Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms

Evolutionary algorithms have been effectively used to solve multiobjective optimization problems with a small number of objectives, two or three in general. However, when problems with many objectives are encountered, nearly all algorithms perform poorly due to loss of selection pressure in fitness evaluation solely based upon the Pareto optimality principle. In this paper, we introduce a new fitness evaluation mechanism to continuously differentiate individuals into different degrees of optimality beyond the classification of the original Pareto dominance. The concept of fuzzy logic is adopted to define a fuzzy Pareto domination relation. As a case study, the fuzzy concept is incorporated into the designs of NSGA-II and SPEA2. Experimental results show that the proposed methods exhibit better performance in both convergence and diversity than the original ones for solving many-objective optimization problems.
Interpretation of Controversial Teratogenic Findings of Drugs Such As Phenobarbital

Objective. To check the debated association between phenobarbital treatment during pregnancy and risk for congenital abnormalities (CAs) in their children. Study Design. It is a comparison of phenobarbital treatment in the mothers of cases with CA and matched controls without CAs in the Hungarian Case-Control Surveillance System of Congenital Abnormalities. Results. Of 22,843 cases with CA, 149 (0.65%) had mothers with phenobarbital treatment, while of 38,151 control newborn infants without CA, 209 (0.55%) were born to mothers with phenobarbital treatment (100–400 mg daily) (OR with 95% CI : 1.3, 1.1–1.7). Of 16 CA groups, only hypospadias had a higher risk after phenobarbital treatment in the critical period of this CA (OR with 95% CI : 2.4, 1.1–5.4). However, if only medically recorded phenobarbital treatments were evaluated and multiple testing bias was considered, this association would disappear. Conclusions. This study stresses the importance of the exclusion of recall bias and multiple testing bias.
Characterization of Antibiotic Producing Rare Actinomycete Nonomuraea sp. JAJ18 Derived from an Indian Coastal Solar Saltern

Rare actinomycete genera are accepted as a promising source of novel metabolites having pharmaceutical importance. One such genus of rare actinomycete is Nonomuraea. The present study was aimed at characterizing the antibiotic producing Nonomuraea strain JAJ18 which was previously isolated from coastal solar saltern. Strain JAJ18 was recognized as a member of genus Nonomuraea based on its almost complete 16S rRNA gene sequence and phenotypic characteristics. The strain JAJ18 was found to be closely related to Nonomuraea maheshkhaliensis 16-5-14T (98.90%), Nonomuraea candida HMC10T (98.58%), and Nonomuraea jabiensis A4036T (98.43%). From cell-free culture broth of strain JAJ18, an antibiotic was extracted and purified by silica column chromatography. The obtained antibiotic was found to be active against a range of Gram-positive and Gram-negative bacteria including drug-resistant Staphylococcus, with minimal inhibitory concentration (MIC) ranging from 0.5 to 16.0 µg mL−1. The structural characteristics of antibiotic were determined by FTIR and NMR spectroscopy. The antibiotic was identified to be an aliphatic rich compound with significant dissimilarity to known antibiotics reported from members of the genus, Nonomuraea. As the trends to discover novel metabolites from Nonomuraea are vibrant, further studies are needed to understand the structural and biotechnological significance of antibiotic compound produced by Nonomuraea sp. JAJ18.
A class of non-contractive, trial-dependent update rules for iterative learning control

In this paper, a family of trial-dependent update laws is studied and contrasted with a class of fixed update laws. In particular, it is investigated whether the principle of equivalent feedback extends to trial-dependent update laws. It turns out that this is not the case. Nonetheless, it is shown that a well-known performance bound arising in feedback control architectures, Bode's sensitivity integral, also applies here.
Curved Trajectory Prediction Using a Self-Organizing Neural Network

Existing neural network models are capable of tracking linear trajectories of moving visual objects. This paper describes an additional neural mechanism, disfacilitation, that enhances the ability of a visual system to track curved trajectories. The added mechanism combines information about an object's trajectory with information about changes in the object's trajectory, to improve the estimates for the object's next probable location. Computational simulations are presented that show how the neural mechanism can learn to track the speed of objects and how the network operates to predict the trajectories of accelerating and decelerating objects.
Markov Chain Monte Carlo Methods for Generalized Stochastic Volatility Models

This paper is concerned with Markov chain Monte Carlo based Bayesian inference in generalized models of stochastic volatility defined by heavy-tailed student-t distributions (with unknown degrees of freedom) and covariate effects in the observation and volatility equations. A simple, fast and highly efficient algorithm, that builds on Kim, Shephard and Chib (1998), is developed for estimating these models. Computation of the likelihood function by a particle filter is considered as are methods for constructing diagnostic measures and the model marginal likelihood. The techniques are applied in detail to daily returns on the S&P 500 index and to weekly changes in the short-term interest rate.
3D Image Browsing: The Planets

