Miracle-dz/UniFAR-FTUs huggingface dataset:
Constitutions and Economic Development: Evidence from the American Indian Nations

This paper presents an empirical examination of economic and institutional development. Utilizing a novel data set on American Indian tribal nations, we investigate how constitutional design affects economic development, while holding the broader legal and political environment fixed. Instrumental variables regressions, using the party of the US President at the time of the initial adoption of tribal constitutions as an instrument for constitutional design, indicate that parliamentary systems (versus presidential) have a strong positive effect on economic development, while ordinary least squares regressions of current economic outcomes on parliamentary systems of government show no effects. Robustness checks suggest that the results are not explained by differences in other institutions or geographic characteristics. Additional results provide some suggestive evidence that the effects may operate through channels that are typically associated with parliamentary systems, such as larger public employment, and more equitable income distribution.
An Improved Approach of Sending BSR and SR Based on MAC Layer in LTE System

The Buffer Status Report (BSR) and Scheduling Request (SR) are important procedures based on Medium Access Control (MAC) layer in Long Term Evolution (LTE) system. First, we study the BSR, SR and Semi-Persistent Scheduling (SPS) separately, then illustrate the priority of BSR and other data when sending MAC PDUs. The issue about the priority has been definitely defined by 3GPP, but it doesn't explain the reason, the article made a detailed analysis of it. The UE will send BSR and SR for gaining radio resources, the resources may be wasted if they exist at the same time. Finally we proposed a solution of deciding whether triggering BSR and SR in SPS and a solution of conflicts between padding BSR and other kinds of BSR.
Public Goods and Budget Deficit

We examine incentive-compatible mechanisms for fair financing and efficient selection of a public budget (or public good). A mechanism selects the level of the public budget and imposes taxes on individuals. Individuals’ preferences are quasilinear. Fairness is expressed as weak monotonicity (called scale monotonicity) of the tax imposed on an individual as a function of his benefit from an increased level of the public budget. Efficiency is expressed as selection of a Pareto-optimal level of the public budget. The budget deficit is the difference between the public budget and the total amount of taxes collected from the individuals. We show that any efficient scale-monotonic and incentive-compatible mechanism may generate a budget deficit. Moreover, it is impossible to collect taxes that always cover a fixed small fraction of the total cost.
Investigating visual feature extraction methods for image annotation

In order to investigate the performance of visual feature extraction method for automatic image annotation, three visual feature extraction methods, namely discrete cosine transform, Gabor transform and discrete wavelet transform, are studied in this paper. These three methods are used to extract low-level visual feature vectors from images in a given database separately, then these feature vectors are mapped to high-level semantic words to annotate images with labels in a given semantic label set. As it is more efficient to depict the visual features of an image by the feature distribution than to resort to image segmentation technology for semantic image blocks, this paper is going to find out which of the three feature extraction methods performs better in image annotation based on the distribution of feature vectors from the image. The performance of three different kinds of feature extraction method is fully analyzed, and it is found that discrete cosine transform method is more suitable for Gaussian mixture model in automatic image annotation.
Higher-order time frequency-based blind source separation technique

This letter considers the separation and estimation of independent sources from their instantaneous linear mixed observed data. Here, unknown source signals are estimated from their unknown linear mixtures using the strong assumption that the sources are mutually independent. In practice, separation can be achieved by using suitable second- or higher-order statistics. The authors propose a novel source separation technique exploiting fourth-order time frequency distributions. A computationally feasible implementation is presented based on joint diagonalization of the matrices of the principal slices of time-multifrequency domain of support of the cumulant-based Wigner trispectrums. A numerical example demonstrates the effectiveness of the proposed approach.
Circular-antenna-array-based codebook design and training method for 60GHz beamforming

Beamforming is necessary in 60GHz millimeterwave communications in order to compensate for high path loss. A complete beamforming algorithm includes codebook design and beam training. The existing beamforming protocol of IEEE 802.15. 3c standard has following flaws: (1) Not all three beamforming pattern types (quasi-omni pattern, sector and beam) have their own codebooks; (2) Almost every beam points to two directions, one of which is expected but the other one is unwanted; (3) Setup time of beam training is long. This paper proposes a codebook design and corresponding training procedure based on circular antenna array with a two-layer-structure. It allows every pattern type to own its corresponding codebook and highly directional antenna radiation pattern. The training setup time is reduced to around half of 3c training time. Performance evaluations also manifest that the proposed algorithm leads to less antenna gain loss and more robust performance than the 3c standard.
Joint prediction of observations and states in time-series : a partially supervised prognostics approach based on belief functions and KNN

