Miracle-dz/UniFAR-FTUs huggingface dataset:
An Empirical Comparison of Systems of Demand Equations for Tourist Expenditures in Resort Destinations

In this paper, we employ the systems approach to the estimation of demand equations. We model visitor expenditures on six different categories of goods at a major resort destination,Hawaii.This study breaks new ground in several respects: (a) we apply systems estimation techniques to a new area -- detailed budget data on visitor expenditures at a given resort destination, (b) we compare elasticities generated by the linear expenditure system and the Rotterdam model with the almost ideal demand system, a new functional form that has not been extensively tested empirically, and (c) we improve on a method suggested by Parks to measure goodness of fit in the Rotterdam model.
A case of bilateral high division of the sciatic nerves, together with a unilateral unusual course of the tibial nerve

In a 62-year-old male cadaver, high division of the sciatic nerve was observed bilaterally. Additionally, on the right side of the same cadaver, the common peroneal nerve passed just inferior to the piriformis muscle and the tibial nerve emerged inferior to the gemellus superior, between the gemellus superior and obturator internus muscles. Then, both of the nerves coursed posterior to the obturator internus, gemellus inferior and quadratus femoris muscles. The gemellus superior muscle, lying just posterior to the tibial nerve may cause to the symptoms of sciatica, because of the compression of the tibial nerve between the gemellus superior and obturator internus muscles. This pathology may lead to a new syndrome; the gemellus superior syndrome, just like the piriformis syndrome. As a conclusion, in the etiology and pathogenesis of sciatica, in addition to the priformis muscle, the abnormalities of the other gluteal external rotator muscles of the hip joint must also be taken into consideration by the clinicians. MR imaging of this region will be very helpful for the accurate diagnosis of this type of pathologies.
Error assessment in a soil acidification modelling study: efficiency issues and change of support

The soil acidification model SMART2 requires 25 input variables for each point support location it is run. For the regional modelling of soil acidification, the model is run at a dense grid of point locations, and point support model output (aluminium concentration below the root zone) is spatially aggregated to values for 10 km × 10 km blocks. Monte Carlo analysis was used to assess the uncertainty in model output due to uncertainty in model input variables. Spatial correlation of input variables had to be incorporated to get realistic values for the uncertainty in block aggregated model output. To increase the efficiency of the Monte Carlo analysis, Latin hypercube sampling of Gaussian random fields was used. For several sample sizes the efficiency of Latin hypercube sampling is compared to simple random (iid) sampling.
Near-Optimal Target Learning With Stochastic Binary Signals

We study learning in a noisy bisection model: specifically, Bayesian algorithms to learn a target value V given access only to noisy realizations of whether V is less than or greater than a threshold theta. At step t = 0, 1, 2, . , the learner sets threshold theta t and observes a noisy realization of sign(V - theta t). After T steps, the goal is to output an estimate V^ which is within an eta-tolerance of V . This problem has been studied, predominantly in environments with a fixed error probability q V, and there is little known when this happens. We give a pseudo-Bayesian algorithm which provably converges to V. When the true prior matches our algorithm's Gaussian prior, we show near-optimal expected performance. Our methods extend to the general multiple-threshold setting where the observation noisily indicates which of k >= 2 regions V belongs to.
Repression of FLOWERING LOCUS C and FLOWERING LOCUS T by the Arabidopsis Polycomb Repressive Complex 2 Components

Polycomb group (PcG) proteins are evolutionarily conserved in animals and plants, and play critical roles in the regulation of developmental gene expression. Here we show that the Arabidopsis Polycomb repressive complex 2 (PRC2) subunits CURLY LEAF (CLF), EMBRYONIC FLOWER 2 (EMF2) and FERTILIZATION INDEPENDENT ENDOSPERM (FIE) repress the expression of FLOWERING LOCUS C (FLC), a central repressor of the floral transition in Arabidopsis and FLC relatives. In addition, CLF directly interacts with and mediates the deposition of repressive histone H3 lysine 27 trimethylation (H3K27me3) into FLC and FLC relatives, which suppresses active histone H3 lysine 4 trimethylation (H3K4me3) in these loci. Furthermore, we show that during vegetative development CLF and FIE strongly repress the expression of FLOWERING LOCUS T (FT), a key flowering-time integrator, and that CLF also directly interacts with and mediates the deposition of H3K27me3 into FT chromatin. Our results suggest that PRC2-like complexes containing CLF, EMF2 and FIE, directly interact with and deposit into FT, FLC and FLC relatives repressive trimethyl H3K27 leading to the suppression of active H3K4me3 in these loci, and thus repress the expression of these flowering genes. Given the central roles of FLC and FT in flowering-time regulation in Arabidopsis, these findings suggest that the CLF-containing PRC2-like complexes play a significant role in control of flowering in Arabidopsis.
History and the Future of Scholarly Publishing

