Miracle-dz/UniFAR-FTUs huggingface dataset:
Tax Me, But Spend Wisely? Sources of Public Finance and Government Accountability

Existing evidence suggests that extra grant revenues lead to little improvements in public services in developing countries - but would governments spend tax revenues differently? This paper considers a program that invests in the tax capacity of Brazilian municipalities. Using variations in the timing of program uptake I find that it raises local tax revenues and that the increase in taxes is used to improve both the quantity and quality of municipal education infrastructure. In contrast increases in grants over which municipalities have the same discretion as over taxes have no impact on any measure of local public infrastructure. These results suggest that the way governments are financed matters: governments spend increases in tax revenues more towards expenditures that benefit citizens than increases in grant revenues.
The dark side of agile software development

We believe, that like most innovations, Agile has followed the Gartner Hype Cycle and it has now reached the Trough of Disillusionment, where it is currently stuck. Moreover, we believe this is due to a "guru phenomenon. " However, we think that Agile can make a step forward. Our experience lead us to the conviction that through the application of a suitable quality improvement paradigm Agile will be able to reach what Gartner's experts call the Slope of Enlightenment and eventually the Plateau of Productivity.
Scalable Computing: Practice and Experience

Increasing number of vehicles on the roads caused the increase of popularity of GPS devices that the drivers can install in their cars. Efficient vehicle routing is very significant task nowadays, as the number of vehicles on the roads is growing rapidly. As many drivers have an ability use a computer while planning their itinerary, they need to have an application to find the best route for them. The paper describes a new approach for path finding problem. The proposition of solving the path finding problem with the use of multi-agent system is proposed. The idea of multi-agent system includes cooperation between autonomous software agents to complete a certain task.
Capital Mobility and Reform

Financial globalization is commonly viewed as a powerful force in constraining or disciplining domestic policies. This paper presents a model that captures various ways in which international capital mobility affects domestic policy incentives. Capital mobility supports reform in two ways: 1) capital inflows enhance the benefits of good policies; 2) liberalizing capital outflows may lock in political support for reforms. On the downside, capital mobility makes possible self-fulfilling capital flight that destroys the domestic investor basis and the political support for reform. More generally, individual investment decisions do not internalize their impact on policy incentives, opening some scope for second-best public intervention.
Lower bounds for restricted-use objects: extended abstract

Concurrent objects play a key role in the design of applications for multi-core architectures, making it imperative to precisely understand their complexity requirements. For some objects, it is known that implementations can be significantly more efficient when their usage is restricted. However, apart from the specific restriction of one-shot implementations, where each process may apply only a single operation to the object, very little is known about the complexities of objects under general restrictions. This paper draws a more complete picture by defining a large class of objects for which an operation applied to the object can be "perturbed" L consecutive times, and proving lower bounds on the time and space complexity of deterministic implementations of such objects. This class includes bounded-value max registers, limited-use approximate and exact counters, and limited-use collect and compare-and-swap objects; L depends on the number of times the object can be accessed or the maximum value it supports. For implementations that use only historyless primitives, we prove lower bounds of Omega(min(log L, n)) on the worst-case step complexity of an operation, where n is the number of processes; we also prove lower bounds of Omega( min( L, n )) on the space complexity of these objects. When arbitrary primitives can be used, we prove that either some operation incurs Omega( min( log L, n)) memory stalls or some operation performs Omega( min( log L, n)) steps. In addition to these deterministic lower bounds, the paper establishes a lower bound on the expected step complexity of restricted-use randomized approximate counting in a weak oblivious adversary model.
A fast, effective local search for scheduling independent jobs in heterogeneous computing environments

The efficient scheduling of independent computational jobs in a heterogeneous computing (HC) environment is an important problem in domains such as grid computing. Finding optimal schedules for such an environment is (in general) an NP-hard problem, and so heuristic approaches must be used. Work with other NP-hard problems has shown that solutions found by heuristic algorithms can often be improved by applying local search procedures to the solution found. This paper describes a simple but effective local search procedure for scheduling independent jobs in HC environments which, when combined with fast construction heuristics, can find shorter schedules on benchmark problems than other solution techniques found in the literature, and in significantly less time.
A role for synGAP in regulating neuronal apoptosis

