Miracle-dz/UniFAR-FTUs huggingface dataset:
Calculation of Totally Optimized Button Configurations Using Fitts' Law

This paper addresses the problem of optimal placement and configuration for a set of buttons on a graphical user interface (GUI). We present an optimization algorithm that reduces the average time necessary for pointing device motions. Fitts’ law (Fitts 1954) is used to estimate the transfer time for cursor movements between buttons. Numerous studies in the literature focus on the verification and application of Fitts’ law in a rather direct way (MacKenzie 1992). Our work differs in its goal: The problem of finding totally optimized button configurations is a non-trivial optimization task and is still an open issue.
Zinc in the Monoaminergic Theory of Depression: Its Relationship to Neural Plasticity

Preclinical and clinical studies have demonstrated that zinc possesses antidepressant properties and that it may augment the therapy with conventional, that is, monoamine-based, antidepressants. In this review we aim to discuss the role of zinc in the pathophysiology and treatment of depression with regard to the monoamine hypothesis of the disease. Particular attention will be paid to the recently described zinc-sensing GPR39 receptor as well as aspects of zinc deficiency. Furthermore, an attempt will be made to give a possible explanation of the mechanisms by which zinc interacts with the monoamine system in the context of depression and neural plasticity.
PERFORMANCE ENHANCEMENT OF HIGH VOLTAGE GAIN TWO PHASE INTERLEAVED BOOST CONVERTER USING MPPT ALGORITHM

This paper proposes the simulation and implementation of performance enhancement of two phase interleaved boost converter using Maximum Power Point Tracking (MPPT) algorithm to achieve maximum power for Photo Voltaic ( PV) application. The output current is divided by two phase since current stress on each switch is reduced. Each switch is turn on by same frequency with phase difference of π. The output of PV panel is affected by temperature and insulation level, Hence conversion efficiency is very low. To improve the efficiency, additionally the MPPT controller is used in our proposed converter to efficiently draw the maximum power from the solar panel. The maximum power point is identified using Perturb &Observe (P&O) algorithm. The Perturb &Observe algorithm suitably to track the maximum power output of two phase interleaved boost converter with proper duty ratio. This paper present simulation and implementation procedure for two phase Interleaved Boost Converter with MPPT algorithm. The simulation results are obtained by using MATLAB/SIMULINK. The simulation results for non-isolated two stage interleaved high voltage gain boost converter were compared with and without MPPT. The MATLAB/simulink simulation results are presented to validate proposed converter. The hardware prototype of 12volt input 102 volt output has been developed.
The Impact of the NHSC on the Utilization of Physician Services and on Health Status in Rural Areas

In this paper we present the results of an analysis of the impact of the National Health Service Corps (NHSC) on the utilization of physician services and on health status in rural areas, using Health Interview Survey (HIS) data for 1978. Because county identifiers were available to us for the study, we were able to link the HIS data to aggregate county data and to control for characteristics of the market for physicians' services in the individual's area of residence, including whether or not the individual was nearby to an NHSC site. Although weak evidence of a favorable NHSC impact is found for children, on balance, there is no conclusive evidence in either direction for men or women. Differences in neither income level nor race are found to be strongly associated with differences in utilization or in the number of bed days.
Accurate Value-at-Risk forecast with the (good old) normal-GARCH model

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.
LocAAP: Location based actuation of appliances

We present the design and development of a smart control system that integrates ambient sensing and appliance actuation. The sensor system comprises of smartphone embedded with magnetic field sensor and Zigbee light sensor. The phone is used for capturing ambient magnetic fields for indoor localization and a Zigbee based Micaz mote captures the ambient light intensity levels in different rooms. The control system combines both the location and the light intensity information to turn appliances ON/OFF. This light weight sensing and control system performs local computation on the user's smartphone, requires no additional infrastructure, no user intervention and most importantly saves power. We deploy the system across four users moving between different locations and showcase the feasibility of the system in efficiently actuating appliances with a minimal set of sensors.
Site-Specific Management of Miscanthus Genotypes for Combustion and Anaerobic Digestion: A Comparison of Energy Yields