Over the past few years, discussions about scholarly publishing have been invariably preceded by the word “crisis. ” The university press community, research libraries, and the Modern Language Association (MLA) warn about deep and systemic problems that threaten the production of knowledge and the future careers of many junior faculty.1 Several of the factors that feed into this sense of crisis—the rising cost of serials, rising deficits at university presses, and increasing pressure on junior faculty to publish monographs—are already well known. But the actual evidence for a “crisis” often comes down to inference and anecdote. Digging further into the available data turns up a range of useful—albeit imperfect—information. Examining the evidence for the history field reveals why so many in the profession seem untroubled by the problems at university presses, but also provides ample cause for alarm among all who care about the future of the profession. Despite the alarm, history as a field appears quite successful at finding publishing outlets, as commercial publishers and university presses are producing an unprecedented number of history books. Yet there are significant disparities in the available publishing outlets for different regions and periods, particularly for work on earlier periods and regions outside the United States. While cloudy, future trends for the field as a whole seem quite alarming. As a discipline, history is particularly tied to the (flagging) health and welfare of university presses, which produce almost 50 percent of the new titles in the field (a good 10 percent higher than other humanities and social science fields, and more than twice the rate of many of the natural sciences). So as a result, their troubles are sure to become ours in due time. Their troubles arrive at a particularly inauspicious time, as a fast-growing cohort of junior faculty will be coming up for tenure in the next decade and running up against the increased reliance on monographs as a criterion for tenure. This suggests the need for greater care in the way we consider and describe the problems of today, and a certain urgency in addressing the problems of tomorrow.
Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis

Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression.
International Conference on Intelligent and Advanced Systems 2007 Text Independent Speaker Identification Using Gaussian Mixture Model Abstract— This Paper Describes Text-independent (ti) Speaker Identification (id) Using Gaussian Mixture Models (gmm). the Use of Gmm Approach Is Motivated by That th

I. INTRODUCTION There are numerous measurements and signals have been investigated for the use in biometric systems. Each has its advantages and disadvantages in term of accuracy and deployment. Speech signal, which conveys information about the identity of the speaker, has become compelling in biometric area. The advantage of voice biometrics is that firstly, speech is a natural signal to produce. Secondly, speech has been used as common communication medium in many applications (e.g. telephone transaction), so users can provide the signals conveniently. Besides, speech data acquisition is low-cost, using microphone and existing telephone systems without much extra installations.
In-Home Power Line Communications Local Area Network Based on Uniform Discrete Multitone Transceiver

Cyclic prefix based channel equalization employed in the Discrete Multitone (DMT) modulation offers the advantage of simplified implementation. However, this method has the disadvantage of amplifying channel noise for channels having deep nulls in the frequency response. The in-home power line channel is one such channel that has high noise content, in addition to deep frequency nulls. Enhancement of channel noise degrades bit error rate (BER), at the receiver. In order to improve the BER and the signal-to-noise ratio (SNR), for the in-home power line channel, a novel Uniform DMT transceiver is proposed. It divides the channel spectrum into uniform bandwidth sub-bands, and allocates variable power to each sub-band, according to the modified Fischer's power loading algorithm. The proposed Uniform DMT transceiver shows BER improvement in comparison with the conventional DMT system, for the in-home power line channel.
Feedback suppression in a mechanically coupled, short signal path sensor-actuator system for use as a hearing implant

We examine a 10:1 scale model of a recently proposed type of integrated sensor-actuator system to be used as part of a middle-ear hearing implant, and show that this inherently unstable system can be controlled by conventional methods of digital feedback suppression. Sensor and actuator of the model are mechanically coupled by a free-floating hard metal frame about 30 mm in length, corresponding to 3 mm original scale. Due to the direct mechanical coupling, the resulting electroacoustic system exhibits strong feedback and high-frequency oscillation will occur even at small gain. We show that the feedback of this system can be successfully controlled by delaying the signal in the forward path and then applying adaptive and active filtering. Through the use of a least-mean-square adaptive filter combined with active digital filtering, an increase in maximum stable gain (MSG) of up to 43 dB and a functional gain of up to 35 dB (maximum) and 24.7 dB (mean) are achieved.
Contextualized text explanations for visualizations