In this paper, a method of browsing a large collection of images in a 3D environment is presented. Planetary bodies are used as a metaphor for browsing the image collection, where each planet represents a cluster of related images from the dataset. Salient point descriptors are used to cluster the imagery into planets. For each planet, maximum salient overlap is used to select a representative image. The user can move in 3D space through the planetary solar system. From a large distance, representative images painted on the planets are displayed. From a short distance, the images within the cluster are shown on the planet.
Deficient Regulatory T Cell Activity and Low Frequency of IL-17-Producing T Cells Correlate with the Extent of Cardiomyopathy in Human Chagas' Disease

Background Myocardium damage during Chagas' disease results from the immunological imbalance between pro- and production of anti-inflammatory cytokines and has been explained based on the Th1–Th2 dichotomy and regulatory T cell activity. Recently, we demonstrated that IL-17 produced during experimental T. cruzi infection regulates Th1 cells differentiation and parasite induced myocarditis. Here, we investigated the role of IL-17 and regulatory T cell during human Chagas' disease. Methodology/Principal Findings First, we observed CD4+IL-17+ T cells in culture of peripheral blood mononuclear cells (PBMC) from Chagas' disease patients and we evaluated Th1, Th2, Th17 cytokine profile production in the PBMC cells from Chagas' disease patients (cardiomyopathy-free, and with mild, moderate or severe cardiomyopathy) cultured with T. cruzi antigen. Cultures of PBMC from patients with moderate and severe cardiomyopathy produced high levels of TNF-α, IFN-γ and low levels of IL-10, when compared to mild cardiomyopathy or cardiomyopathy-free patients. Flow cytometry analysis showed higher CD4+IL-17+ cells in PBMC cultured from patients without or with mild cardiomyopathy, in comparison to patients with moderate or severe cardiomyopathy. We then analyzed the presence and function of regulatory T cells in all patients. All groups of Chagas' disease patients presented the same frequency of CD4+CD25+ regulatory T cells. However, CD4+CD25+ T cells from patients with mild cardiomyopathy or cardiomyopathy-free showed higher suppressive activity than those with moderate and severe cardiomyopathy. IFN-γ levels during chronic Chagas' disease are inversely correlated to the LVEF (P = 0.007, r = −0.614), while regulatory T cell activity is directly correlated with LVEF (P = 0.022, r = 0.500). Conclusion/Significance These results indicate that reduced production of the cytokines IL-10 and IL-17 in association with high levels of IFN-γ and TNF-α is correlated with the severity of the Chagas' disease cardiomyopathy, and the immunological imbalance observed may be causally related with deficient suppressor activity of regulatory T cells that controls myocardial inflammation.
Electrodynamic resonant energy harvester for low frequencies and amplitudes

Vibration is a suitable source for powering wireless sensors because of its energy level. A high energy output can be only reached by an appropriate harvester design taking the parameters of the available vibration into account. Very often ambient vibration sources have relative low frequencies and amplitudes. In this paper, a novel cylindrical electrodynamic resonant vibration converter is developed for low frequency and low amplitude. The design envisages a fixed coil to have a reliable connection to energy management electronic. For repulsion forces a magnetic spring is proposed to ovoid friction and aging effects of mechanical springs. This ensures a high reliability and compactness of the system. The design parameters have been optimized by finite element method modeling and by experiments. In order to validate the simulation results, an experimental setup for the converter is realized. An evaluation for the generated energy is also treated. The results show that the harvester is able to generate 470 mV for frequency excitation equal to 26 Hz and a low amplitude vibration equal to 1 mm. For the power output evaluation, the optimal load resistance is close to the coil resistance which is equal to 34 Ω and the converter is able to generate 0.72 mW.
Design and simulation of a fast DC recharging station for EV

In this paper a detailed description of the design and simulation of a DC ultra-fast recharging station for Electric Vehicles is carried out. The system consist of a single AC/DC grid connected inverter, a DC-Bus and two DC/DC converter to recharge the batteries of the EVs. The system also has the vehicle-to-grid (V2G) capability. The design of the components of the system and the control schemes are explained and a simulation of the system, performed in Matlab/Simulink environment is presented.
Power-constrained communications using LDLC lattices

An explicit code construction for using low-density lattice codes (LDLC) on the constrained power AWGN channel is given. LDLC lattices can be decoded in high dimension, so that the code relies on the Euclidean distance between codepoints. A sublattice of the coding lattice is used for code shaping. Lattice codes are designed using the continuous approximation, which allows separating the contribution of the shaping region and coding lattice to the total transmit power. Shaping and lattice decoding are both performed using a belief-propagation decoding algorithm. At a rate of 3 bits per dimension, a dimension 100 code which is 3.6 dB from the sphere bound is found.
Political Interference on Firms : Effect of Elections on Bank Lending in India

