach by combining support vector machine (SVM) and optical character recognition (OCR) to classify visual content into figures, text and equations. The initial results show overall classification accuracy above 85 percent.
NSOM/QD-Based Visualization of GM1 Serving as Platforms for TCR/CD3 Mediated T-Cell Activation

Direct molecular imaging of nanoscale relationship between T-cell receptor complexes (TCR/CD3) and gangliosidosis GM1 before and after T-cell activation has not been reported. In this study, we made use of our expertise of near-field scanning optical microscopy(NSOM)/immune-labeling quantum dots- (QD-)based dual-color imaging system to visualize nanoscale profiles for distribution and organization of TCR/CD3, GM1, as well as their nanospatial relationship and their correlation with PKCθ signaling cascade during T-cell activation. Interestingly, after anti-CD3/anti-CD28 Ab co-stimulation, both TCR/CD3 and GM1 were clustered to form nanodomains; moreover, all of TCR/CD3 nanodomains were colocalized with GM1 nanodomains, indicating that the formation of GM1 nanodomains was greatly correlated with TCR/CD3 mediated signaling. Specially, while T-cells were pretreated with PKCθ signaling inhibitor rottlerin to suppress IL-2 cytokine production, no visible TCR/CD3 nanodomains appeared while a lot of GM1 nanodomains were still observed. However, while T-cells are pretreated with PKCα β signaling inhibitor GÖ6976 to suppress calcium-dependent manner, all of TCR/CD3 nanodomains were still colocalized with GM1 nanodomains. These findings possibly support the notion that the formation of GM1 nanodomains indeed serves as platforms for the recruitment of TCR/CD3 nanodomains, and TCR/CD3 nanodomains are required for PKCθ signaling cascades and T-cell activation
Large Aggregates Are the Major Soluble Aβ Species in AD Brain Fractionated with Density Gradient Ultracentrifugation

Soluble amyloid-β (Aβ) aggregates of various sizes, ranging from dimers to large protofibrils, have been associated with neurotoxicity and synaptic dysfunction in Alzheimer's Disease (AD). To investigate the properties of biologically relevant Aβ species, brain extracts from amyloid β protein precursor (AβPP) transgenic mice and AD patients as well as synthetic Aβ preparations were separated by size under native conditions with density gradient ultracentrifugation. The fractionated samples were then analyzed with atomic force microscopy (AFM), ELISA, and MTT cell viability assay. Based on AFM appearance and immunoreactivity to our protofibril selective antibody mAb158, synthetic Aβ42 was divided in four fractions, with large aggregates in fraction 1 and the smallest species in fraction 4. Synthetic Aβ aggregates from fractions 2 and 3 proved to be most toxic in an MTT assay. In AβPP transgenic mouse brain, the most abundant soluble Aβ species were found in fraction 2 and consisted mainly of Aβ40. Also in AD brains, Aβ was mainly found in fraction 2 but primarily as Aβ42. All biologically derived Aβ from fraction 2 was immunologically discriminated from smaller species with mAb158. Thus, the predominant species of biologically derived soluble Aβ, natively separated by density gradient ultracentrifugation, were found to match the size of the neurotoxic, 80–500 kDa synthetic Aβ protofibrils and were equally detected with mAb158.
Emissivity retrievals from airborne infrared hyperspectral images coupled with visible to SWIR hyperspectral images

Emissivity extraction from hyperspectral infrared data is a challenge as it is a under-determined problem, and particularly with noisy data. A new method for emissivity retrieval dedicated to hyperspectral data that cover infrared as well as reflective spectral domains has been developed to overcome difficulties related to noise. The method is derived from the EARTH (surface Emissivity, temperature and Atmosphere Retrievals from Thermal infrared Hyperspectral image) algorithm [1], but takes advantage of the abundance of spectral information in the reflective domain, by including a classification step in the emissivity retrieval process. The attributes considered in this step are the first principal components of the reflective image (in radiance or reflectance units) that contain rich spectral information, and the brightness temperatures computed on the infrared image after spectral binning that give information on surface temperature. A k-means classification is carried out. Infrared spectral radiances are then averaged in each class and atmospheric compensation, based on neural networks followed by surface temperature / emissivity separation (TES), based on spectral smoothness is achieved. The benefits of the classification step are demonstrated on AHS data. Then the method is applied on simulated noisy data. The accuracy on emissivity is clearly improved when compared to results obtained without classification step.
Tourism demand forecasting with neural network models: different ways of treating information.