According to the multimedia design principle of spatial contiguity, presenting text explanations for visualizations within the image space improves the users' ability to make referential links between the text and its corresponding objects. In this paper we introduce a concept of Dual-Use of Image Space (DUIS) and we show how the concept presents text explanations for visualizations within the image space without obstructing the image. In DUIS the pixels are used both as shading information for the objects as well as text which can be read.The following are other benefits of DUIS: (1) It provides a mechanism to help user compare information for different objects with minimum cognitive burden (2) By using the same space for both the image and text the concept uses the screen real estate efficiently.
Successive iterative decoding of Reed Solomon codes using cryptographic hash codes as parity

Coding theory and Cryptography have common roots. Both the fields were introduced by Claude Shannon in his legendary work. The applications of both the fields are however quite different and therefore not significant research work has previously been done to investigate the connection between the both. In this work, those applications that require security in the form of cryptographic hash codes are considered and this cryptographic hash code is used as a means to improve the decoding results of concatenated Convolutional/Reed Solomon codes. Using the message digest, the results of concatenated decoding are enhanced and vice versa i.e. using the concatenated codes, the errors in the message digest are minimized. It is also demonstrated that a coding gain is achieved in both the cases.
Multiple Actor-Critic Structures for Continuous-Time Optimal Control Using Input-Output Data

In industrial process control, there may be multiple performance objectives, depending on salient features of the input-output data. Aiming at this situation, this paper proposes multiple actor-critic structures to obtain the optimal control via input-output data for unknown nonlinear systems. The shunting inhibitory artificial neural network (SIANN) is used to classify the input-output data into one of several categories. Different performance measure functions may be defined for disparate categories. The approximate dynamic programming algorithm, which contains model module, critic network, and action network, is used to establish the optimal control in each category. A recurrent neural network (RNN) model is used to reconstruct the unknown system dynamics using input-output data. NNs are used to approximate the critic and action networks, respectively. It is proven that the model error and the closed unknown system are uniformly ultimately bounded. Simulation results demonstrate the performance of the proposed optimal control scheme for the unknown nonlinear system.
[Sustainability of Brazilian policy for access to antiretroviral drugs].

OBJECTIVE The expense of acquiring antiretroviral drugs in Brazil has given rise to debate about the sustainability of the policy of universal access to AIDS medications, despite the evident benefits. The objective of this study was to analyze the evolution of the Ministry of Health's spending on acquiring antiretroviral drugs from 1998 to 2005, the determining factors and the medium-term sustainability of this policy (2006-2008). METHODS The study on the evolution of spending on antiretrovirals included analysis of their prices, the year-by-year expenditure, the number of patients utilizing the medication, the mean expenditure per patient and the strategies for reducing the prices maintained during this period. To analyze the sustainability of the policy for access to antiretrovirals, the cost of acquiring the drugs over the period from 2006 to 2008 was estimated, along with the proportion of gross domestic product and federal health expenditure represented by this spending. The data were collected from the Ministry of Health, the Brazilian Institute for Geography and Statistics (IBGE) and the Ministry of Planning. RESULTS The expenditure on antiretrovirals increased by 66% in 2005, breaking the declining trend observed over the period from 2000 to 2004. The main factors associated with this increase were the weakening of the national generics industry and the unsatisfactory results from the process of negotiating with pharmaceutical companies. CONCLUSIONS The Brazilian policy for universal access is unsustainable at the present growth rates of the gross domestic product, unless the country compromises its investments in other fields.
Exposure to Beta-(1,3)-D-Glucan in House Dust at Age 7–10 Is Associated with Airway Hyperresponsiveness and Atopic Asthma by Age 11–14