The brain‐specific Ras/Rap GTPase‐activating protein synGAP is a major component of the postsynaptic density at glutamatergic synapses. It is a target for phosphorylation by Ca2+/calmodulin‐dependent protein kinase II, which up‐regulates its GTPase‐activating activity. Thus, SynGAP may play an important role in coupling N‐methyl‐d‐aspartate‐type glutamate receptor activation to signaling pathways downstream of Ras or Rap. Homozygous deletion of synGAP is lethal within the first few days after birth. Therefore, to study the functions of synGAP, we used the cre/loxP recombination system to produce conditional mice mutants in which gradual loss of synGAP begins at ∼ 1 week, and usually becomes maximal by 3 weeks, after birth. The resulting phenotypes fall into two groups. In a small group, the level of synGAP protein is reduced to 20–25% of wild type, and they die at 2–3 weeks of age. In a larger group, the levels remain higher than ∼ 40% of wild type, and they survive and remain healthy. In all mutants, however, an abnormally high number of neurons in the hippocampus and cortex undergo apoptosis, as detected by caspase‐3 activation. The effect is cell autonomous, occurring only in neuronal types in which the synGAP gene is eliminated. The level of caspase‐3 activation in neurons correlates inversely with the level of synGAP protein measured at 2 and 8 weeks after birth, indicating that neuronal apoptosis is enhanced by reduction of synGAP. These data show that synGAP plays a role in regulation of the onset of apoptotic neuronal death.
Effect of Homocysteine-Lowering Treatment With Folic Acid and B Vitamins on Risk of Type 2 Diabetes in Women

OBJECTIVE Homocysteinemia may play an etiologic role in the pathogenesis of type 2 diabetes by promoting oxidative stress, systemic inflammation, and endothelial dysfunction. We investigated whether homocysteine-lowering treatment by B vitamin supplementation prevents the risk of type 2 diabetes. RESEARCH DESIGN AND METHODS The Women's Antioxidant and Folic Acid Cardiovascular Study (WAFACS), a randomized, double-blind, placebo-controlled trial of 5,442 female health professionals aged ≥40 years with a history of cardiovascular disease (CVD) or three or more CVD risk factors, included 4,252 women free of diabetes at baseline. Participants were randomly assigned to either an active treatment group (daily intake of a combination pill of 2.5 mg folic acid, 50 mg vitamin B6, and 1 mg vitamin B12) or to the placebo group. RESULTS During a median follow-up of 7.3 years, 504 women had an incident diagnosis of type 2 diabetes. Overall, there was no significant difference between the active treatment group and the placebo group in diabetes risk (relative risk 0.94 [95% CI 0.79–1.11]; P = 0.46), despite significant lowering of homocysteine levels. Also, there was no evidence for effect modifications by baseline intakes of dietary folate, vitamin B6, and vitamin B12. In a sensitivity analysis, the null result remained for women compliant with their study pills (0.92 [0.76–1.10]; P = 0.36). CONCLUSIONS Lowering homocysteine levels by daily supplementation with folic acid and vitamins B6 and B12 did not reduce the risk of developing type 2 diabetes among women at high risk for CVD.
Reduced outage probability relay selection for underlay cognitive networks

In underlay cognitive networks, the unlicensed (secondary) user is allowed to share the spectrum with the licensed (primary) user under the constraint that the interference at the primary user should be below a specific threshold. This constraint forces the cognitive network to apply power control techniques, which typically result in limited transmission power and hence limited coverage area. As a solution to reach the intended far destinations, relaying techniques can be used to improve the performance of underlay cognitive networks in terms of signal-to-noise ratio (SNR). Recently, single best relay selection schemes have been proposed that maintain a desired SNR for the cognitive network while satisfying the interference level at the primary network. However, these schemes suffer from high outage probability especially at low SNR, where the probability of finding a single relay that satisfies both constraints is reduced. Therefore, in this paper, we propose a multiple relay selection scheme, where at each channel realization, we allow for multiple relay selection in case the best relay, among those that satisfy the interference constraint, does not satisfy the desired SNR. In particular, we select the least number of relays whose sum of their individual SNR's achieves the desired level. This scheme leads to a reduced outage probability especially for low SNR. We derive a closed form expression for the cumulative density function (CDF) of the selected relay(s) SNR for a certain number of relays. Simulation results confirm the analytical results and show that the proposed relay(s) selection algorithm in an underlay cognitive environment improves the outage probability and symbol error rate (SER) in low SNR regions.
Formation flight using multiple Integral Backstepping controllers

In this paper, a new approach for the formation control of a group of UAVs is presented. The proposed method is based on a combination of multiple Integral Backstepping (IB) controllers. The paper considers a group of quadrotor UAVs, each having an identical nonlinear dynamics. The stability of the formation flight is shown using the Lyapunov approach. The main contribution of the paper stems from the proposed combination of individual controllers, where each individual controller satisfies a reference configuration between two UAVs. The combination of all individual controllers provides the total force and moments required, in each UAV, for the stability of the formation.
A Point Sets Smoothing Algorithm Using Curvature Flow