In Europe, the perennial C4 grass miscanthus is currently mainly cultivated for energy generation via combustion. In recent years, anaerobic digestion has been identified as a promising alternative utilization pathway. Anaerobic digestion produces a higher-value intermediate (biogas), which can be upgraded to biomethane, stored in the existing natural gas infrastructure and further utilized as a transport fuel or in combined heat and power plants. However, the upgrading of the solid biomass into gaseous fuel leads to conversion-related energy losses, the level of which depends on the cultivation parameters genotype, location, and harvest date. Thus, site-specific crop management needs to be adapted to the intended utilization pathway. The objectives of this paper are to quantify (i) the impact of genotype, location and harvest date on energy yields of anaerobic digestion and combustion and (ii) the conversion losses of upgrading solid biomass into biogas. For this purpose, five miscanthus genotypes (OPM 3, 6, 9, 11, 14), three cultivation locations (Adana, Moscow, Stuttgart), and up to six harvest dates (August–March) were assessed. Anaerobic digestion yielded, on average, 35% less energy than combustion. Genotype, location, and harvest date all had significant impacts on the energy yield. For both, this is determined by dry matter yield and ash content and additionally by substrate-specific methane yield for anaerobic digestion and moisture content for combustion. Averaged over all locations and genotypes, an early harvest in August led to 25% and a late harvest to 45% conversion losses. However, each utilization option has its own optimal harvest date, determined by biomass yield, biomass quality, and cutting tolerance. By applying an autumn green harvest for anaerobic digestion and a delayed harvest for combustion, the conversion-related energy loss was reduced to an average of 18%. This clearly shows that the delayed harvest required to maintain biomass quality for combustion is accompanied by high energy losses through yield reduction over winter. The pre-winter harvest applied in the biogas utilization pathway avoids these yield losses and largely compensates for the conversion-related energy losses of anaerobic digestion.
Effects of Sitagliptin on Lipid Profiles in Patients With Type 2 Diabetes Mellitus

AbstractSitagliptin has been reported to improve lipid profiles, but findings from these studies are conflicting. We conducted this meta-analysis to evaluate the effects of sitagliptin on serum lipids in patients with type 2 diabetes mellitus.We made a comprehensive literature search in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and VIP database until June 2015. Eligible studies were randomized clinical trials (RCTs) that investigated the effect of sitagliptin on serum triglycerides (TGs), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C). Eleven RCTs with 2338 patients were identified. Compared with controls, sitagliptin alone or in combination significantly improved serum TG (weighted mean difference [WMD] −0.24 mmol/L; 95% confidence interval [CI] −0.40 to −0.09; P = 0.002) and HDL-C (WMD 0.05 mmol/L; 95% CI 0.02–0.07; P < 0.001). However, no statistical significances were observed in LDL-C (WMD −0.07 mmol/L; 95% CI −0.22 to 0.08; P = 0.337) and TC (WMD −0.14; 95% CI −0.33 to 0.06; P = 0.177). Subgroup analyses revealed that sitagliptin alone achieved greater improvement in serum TG, TC, and HDL-C levels.These findings suggested that sitagliptin alone or in combination significantly improved serum TG and HDL-C levels in patients with type 2 diabetes mellitus.
Estimating the mortality impacts of particulate matter: what can be learned from between-study variability?

Epidemiologic studies of the link between particulate matter (PM) concentrations and mortality rates have yielded a range of estimates, leading to disagreement about the magnitude of the relationship and the strength of the causal connection. Previous meta-analyses of this literature have provided pooled effect estimates, but have not addressed between-study variability that may be associated with analytical models, pollution patterns, and exposed populations. To determine whether study-specific factors can explain some of the variability in the time-series studies on mortality from particulate matter [less than/equal to] 10 microm in aerodynamic diameter (PM(10)), we applied an empirical Bayes meta-analysis. We estimate that mortality rates increase on average by 0.7% per 10 microg/m(3) increase in PM(10) concentrations, with greater effects at sites with higher ratios of particulate matter [less than/equal to] 2.5 microm in aerodynamic diameter (PM(2.5))/PM(10). This finding did not change with the inclusion of a number of potential confounders and effect modifiers, although there is some evidence that PM effects are influenced by climate, housing characteristics, demographics, and the presence of sulfur dioxide and ozone. Although further analysis would be needed to determine which factors causally influence the relationship between PM(10) and mortality, these findings can help guide future epidemiologic investigations and policy decisions. ImagesFigure 1
Improvement of short-span seeking performance in a dual-stage hard disk drive actuator

This paper proposes an alternative method to improve short-span seeking performance of a compensator based control system for a dual-stage servo actuator. The short-span seeking performance is improved by presetting initial conditions of the compensator during the short-span seek commands. This results in faster response of the secondary control loop and hence in faster seek times within the range of the secondary actuator. The performance of the proposed initial conditions based method is compared with the performance of recently proposed methods using constant and dynamic saturations in the secondary loop. The results show that the performance of the proposed method is comparable with the performance of the method using the dynamic saturation and thus can be used as an alternative, simpler method, to achieve faster short-span seek times.
Reactivity of the Gold/Water Interface During Selective Oxidation Catalysis