Background Mould exposure has been linked to childhood asthma and bronchial hyper-responsiveness. Few studies have assessed beta-(1,3)-d-glucan (beta-glucan), a significant fungal cell wall constituent, in relation to asthma in adolescence. Objective To determine whether house dust-derived beta-glucan exposure at age 7–10 is associated with the development and persistence of atopic and non-atopic asthma, and bronchial hyper-responsiveness (BHR) by age 11–14. Methods Dust samples were collected from the 1995 Study of Asthma, Genes, and Environment (SAGE) birth cohort. This cohort was derived from Manitoba provincial healthcare administrative records of children high and low risk for asthma. Samples were collected from the homes of 422 children at age 7–10 and analyzed using beta-glucan and endotoxin-specific Limulus Amoebocyte Lysate assays. Asthma, atopy, and BHR status of each child were also assessed at ages 7–10 and 11–14. Results At age 7–10, beta-glucan dust levels in the home were associated with persistent atopic asthma at age 11–14 (OR 1.79 for each unit increase in levels, 95% CI 1.14–2.81), independent of endotoxin exposure, and Alternaria or Cladosporium sensitization. The likelihood of BHR almost doubled with unit increases in dust beta-glucan in asthmatic children. In children without asthma, exposure to high beta-glucan levels at age 7–10 also elevated risk for BHR in adolescence (OR 1.74, 95% CI 1.05–2.89). New-onset atopic asthma was twice more likely following high beta-glucan exposure in children without asthma but the association did not reach statistical significance. No associations were evident with concurrent asthma phenotype at age 7–10 or non-atopic asthma at age 11–14. Conclusion These findings implicate home beta-glucan exposure at school-age as a risk factor for persistent atopic asthma and new-onset BHR. The higher prevalence of BHR in urban adolescents may be propagated by this home exposure.
Semantic human image classification based on Energy-Action model

The classification of semantic human images is an active problem in interpreting multimedia images. Many researchers have attempted to improve the semantic model by using semantic action concepts. Although previous techniques, such as keyword definition and using content features of human action, have been applied, most results indicate that human images cannot be mapped into actual image meaning. The aim of this paper is to classify semantic human images by integrating relevant image contents and the energy expenditure. We proposed a new semantic model called the energy-action (EA) model, which analyzes the energy intensity of body parts with essential reference points. The EA model is presented in two stages: human action analysis and energy intensity analysis. Our results indicate that the proposed approach offers significant performance improvements in the interpretation of semantic human images.
Synchronization control scheme for gait training robot and treadmill

Presently, gait training robots with treadmills have been widely used. If the robot and the treadmill lack of an appropriate synchronization, it may affected the performance of the whole system and foot slips on a moving treadmill may cause injuries to patients. Treadmill speed cannot be simply set as constant because foot speed is not constant throughout a gait cycle and the treadmill speed must only be the same as the touching foot in stance phase and the foot speed in swing phase must be ignored. This paper proposes a synchronization control scheme for a two-legged gait training robot and a treadmill. The treadmill speed is calculated based on the horizontal velocities of the left and right feet during the stance phase in order to adjust the treadmill speed. The effectiveness of the proposed synchronization method is confirmed by sixteen experimental tests with five healthy and three patient subjects.
Lfd_infer: an Implementation of a Static Inference on Heap Space Usage

We will exhibit an implementation of the static prediction of heap space usage for first-order functional programs as proposed by M. Hofmann and S. Jost in 2003. The implementation shows that this static inference can be implemented efficiently and is able to identify upper bounds on the consumption of heap memory for a large range of example programs. We will use these examples to investigate the inference’s strengths and weaknesses. Furthermore, this implementation extends the theoretic work by including annotation-related subtyping and arbitrary recursive data types.
Neural network-based optimal control for autonomous mobile vehicle navigation

This work addresses the problem of generating autonomously an optimal control action sequence for an autonomous vehicle based on artificial neural networks (ANN). The principal objective is to autonomously design an optimal controller that steers the center of the vehicle through a number of via points in a particular order using a minimum amount of time. In general, the steering of robotic vehicles depends on the interactions between the vehicle and its supporting medium. Planning for the future encounters with the via points should be part of the current control decision, since the vehicle's position and orientation as it moves through one gate greatly alter the case of navigation through successive points. The proposed neural network-based intelligent controller learns to guide the vehicle through a set of points autonomously. The simulation results show the performance of the proposed approach for a simple case.
Memantine: efficacy and safety in mild-to-severe Alzheimer’s disease

Alzheimer’s disease (AD) is the most common cause of dementia, accounting for 25 million cases worldwide. Until recently, the pharmacotherapy of AD was limited to the use of cholinesterase inhibitors (ChEIs) that are approved only for the mild to moderate stages of the illness. Memantine, an NMDA receptor antagonist has been found to be effective, both as monotherapy and in combination with donepezil, in the treatment of patients with moderate to severe stage AD. More recent studies have examined the role of memantine in the treatment of the mild to moderate stages of the disease, although the collective results of these studies remain inconclusive. Available pharmacoeconomic data indicate that treatment with memantine is cost-effective when compared with no treatment in patients with moderate to severe AD. Memantine treatment is predicted to be associated with lower costs of care, longer time to dependence and institutionalization, and gains in quality-adjusted life-years. In this article, we review the evidence for the use of memantine in patients with AD, ranging from the mild to severe stages of disease.