We present a method for anisotropic fairing of point sets, which based on the covariance analysis and the efficiently constructed curvature. We use principal curvatures to detect features such as edges. Anisotropic curvature flow allows prominent surface features and other details of the objects to be treated in different ways. It is able to retain and even enhance important features such as edges and corners on the surface. We define such a diffusion flow which allows the point moving along the normal with a speed equal to the curvature. Since the point is moved along the normal direction, the proposed curvature flow will not introduce undesirable points drifting over the surface.
Computer-Aided Diagnosis of Speech Disorder Signal in Parkinson’s Disease

Computer-aided diagnosis (CAD) can be used as a decision support system by physicians in the diagnosis and treatmentof disordered speech especially those who specialize in neurophysiology diseases. Parkinson's disease (PD) is aprogressive disorder of the nervous system that affects movement. It develops gradually, sometimes starting with a barelynoticeable tremor in speech. It has been found that 80% of persons with PD reported speech and voice disorders.Parkinson's disease symptoms worsen as the condition progresses over time. Therefore, Speech may become soft orslurred and these deficits in speech intelligibility impact on health status and quality of life. Different researchers arecurrently working in the analysis of speech signal of people with PD, including the study of different dimensions in speechsuch as phonation, articulation, prosody, and intelligibility. Here, we present the characteristics and features of normalspeech and speech disorders in people with PD and the types of classification for implementation of the efficacy oftreatment interventions. The results show that our classification algorithm using ANN is outperformed KNN and SVM. ANNis a practical and useful as a predictive tool for PD screening with a high degree of accuracy, approximately 96.1% of acorrect detection rate (sensitivity 94.7%, and specificity 96.6%). Based on the high levels of accuracy obtained by ourproposed algorithm, it can be used for enhancing the detection purpose to discriminate PD patients from healthy people.Our algorithm may be used by the clinicians as a tool to confirm their diagnosis.
Website quality assessment for portal hospital Indonesia using Gap Analysis

The purpose of this study is to measure the staff medical expectations in one of the hospital in Jakarta towards the Portal Hospital Indonesia (PHI) website. The expectations are measured by the dimensions of the website, from the contents, the navigations, the structure and design, the appearance and multimedia, and the uniqueness of the website. Those dimensions are used based on previous study that has been conducted by other researcher about the website quality assessment. The research was conducted at one of the hospital in Jakarta. The sample of this study are the medical staff of the chosen hospital. After the data was gathered, Gap Analysis methodology was conducted. Gap Analysis is a methodology to find the gap between two components. In this case, the methodology is used to find the gap between the current Portal Hospital Indonesia website quality and the medical staff expectations of one hospital in Jakarta. Using gap analysis, some weaknesses of the Portal Hospital Indonesia website which is still under the medical staff expectations were revealed.
Isolation and identification of a novel, lipase-producing bacterium, Pseudomnas aeruginosa KM110

Background and Objectives Lipases are particularly important due to the fact that they specifically hydrolyze acyl glycerol, oils and greases, which is of great interest for different industrial applications. Materialst and Methods In this study, several lipase-producing bacteria were isolated from wastewater of an oil processing plant. The strain possessing the highest lipase activity was identified both biochemically and sequencing of 16S rRNA gene. Then we increase lipase activity by improving conditions of production medium. Also, lipase from this strain was preliminarily characterized for use in industrial application. Results The 16S rRNA sequensing revealed it as a new strain of Pseudomonas aeruginosa and the type strain was KM110. An overall 3-fold enhanced lipase production (0.76 U mL−1) was achieved after improving conditions of production medium. The olive oil and peptone was found to be the most suitable substrate for maximum enzyme production. Also the enzyme exhibited maximum lipolytic activity at 45°C where it was also stably maintained. At pH 8.0, the lipase had the highest stability but no activity. It was active over a pH range of 7.0–10.0. The lipase activity was inhibited by Zn2+ & Cu2+ (32 and 27%, respectively) at 1mM. The enzyme lost 29% of its initial activity in 1.0% SDS concentration, whereas, Triton X-100, Tween-80 & DMSO did not significantly inhibit lipase activity. Conclusions Based on the findings of present study, lipase of P. aeruginosa KM110 is a potential alkaline lipase and a candidate for industrial applications such as detergent, leather and fine chemical industries.
Somatosensory computation for man-machine interface from motion-capture data and musculoskeletal human model

We discuss the computation of somatosensory information from motion-capture data. The efficient computational algorithms previously developed by the authors for multibody systems, such as humanoid robots, are applied to a musculoskeletal model of the human body. The somatosensory information includes tension, length, and velocity of the muscles, tension of the tendons and ligaments, pressure of the cartilages, and stress of the bones. The inverse dynamics of the musculoskeletal human model is formulated as an optimization problem subject to equality and inequality conditions. We analyzed the solutions obtained by linear and quadratic programming methods, and showed that linear programming has better performance. The technological development aims to define a higher dimensional man-machine interface and to open the door to the cognitive-level communication of humans and machines.
The Efficient Features for Tracking