Indirect Oxidation by Oxygen Partial oxidation of alcohols to aldehydes and ketones must avoid complete oxidation to carbon dioxide and water. Zope et al. (p. 74) examined the partial oxidation of ethanol and glycerol to acids in alkaline aqueous solvents over gold and platinum catalysts. Conversions were highest for gold supported on titania, but studies with isotopically labeled molecular oxygen showed that oxygen incorporated into the acid comes from hydroxide ions. Direct incorporation of oxygen did not occur even for the platinum catalysts, despite the fact that oxygen can dissociate on this metal. Instead, molecular oxygen appeared to regenerate hydroxide ions at the metal surface through the formation of peroxide intermediates. Hydroxide at the metal/liquid interface promotes the catalytic activity of gold during the partial oxidation of alcohols. The selective oxidation of alcohols in aqueous phase over supported metal catalysts is facilitated by high-pH conditions. We have studied the mechanism of ethanol and glycerol oxidation to acids over various supported gold and platinum catalysts. Labeling experiments with 18O2 and H218O demonstrate that oxygen atoms originating from hydroxide ions instead of molecular oxygen are incorporated into the alcohol during the oxidation reaction. Density functional theory calculations suggest that the reaction path involves both solution-mediated and metal-catalyzed elementary steps. Molecular oxygen is proposed to participate in the catalytic cycle not by dissociation to atomic oxygen but by regenerating hydroxide ions formed via the catalytic decomposition of a peroxide intermediate.
Lipless Tracking and Emotion Estimation

Automatic human lip tracking is one of the key components tomany facial image analysis tasks, such as, lip-reading and emotion from lips. It has been a classical hard image analysis problem over decades. In this paper, we propose an indirect lip tracking strategy: `lipless tracking'. It is based on the observation that many of us don't have clear lips and some even don't have visible lips. The strategy is to select and localize stable lip features around the mouth for tracking. For this purpose deformable contour-segments are modelled based on lip features and tracking is done using dynamic programming and Viterbi Algorithm. The strength of proposed algorithm is demonstrated in emotion estimation domain. Finally, real-time video experiments performed on private and publicity available data set (MMI face database) have shown the robustness of our proposed lipless tracking technique.
Image resolution enhancement based on edge directed interpolation using dual tree — Complex wavelet transform

Image resolution enhancement is a usable process for many image processing applications such as geoscience studies, astronomy and geographical information systems. One of the traditional methods used to increase the image resolution is image interpolation but the potential problem associated with it is to magnify the image many times without loss in image clarity. However, all the classical linear interpolation techniques like bilinear, bi-cubic interpolation methods generate blurred image. By employing dual-tree complex wavelet transform (DT-CWT) on a edge directional interpolation, it is possible to recover the high frequency components which provides an image with good visual clarity and thus super resolved high resolution images are obtained. The obtained simulation results comply with the above stated claim. A performance comparison of it is made with the recent work discussed in [7].
Psychometric Properties of Translation of the Child Perception Questionnaire (CPQ11-14) in Telugu Speaking Indian Children

Oral health related quality of life research among children in India is still nascent and no measures have been validated to date. Although CPQ11-14 has been previously used in studies from the Indian sub-continent, the instrument has never been tested for cross-cultural adaptability. This study aimed to assess the validity and reliability of CPQ11-14 in Telugu speaking Indian school children. Primary school children of Medak district, Telangana State, India, were recruited by a multi-stage probability sampling method. The translated questionnaire was initially pilot tested on a small subset of children (n = 40). Children with informed consent from parents (N = 1342) were then provided with questionnaires containing the Telugu translation of CPQ11-14, followed by a clinical examination conducted by a single examiner, using Basic WHO survey methods for dental caries, malocclusion, and Dean’s Fluorosis index. Children (n = 161) in randomly chosen schools were re-administered the same questionnaire after a two week interval to test reliability of CPQ11-14 on repeated administrations. Internal consistency and test-retest reliability as determined by Cronbach’s alpha and Intra-class correlation coefficient for overall CPQ11-14 scale were 0.925 and 0.923, respectively. CPQ11-14 discriminated between the categories of fluorosis and malocclusion while its discriminant validity with respect to dental caries was limited. CPQ11-14 also demonstrated good construct validity with both overall CPQ11-14 and its subscales having significant positive correlation with global ratings of oral health and overall wellbeing, even after adjusting for confounding variables. CPQ11-14 had a correlation of 0.405 with self-evaluated oral health and 0.407 with self-evaluated impact of oral health on overall wellbeing. In conclusion, Telugu translation of CPQ11-14 demonstrated good internal consistency and excellent reliability on repeated administrations after two weeks. It also exhibited good discriminant and construct validity.
Comparison of ARMA and Multilayer Perceptron Based Methods for Economic Time Series Forecasting