Forecasting the future states of a complex system is a complicated challenge that is encountered in many industrial applications covered in the community of Prognostics and Health Management (PHM). Practically, states can be either continuous or discrete: Continuous states generally represent the value of a signal while discrete states generally depict functioning modes reflecting the current degradation. For each case, specific techniques exist. In this paper, we propose an approach based on case-based reasoning that jointly estimates the future values of the continuous signal and the future discrete modes. The main characteristics of the proposed approach are the following: 1) It relies on the K-nearest neighbours algorithm based on belief functions theory; 2) Belief functions allow the user to represent his partial knowledge concerning the possible states in the training dataset, in particular concerning transitions between functioning modes which are imprecisely known; 3) Two distinct strategies are proposed for states prediction and the fusion of both strategies is also considered. Two real datasets were used in order to assess the performance in estimating future break-down of a real system.
REV Hybrid Peptide Polyketide Natu Prospects toward Engin

The structural and catalytic similarities between modular nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) inspired us to search for hybrid NRPS PKS systems. By examining the biochemical and genetic data known to date for the biosynthesis of hybrid peptide polyketide natural products, we show (1) that the same catalytic sites are conserved between the hybrid NRPS PKS and normal NRPS or PKS systems, although the ketoacyl synthase domain in NRPS PKS hybrids is unique, and (2) that specific interpolypeptide linkers exist at both the Cand N-termini of the NRPS and PKS proteins, which presumably play a critical role in facilitating the transfer of the growing peptide or polyketide intermediate between NRPS and PKS modules in hybrid NRPS PKS systems. These findings provide new insights for intermodular communications in hybrid NRPS PKS systems and should now be taken into consideration in engineering hybrid peptide polyketide biosynthetic pathways for making novel ``unnatural'' natural products.
Self-Organizing and Self-Evolving Neurons: A New Neural Network for Optimization

A self-organizing and self-evolving agents (SOSENs) neural network is proposed. Each neuron of the SOSENs evolves itself with a simulated annealing (SA) algorithm. The self-evolving behavior of each neuron is a local improvement that results in speeding up the convergence. The chance of reaching the global optimum is increased because multiple SAs are run in a searching space. Optimum results obtained by the SOSENs are better in average than those obtained by a single SA. Experimental results show that the SOSENs have less temperature changes than the SA to reach the global minimum. Every neuron exhibits a self-organizing behavior, which is similar to those of the self-organizing map (SOM), particle swarm optimization (PSO), and self-organizing migrating algorithm (SOMA). At last, the computational time of parallel SOSENs can be less than the SA
A linear parameter variant H/sub /spl infin// controller design for a permanent magnet synchronous machine

A robust decoupling current multivariable controller for a permanent synchronous machine is designed using a linear parameter variant (LPV) of Hinfin control. This controller is scheduled with the rotor speed. Closed loop sensitivity functions analysis and simulation results evaluate the performance and the stability robustness of the resulting controller over all admissible PMSM operating range and under both unstructured disturbances related to the implementation and uncertainties in stator parameters
Automated border control: Problem formalization

This paper introduces a formalization of the Automated Border Control (ABC) machines deployed worldwide as part of the eBorder infrastructure for automated traveller clearance. Proposed formalization includes classification of the eBorder technologies, definition of the basic components of the ABC machines, identification of their key properties, establishment of metrics for their evaluation and comparison, as well as development of a dedicated architecture based on the assistant-based concept. Specifically, three generations of the ABC machines are identified: Gen-1 ABC machines which are biometric enabled kiosks, such as Canada's NEXUS or UK IRIS, to process low-risk pre-enrolled travellers; Gen-2 ABC machines which are eGate systems to serve travellers with biometric eID / ePassports; and Gen-3 ABC machines that will be working to support the eBorder process of the future. These ABC machines are compared in this paper based on certain criteria, such as availability of the dedicated architectural components, and in terms of the life-cycle performance metrics. This paper addresses the related problems of deployment and evaluation of the ABC technologies and machines, including the vulnerability analysis and strategic planning of the eBorder infrastructure.
English to Sanskrit Translator and Synthesizer (ETSTS)

The development of Machine Translation system for ancient language such as Sanskrit language is much more fascinating and challenging task. In the proposed algorithm we integrate traditional dictionary rule based approach for translation which translate source English sentence into target Sanskrit sentence. It has two models Text to Text Translator module and Text to speech synthesizer module. Due to morphological richness of Sanskrit language, this system uses morphological markings to identify Subject, Object, Verb, Preposition, Adjective, Adverb sentences. This paper presents English to Sanskrit approach for translating well-structured English sentences into well-structured Sanskrit sentences.
Pricing Digital Outperformance Options With Uncertain Correlation