In computer vision, optical flow is very useful in tracking objects from frame to frame. The well-known KLT (Kanade-Lucas-Tomasi) of the differential method can trace local features through a generalized affine transform explained by six parameters. Since most of the distortion of the local patch between frames can be explained by four factors (horizontal and vertical translation, scaling and rotation), we present a tracking method with four parameters in this paper. The advantages of our method are that it has lower complexity than KLT and calculates the values of the four parameters directly. In this experiment, we show the four estimated factors in a virtual scene and track local features in a real scene. As a result, despite reducing the parameters, the proposed method performs very well for feature tracking and can track local features using only four parameters.
Rapid analysis of interprocessor communications on heterogeneous system architectures via parallel cache emulation

The recently proposed heterogeneous system architecture (HSA) specifications enable shared-memory-based interprocessor communications between CPU cores and GPU cores via a flat coherent address space and memory-based signals to reduce explicit data copy overheads. Since modern CPU/GPU cores are often designed with distributed caches, the interprocessor communications occur implicitly in the form of coherence traffics among the distributed caches and are hardly noticed by the programmers. Although existing cache simulators such as GEMS can help reveal the coherence traffics, they are extremely slow for large systems, where reducing interprocessor communications is often key to performance optimization. This paper proposes a framework with end-to-end parallel emulation schemes to speed up the analysis of interprocessor communications for large-scale HSA applications. We developed multithreaded distributed cache analysis schemes and integrated them into HSAemu, an open-source, multithreaded full-system emulator, to form a high-speed execution-driven analysis framework to assist software optimization and early-stage architectural development. As a proof of concept, experimental results with OpenCL benchmark programs show that the proposed scheme delivered scalable performance and outperformed GEMS by 3.5 times with 4 threads.
A Hybrid Bootstrapping Approach for developing Odiya Named Entity Corpora from Wikipedia

Named Entity Recognition (NER) is considered as very influential undertaking in natural language processing appropriate to Question Answering system, Machine Translation (MT), Information extraction (IE), Information Retrieval (IR) etc. Basically NER is to identify and classify different types of proper nouns present inside given file like location name, person name, number, organization name, time etc. Although huge amount of progress is made for different Indian languages, NER is still a big problem for Odiya Language. Odiya is also a resource constrained language and till today, this is very tough to find out a large and accurate corpus for training and test. Therefore in this paper, we have utilized Wikipedia to develop a huge Odiya corpus of annotated name entities which is quite efficient to be training dataset further. After evaluation, we have got a very promising result with a F-score of 78.89.
VEGETATION SPECIES IDENTIFICATION USING HYPERSPECTRAL IMAGERY AND A PROGRESSIVE ANALYSIS

The development of hyperspectral remote sensing provides an opportunity to considerably improve the accuracy of vegetation species classification, because the fine spectral resolution of hyperspectral remote sensing data offers the potential to discriminate between species with subtle spectral signature differences. The high spectral resolution, on the other hand, makes the hyperspectral data highly redundant and poses great challenges in developing methodologies suited for vegetation identification. Without proper approaches to dealing with the high redundancy of hyperspectral data, important characteristics of a vegetation cover may be lost or submerged by other insignificant information which co-exists in the hyperspectral data, and thus classification accuracy may be even deteriorated. It is well recognized that using a smaller number of spectral bands can probably produce better classification accuracies than the use of all bands. As a result, feature selection including band selection is very important for vegetation cover classification using hyperspectral data as well. The commonly used approaches to represent the data by a few basic components include principal component analysis (PCA) [1] and its variants, and the minimum noise fraction (MNF) transformation [2]. The basic assumption for these methods is that remote sensing signal is stationary and ergodic across the whole image, which is not always realistic [3]. In this study, an advanced method was proposed to extract spectral features progressively from individual reflectance spectrum.
Towards merging common and technical lexicon wordnets

The growing amount of available information and the growing importance given to the access to technical information enhance the potential role of NLP applications in enabling users to deal with information for a variety of knowledge domains. In this process, lexical resources are crucial. Using and comparing already existent wordnets for common and technical lexica, we set up a basis for integrating these resources without losing their specific information and properties. We demonstrate their compatibility and discuss strategies to overcome the issues arrising in their merging, namely aspects concerning conceptual variation, subnet and synset merging, and the incorporation of technical and non-technical information in definitions. As we are using models of the lexicon that mirror the organization of the mental lexicon, the accomplishment of this goal can provide insights on the type of relations holding between common lexical items and terms. Also, the results of integrating such resources can contribute to the better intercommunication between experts and non-experts, and provide a useful resource for NLP, particularly for tools simultaneously serving specialist and non-specialist publics.