This paper aims to compare the performance of three different artificial neural network techniques for tourist demand forecasting: a multi-layer perceptron, a radial basis function and an Elman network. We find that multi-layer perceptron and radial basis function models outperform Elman networks. We repeated the experiment assuming different topologies regarding the number of lags used for concatenation so as to evaluate the effect of the memory on the forecasting results. We find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the importance of increasing the dimensionality for long-term forecasting.
Adequacy of Data for Characterizing Caller Behavior

increase of advanced service offered by cellular networks draws lots of interest from researchers to study the networks and phone user behavior. From the phone user's point of view, we are interested in learning caller behavior. In this paper, we characterize caller behavior using probabilistic models based on caller's call arrival, inter-arrival, and talk time from the call logs. A probabilistic model is generally used to predict or estimate the future observation which is conditioned by a knowledge of the historical data. The question is how much historical data is adequate? We answer this question by presenting a technique to detect and compute the adequate amount of historical data to capture the caller behavior. In fact, this adequate amount of historical data is proved to be more relevant to the future caller behavior than considering the entire historical data and hence useful for constructing a predictive model for caller behavior. In addition, we show the improvement in the performance of a Call Predictor (16) when applying adequacy of data. For our analysis, we use the real-life call logs of 94 mobile users collected at MIT over nine months by the Reality Mining Project group. This paper extends our understanding of caller behavior. We believe that the results are useful in constructing a predictive model of a time series.
Says who? On the treatment of speech attributions in discourse structure

In this paper, we present what we think is an elegant solution to some problems in the discourse-structural modelling of speech attribution. Using mostly examples from the Wall Street Journal Corpus, we show that the approach proposed by Carlson and Marcu (2001) leads to irresolvable dilemmas that can be avoided with a suitable treatment of attribution in an underspecified representation of discourse structure. Most approaches to discourse structure assume that textual coherence can be modelled as trees. In particular, it has been shown that coherent discourse follows the so-called rightfrontier constraint (RFC), which essentially ascertains a hierarchical structure without crossed dependencies. We will discuss putative counterexamples to these two assumptions, most of which involve reported speech as in (1) (cited in Wolf and Gibson 2005): (1) “Sure I’ll be polite,” promised one BMW driver who gave his name only as Rudolph. “As long as the trucks and the timid stay out of the left lane. ” In (1) the second part of the quote should be linked to the first part (and not the whole first sentence) by a condition relation. If we were to analyse the parenthetical speech reporting clause (“promised one BMW driver .”) as the nucleus of its host clause (i.e., the quote), the RFC would prevent linkage between the two parts of the quote. If the attribution is analysed as a satellite of the quote, as in Carlson and Marcu (2001), Wolf and Gibson argue, it should be a satellite to both parts of the quote, thus violating treeness. In this paper, we will explore the problems arising from this type of construction and propose a treatment of speech report attributions that we will argue allows us to preserve both, treeness and the RFC in building discourse structures. 1 The (non-)treatment of speech attribution in classic Rhetorical Structure Theory (RST) In ‘classic’ Rhetorical Structure Theory (RST; Mann and Thompson 1988), the problems in accommodating speech report attributions do not arise, because classic RST does not separate complements of verbs and parenthetical speech reporting clauses from their host clause. Leaving speech attribution implicit is in line with the general ‘philosophy’ of RST, which aims to represent not all possible links, but the most plausible structure licensed by 1 Markus Egg is now at Humboldt University, Berlin. This manuscript is a slightly updated (2009) version of our paper in the Proceedings of the Workshop on Constraints in Discourse, Maynooth, Ireland 2006 (http://www.constraints-in-discourse.org/cid06/).
Influence of Body Mass Index on the Growth Hormone Response to Provocative Testing in Short Children without Growth Hormone Deficiency