Multi-asset options exhibit sensitivity to the correlations between the underlying assets and these correlations are notoriously unstable. Moreover, some of these options such as the digital outperformance options, have a cross-gamma that changes sign depending on the relative evolution of the underlying assets. In this paper, I present a model to price digital outperformance options when there is uncertainty about correlation, but it is assumed to lie within a certain range. Under the assumption that assets prices follow a Geometric Brownian motion with constant instantaneous volatilities I present an analytic expression for the price of the digital outperformance option under the constant correlation assumption, as well as the partial differential equation corresponding to the uncertain correlation model. The comparison of the prices obtained using both models shows that there is no constant correlation which allows attaining the price obtained under the uncertain correlation model. This fact shows that it can be dangerous to assume a constant instantaneous correlation for products with a cross-gamma that changes sign.
Alcohol Prices and Traffic Safety

How do alcohol beverage prices affect traffic fatalities? Economic theory predicts that alcohol consumption will be negatively related to price, and thus increases in price are expected, ceteris paribus, to reduce alcohol-related fatalities. Furthermore, price is an important policy variable, because it is affected by taxes and other policies, and -- for some beverages in some states -- price is actually set by alcohol control authorities. Schematically, the hypothesized relationships are: tax = > price = > consumption = > fatalities. While there is little dispute about the qualitative nature of these relationships, there is a wide range of quantitative estimates of the magnitudes involved at each step, and a further question about whether, taken together, the estimated magnitudes make sense. Many researchers in the United States have estimated reduced-form relationships based on state-level tax and fatality data, ignoring the intermediate relationships between taxes and prices, prices and consumption, and consumption and fatalities. Studies based on data from the 1970s and early 1980s often found a large, statistically significant negative relationship between state alcohol taxes and fatalities. However, several studies in the late 1990s failed to find significant relationships, and found that the estimates were sensitive to what other variables were included, or were implausible. A large number of studies have addressed the relationship between alcohol consumption and price, but only a few are focused on the high levels of intoxication associated with most alcohol-related fatalities (Simpson et al., 2004). The few studies that estimated a price-fatality relationship yielded inconsistent results. However, two recent studies have demonstrated that the failure to detect a robust and statistically significant relationship between beverage prices and fatalities may result from the poor quality of the available price data. Even after correcting for measurement error, however, substantial uncertainty remains about the true magnitude of price effects. Section II of this paper provides an overview of trends in U.S. traffic fatalities, alcohol consumption, and beverage pricing. Section III reviews a number of studies relating fatalities to beer taxes. Section IV considers whether the available tax or price data are better indicators of the price of alcohol. Section V discusses two recent studies utilizing price data and section VI presents conclusions.
Compromised Glutamate Transport in Human Glioma Cells: Reduction–Mislocalization of Sodium-Dependent Glutamate Transporters and Enhanced Activity of Cystine–Glutamate Exchange

Elevated levels of extracellular glutamate ([Glu]o) can induce seizures and cause excitotoxic neuronal cell death. This is normally prevented by astrocytic glutamate uptake. Neoplastic transformation of human astrocytes causes malignant gliomas, which are often associated with seizures and neuronal necrosis. Here, we show that Na+-dependent glutamate uptake in glioma cell lines derived from human tumors (STTG-1, D-54MG, D-65MG, U-373MG, U-251MG, U-138MG, and CH-235MG) is up to 100-fold lower than in astrocytes. Immunohistochemistry and subcellular fractionation show very low expression levels of the astrocytic glutamate transporter GLT-1 but normal expression levels of another glial glutamate transporter, GLAST. However, in glioma cells, essentially all GLAST protein was found in cell nuclei rather than the plasma membrane. Similarly, brain tissues from glioblastoma patients also display reduction of GLT-1 and mislocalization of GLAST. In glioma cell lines, over 50% of glutamate transport was Na+-independent and mediated by a cystine–glutamate exchanger (system xc−). Extracellularl-cystine dose-dependently induced glutamate release from glioma cells. Glutamate release was enhanced by extracellular glutamine and inhibited by (S)-4-carboxyphenylglycine, which blocked cystine–glutamate exchange. These data suggest that the unusual release of glutamate from glioma cells is caused by reduction–mislocalization of Na+-dependent glutamate transporters in conjunction with upregulation of cystine–glutamate exchange. The resulting glutamate release from glioma cells may contribute to tumor-associated necrosis and possibly to seizures in peritumoral brain tissue.
Theories on the Pathogenesis of Endometriosis

Endometriosis is a common, chronic inflammatory disease defined by the presence of extrauterine endometrial tissue. The aetiology of endometriosis is complex and multifactorial, where several not fully confirmed theories describe its pathogenesis. This review examines existing theories on the initiation and propagation of different types of endometriotic lesions, as well as critically appraises the myriad of biologically relevant evidence that support or oppose each of the proposed theories. The current literature suggests that stem cells, dysfunctional immune response, genetic predisposition, and aberrant peritoneal environment may all be involved in the establishment and propagation of endometriotic lesions. An orchestrated scientific and clinical effort is needed to consider all factors involved in the pathogenesis of this multifaceted disease and to propose novel therapeutic targets to reach effective treatments for this distressing condition.
Iwssip 2010 -17th International Conference on Systems, Signals and Image Processing Convergence of Augmented Reality and Scientific Visualization, and Its Application to Energy, Medicine and Sports