In this paper two popular time series prediction methods - the Auto Regression Moving Average (ARMA) and the multilayer perceptron (MLP) - are compared while forecasting seven real world economical time series. It is shown that the prediction accuracy of both methods is poor in ill-structured problems. In the well-structured cases, when prediction accuracy is high, the MLP predicts better providing lower mean prediction error.
Nowcasting the Global Economy

Forecasts of global economic activity and inflation are important inputs when conducting monetary policy in small open economies such as Canada. As part of the Bank of Canada's broad agenda to augment its short-term forecasting tools, the author constructs simple mixed-frequency forecasting equations for quarterly global output, imports, and inflation using the monthly global Purchasing Managers Index (PMI). When compared against two benchmark models, the results show that the PMIs are useful for forecasting developments in the global economy. As the forecasts are updated throughout the quarter with the monthly release of the PMI, forecasting performance generally improves. An analysis of the forecasts over the period of the Great Recession (in particular, 2008Q4 to 2009Q2) shows that, while models that include the "soft" PMI indicators did not fully capture the sharp deterioration in the global economy, they nevertheless improved the forecasts relative to the benchmark models. This finding highlights the usefulness of such indicators for short-term forecasting.
Harmony search based algorithm for mobile robot global path planning

The global path planning problem is very challenging NP-complete problem in the domain of robotics. An NP-complete problem would be explained as a type of problem that can't be solved in real-time by using naïve deterministic techniques. Many metaheuristic approaches have been developed up to date, to provide an optimal solution to this problem. In this work we present a novel Quad-Harmony Search (QHS) algorithm based on Quad-tree free space decomposition methodology and Harmony Search optimization. The developed algorithm has been evaluated on various grid based environments with different percentage of obstacle coverage. The results have demonstrated that it is superior in terms of time and optimality of the solution compared to other known metaheuristic algorithms and promised to always find the optimal solution.
Control of bilateral teleoperation systems using single controller over delayed communication network

The control problem for bilateral teleoperation systems using only one controller is studied in this paper. In the proposed control framework, the remote robot transmits position/velocity signals to the controller located with the local robot. The corresponding control inputs for local and remote robots are obtained from the same controller. The individual control signal is sent to the local robot directly, and transmitted to the remote robot over a network subject to communication delays. Two control algorithms, P-like and PD-like controllers, are considered in the novel bilateral teleoperation system framework. Stability and tracking performance can be guaranteed if control gains are contingent to time delays when the external force are passive or both robots are in free motion. Numerical examples are presented to validate the performance of the proposed bilateral teleoperation control systems.
Appliance level demand modeling and pricing optimization for demand response management in smart grid

In this paper, we propose a distributed optimization algorithm for the demand response management with a comprehensive customer demand modeling framework in the smart grid. Different from the existing literature, the considered demand modeling framework considers not only the energy management modeling but also the appliance-level usage pattern learning models, both for time-shiftable loads. More specific, a bill minimization based demand optimization model is firstly proposed for the customers choosing to use a home energy management software. Secondly, an appliance level probability behaviour model via calculating the probability distribution of different electricity consumption patterns in response to the dynamic prices is proposed for the customers choosing to manage their energy usages by themselves. Based on the optimization and learning results, we further propose a multi-population genetic algorithm based pricing optimization model for demand response management with the aim to maximize the retailer's profit and maximize customers' benefits. Numerical results indicate the applicability and effectiveness of the proposed models and its benefits.
Metabolic origins and clinical significance of LDL heterogeneity DOI 10.1194/jlr.R200004-JLR200

LDLs in humans comprise multiple distinct subspecies that differ in their metabolic behavior and pathologic roles. Metabolic turnover studies suggest that this heterogeneity results from multiple pathways, including catabolism of different VLDL and IDL precursors, metabolic remodeling, and direct production. A common lipoprotein profile designated atherogenic lipoprotein phenotype is characterized by a predominance of small dense LDL particles. Multiple features of this phenotype, including increased levels of triglyceride rich lipoprotein remnants and IDLs, reduced levels of HDL and an association with insulin resistance, contribute to increased risk for coronary heart disease compared with individuals with a predominance of larger LDL. Increased atherogenic potential of small dense LDL is suggested by greater propensity for transport into the subendothelial space, increased binding to arterial proteoglycans, and susceptibility to oxidative modification. Large LDL particles also can be associated with increased coronary disease risk, particularly in the setting of normal or low triglyceride levels. Like small LDL, large LDL exhibits reduced LDL receptor affinity compared with intermediate sized LDL. Future delineation of the determinants of heterogeneity of LDL and other apoB-containing lipoproteins may contribute to improved identification and management of patients at high risk for atherosclerotic disease.