Obesity and its related factors are known to suppress the secretion of growth hormone (GH). We aimed to evaluate the influence of body mass index (BMI) on the peak GH response to provocative testing in short children without GH deficiency. We conducted a retrospective review of medical records of 88 children (2-15 yr old) whose height was less than 3 percentile for one's age and sex, with normal results (peak GH level > 10 ng/mL) of GH provocative testing with clonidine and dopamine. Peak stimulated GH level, height, weight, pubertal status and serum IGF-1 level were measured. Univariate analysis showed that the BMI standard deviation score (SDS) correlated negatively with the natural log (ln) of the peak stimulated GH level (ln peak GH). BMI SDS did not correlate significantly with sex, age, pubertal status, or ln IGF-1 level. BMI SDS correlated negatively with ln peak GH level induced by clonidine but not by dopamine. In stepwise multivariate regression analysis, BMI SDS was the only significant predictor of ln peak GH level in the combination of tests and the clonidine test, but not in the dopamine test. In children without GH deficiency, BMI SDS correlates negatively with the peak GH level. BMI SDS should be included in the analysis of the results of GH provocation tests, especially tests with clonidine.
Stork: Package Management for Distributed VM Environments

In virtual machine environments each application is often run in its own virtual machine (VM), isolating it from other applications running on the same physical machine. Contention for memory, disk space, and network bandwidth among virtual machines, coupled with an inability to share due to the isolation virtual machines provide, leads to heavy resource utilization. Additionally, VMs increase management overhead as each is essentially a separate system. Stork is a package management tool for virtual machine environments that is designed to alleviate these problems. Stork securely and efficiently downloads packages to physical machines and shares packages between VMs. Disk space and memory requirements are reduced because shared files, such as libraries and binaries, require only one persistent copy per physical machine. Experiments show that Stork reduces the disk space required to install additional copies of a package by over an order of magnitude, and memory by about 50%. Stork downloads each package once per physical machine no matter how many VMs install it. The transfer protocols used during download improve elapsed time by 7X and reduce repository traffic by an order of magnitude. Stork users can manage groups of VMs with the ease of managing a single machine - even groups that consist of machines distributed around the world. Stork is a real service that has run on PlanetLab for over four years and has managed thousands of VMs.
An approach on identification of 802.11b devices by RF signature in wireless local area networks

In this work, a method on identification of transmitter by RF signature in order to enhance security in wireless local area networks where devices operates according to IEEE 802.11b standard is presented. In this scope, RF signatures of Wi-Fi devices are examined and identities of the devices are determined by designating the features of the devices by different classifiers. Also transmitter identity detection system based on RF signature is seen to be more secure than password applications.
An AR Interface to Enable Real-time Preview Design Variations in Actual Environment

In this paper, we propose a way to enable users to preview a modified version of objects in the real world with a mobile device's screen using techniques of augmented reality with live video. Here, we applied the methodology to develop a prototype system and an interface that enables users to modify fonts of designs of a poster put in an actual environment and preview it to reduce the problem referred to as "impression inconsistency. " From another point of view, this system uses an "interaction through video" metaphor. Tani et al. devised a technique to remotely operate machines by manipulating a live video image on a computer screen. Boring et al. applied it to distant large displays and mobile devices. Our system provides interaction with static, unintelligent targets such as posters and signs through live video.
Robust Parallel Filtering for Mobile Agent Tracking

In this paper we develop a robust method of target/mobile agent tracking involving two independent estimators with separate measurement systems. The outputs of the two estimators are combined using simple trigonometry (post-estimation data fusion) and provide a robust and reliable tracking path. We demonstrate that through the use of recent advances in robust set-value state estimation, our robust parallel filter approach performs well even when the individual filters do not. Brief comparisons with common data fusion methods are conducted in order to demonstrate the advantages of our parallel (post-estimation fusion) approach
Towards Comprehensible Control Flow in Visual Data Flow Languages

The use of graphics is a common technique for providing programmers with added information for program comprehension tasks. However, the development of visual programming languages has provided opportunities for programmers to use graphics directly within programming languages. In this paper we investigate the use of control flow notation within visual data flow programs. Our investigation is centered around the comprehensibility of boolean expressions that control the execution of data flow and how variations in these notations can effect the comprehension of programs. We report on a user study of visual boolean expressions and a design to improve the task of program comprehension.
Interventions to Increase Physical Activity Among Older Adults: A Meta-Analysis.