— What do we find in common among systems that seek to convey meaningful images to an oil reservoir interpreter, a medical doctor and an ordinary sports fan enjoying a broadcasted game on TV? They are generated by a system that processes captured signals and produces images conveying relevant information to the viewer. These processes are based on Computer Vision techniques to analyze the signal in order to predict forms and find features mainly to answer a " what, where and when " type of question. With such information, Virtual Reality techniques are used to produce meaningful images to the human observer. These systems can be understood as the convergence of the Augmented Reality and Scientific Visualization areas. This study presents some industry-demanded systems developed by the Tecgraf group which reflect this convergence.
Evidence on the Comparison of Telephone and Internet Surveys for Respondent Recruitment

Internet surveys have a potential use for survey research when compared against costs and declining response rates of traditional modes as they form a powerful tool for reducing respondents' burden in complex questionnaires. On the other hand, there exists scepticism about the reliability and robustness of the collected data. Arenze et al. (2005) argue that case studies involving Internet surveys cannot be generalised to other countries and have recommended systematic collection and reporting of experiences worldwide. Such studies have had limited exposure in the transport literature. This paper provides empirical evidence on the comparison between telephone and Internet surveys in the context of a car ownership study. The comparison between telephone and Internet modes focuses on performance measures such as response speed, response rates, survey costs, demographic profiles and geographical representation of the sample. The results indicate the cost effectiveness of Internet surveys. Moreover, they show that the time and cost for data collection significantly vary by sampling and recruitment method. Finally, Internet survey response rates are lower than those in the telephone interview, which implies that Internet surveys can only be used to complement traditional data collection methods.
Accuracy of Robot-Assisted Placement of Lumbar and Sacral Pedicle Screws: A Prospective Randomized Comparison to Conventional Freehand Screw Implantation

Study Design. Single-center prospective randomized controlled study. Objective. To evaluate the accuracy of robot-assisted (RO) implantation of lumbar/sacral pedicle screws in comparison with the freehand (FH) conventional technique. Summary of Background Data. SpineAssist is a miniature robot for the implantation of thoracic, lumbar, and sacral pedicle screws. The system, studied in cadaver and cohort studies, revealed a high accuracy, so far. A direct comparison of the robot assistance with the FH technique is missing. Methods. Patients requiring mono- or bisegmental lumbar or lumbosacral stabilization were randomized in a 1:1 ratio to FH or RO pedicle screw implantation. Instrumentation was performed using fluoroscopic guidance (FH) or robot assistance. The primary end point screw position was assessed by a postoperative computed tomography, and screw position was classified (A: no cortical violation; B: cortical breach <2 mm; C: ≥2 mm to <4 mm; D: ≥4 mm to <6 mm; E: ≥6 mm). Secondary end points as radiation exposure, duration of surgery/planning, and hospital stay were assessed. Results. A total of 298 pedicle screws were implanted in 60 patients (FH, 152; RO, 146). Ninety-three percent had good positions (A or B) in FH, and 85% in RO. Preparation time in the operating room (OR), overall OR time, and intraoperative radiation time were not different for both groups. Surgical time for screw placement was significantly shorter for FH (84 minutes) than for RO (95 minutes). Ten RO screws required an intraoperative conversion to the FH. One FH screw needed a secondary revision. Conclusion. In this study, the accuracy of the conventional FH technique was superior to the RO technique. Most malpositioned screws of the RO group showed a lateral deviation. Attachment of the robot to the spine seems a vulnerable aspect potentially leading to screw malposition as well as slipping of the implantation cannula at the screw entrance point.
Getting the last laugh: automatic laughter segmentation in meetings

Our goal in this work was to develop an accurate method to identify laughter segments, ultimately for the purpose of speaker recognition. Our previous work used MLPs to perform frame level detection of laughter using short-term features, including MFCCs and pitch, and achieved a 7.9% EER on our test set. We improved upon our previous results by including high-level and long-term features, median filtering, and performing segmentation via a hybrid MLP/HMM system with Viterbi decoding. Upon including the long-term features and median filtering, our results improved to 5.4% EER on our test set and 2.7% EER on an equal-prior test set used by others. After attaining segmentation results by incorporating the hybrid MLP/HMM system and Viterbi decoding, we had a 78.5% precision rate and 85.3% recall rate on our test set. To our knowledge these are the best known laughter detection results on the ICSI Meeting Recorder Corpus to date.