PURPOSE OF THE STUDY To determine the overall effectiveness of interventions designed to increase physical activity (PA) behavior among community-dwelling older adults. DESIGN AND METHODS Comprehensive literature searching identified eligible PA intervention studies among community-dwelling adults aged 65 and older, or sample mean age of 70. Diverse study characteristics were extracted and outcome data were duplicate coded. Overall mean effect sizes (ESs) were synthesized using a random-effects model. Heterogeneity of effects was analyzed using Q and I(2) statistics. Moderator analyses were conducted using meta-analytic analogues of ANOVA and regression for dichotomous and continuous moderators, respectively. RESULTS ESs were calculated from 13,829 primary study subjects. The overall mean ES for two-group posttest comparisons was 0.18 (95% CI 0.10-0.26, p < .001). This represents a difference of 620 steps/day or 73 min of PA/week between treatment and control groups. Significant moderators included the use of theory, how interventions were delivered, and cognitive plus behavioral-type intervention components. Non-significant moderators include the type of interventionist, delivery setting, and various measures of intervention dose. IMPLICATIONS PA interventions significantly improved PA behavior among community-dwelling older adults. Effective PA interventions may be efficiently delivered using already available resources and personnel. Future PA intervention research should be theoretically based, incorporate more diverse subjects, and compare intervention delivery methods.
CS 269 I : Incentives in Computer Science Lecture # 4 : Voting , Machine Learning , and Participatory Democracy ∗

Last lecture was all about strategyproof voting rules (and the lack thereof). Highlights included: the majority rule is strategyproof (for two alternatives); plurality, ranked-choice voting, and the Borda count all fail to be strategyproof; the Gibbard-Sattherwaite theorem states that no non-trivial voting is strategyproof; but sometimes by compromising and restricting the space of possible voter preferences, positive results can be recovered (like the median rule for single-peaked preferences). Strategyproofness is a very reasonable thing to worry about in political decisions, including the participatory democracy applications discussed in Section 5. But recall the other two computer science applications of voting that we mentioned last lecture — rank aggregation (e.g., of multiple heuristics ranking a set of Web pages by relevance) and crowdsourcing (e.g., aggregating the opinions of many Mechanical Turk workers about several different user interfaces). Is strategyproofness relevant here? Not really, since the voters don’t actually care personally about which outcome gets chosen. So in applications like these, what properties of voting rules should we focus on?
Network Coding and Quality of Service for Mobile Ad Hoc Networks

Network Coding is a relatively new forwarding paradigm where intermediate nodes perform a store, code, and forward operation on incoming packets. Traditional forwarding approaches, which employed a store and forward operation, have not been able to approach the limit of the max-flow min-cut throughput wherein sources transmitting information over bottleneck links have to compete for access to these links. With Network Coding, multiple sources are now able to transmit packets over bottleneck links simultaneously, achieving the max-flow min-cut through-put and increasing network capacity. While the majority of the contemporary literature has focused on the performance of Network Coding from a capacity perspective, the aim of this research has taken a new direction focusing on two Quality of Service metrics, e.g., Packet Delivery Ratio (PDR) and Latency, in conjunction with Network Coding protocols in Mobile Ad Hoc Networks (MANETs). Simulations are performed on static and mobile environments to determine a Quality of Service baseline comparison between Network Coding protocols and traditional ad hoc routing protocols. The results show that the Random Linear Network Coding protocol has the lowest Latency and Dynamic Source Routing protocol has the highest PDR in the static scenarios, and show that the Random Linear Network Coding protocol has the best cumulative performance for both PDR and Latency in the mobile scenarios.