Using data from staggered state elections in India, this paper provides evidence that politicians directly interfere with firm activity. In states with forthcoming elections, politicians influence banks to increase lending to farmers at the cost of manufacturing firms. This effect is greater in competitive elections and in locations with higher proportion of voters engaged in agriculture. Comparing firms in states that have an election in a given year against firms in states that do not, I find that unavailability of bank credit affects real decisions of firms. Lack of funding forces firms to reduce production, cut investments and lay off workers. Additionally, new firms are less likely to start production during an election year. These findings suggest that political interference has real costs to firms. 1 I thank my committee members Gregor Matvos, Raghuram Rajan, Amit Seru and Amir Sufi for their continuous guidance, support and comments. I thank Reserve Bank of India for providing data on bank lending. I am grateful to Abhiman Das and V. C. Augustine at the Reserve Bank of India for providing extensive support in accessing and understanding the data. I would also like to thank Efraim Benmelech, Jacopo Ponticelli, Chad Syverson and seminar participants at the University of Chicago for their helpful comments. All remaining errors are my own. 1
Design and testing of diffuse reflectance sensor for continuous monitoring of cutaneous blood perfusion

A dual-wavelength reflectance optical sensor for monitoring cutaneous blood perfusion is presented as a part of multisensor glucose monitoring system. A Monte-Carlo simulation of partial differential pathlengths has been used for the optimization of the distance from light source to detector. The simulation indicated that the light pathlength within the upper vascularised skin layers increases before reaching saturation at separation distances larger than 3 mm. Thus the sensor sensitivity does not benefit from larger source-detector distances. At the same time with a higher separation of the detector from the source, the intensity exponentially decreases while undesirable sensitivity to the muscle perfusion increases. The hardware prototype has been developed based on the simulation findings and tested in a laboratory setting and in a home use study by patients with diabetes. For both testing procedures the optical sensor demonstrated high sensitivity to perfusion changes. The effect of initial cutaneous blood increase under the sensor has been observed which can be associated with pressure-induced vasodilation as a response to the sensor application.
Election algorithms with random delays in trees

The election is a classical problem in distributed algorithmic. It aims to design and to analyze a distributed algorithm choosing a node in a graph, here, in a tree. In this paper, a class of randomized algorithms for the election is studied. The election amounts to removing leaves one by one until the tree is reduced to a unique node which is then elected. The algorithm assigns to each leaf a probability distribution (that may depends on the information transmitted by the eliminated nodes) used by the leaf to generate its remaining random lifetime. In the general case, the probability of each node to be elected is given. For two categories of algorithms, close formulas are provided.
Fully Integrated High-Isolation Low-Loss Digitally Controlled MEMS Filters

In this paper, the design and packaging of fully integrated digitally controlled microelectromechanical system (MEMS) filters with low cost, high performance, and compact size are introduced. The four-channel switched filters operating in the frequency range of 11-20 GHz have been developed using MEMS technologies and four five-pole edge-coupled bandpass filters, which are modified from the traditional edge-coupled bandpass filter in the input and output feeders to achieve a better stopband performance. Microwave filters, MEMS circuits, and related packaging are investigated and demonstrated theoretically and experientially.
The relationship between type D personality and perceived social support in myocardial infarction patients

BACKGROUND: Type D personality is based on two global and stable personality traits, including negative affectivity (NA) and social inhibition (SI). The aim of this study was to examine the relationship between type D personality and perceived social support in post myocardial infarction (MI) patients. METHODS: One hundred seventy six consecutive patients following MI admitted to the cardiac care unit (CCU) of nine hospitals in Isfahan, Iran from April to September 2006 were selected based on the inclusive and exclusive criteria. The patients completed the Persian version of type D personality scale and the Persian version of multidimensional scale of perceived social support (MSPSS). Also, demographic and medical questionnaire was completed for each patient. Chi-squared test, t-test and MANOVA were used to analyze the data. RESULTS: The findings indicated that 35.8% patients (35.8 %) were classified as type D. The results of MANOVA showed that type D patients were significantly different from non-type D patients (F = 8.72, p = 0.0001) on MSPSS scores and on all dimensions including family subscale (F = 11.52, p = 0.001), friends subscale (F= 16.16, p = 0.0001) and significant others subscale (F = 5.04, p = 0.026). CONCLUSIONS: Type D personality substantially affects the way MI patients perceive availability of social support from different sources including family, friends, and significant others. One implication of this finding may be to develop tailor-made interventions for MI patients with type D.
Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes

MOTIVATION Flux estimation using isotopomer information of metabolites is currently the most reliable method to obtain quantitative estimates of the activity of metabolic pathways. However, the development of isotopomer measurement techniques for intermediate metabolites is a demanding task. Careful planning of isotopomer measurements is thus needed to maximize the available flux information while minimizing the experimental effort. RESULTS In this paper we study the question of finding the smallest subset of metabolites to measure that ensure the same level of isotopomer information as the measurement of every metabolite in the metabolic network. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give methods for obtaining exact and fast approximate solutions, and evaluate empirically the efficacy of the proposed methods by analyzing a metabolic network that models the central carbon metabolism of Saccharomyces cerevisiae.
A Reference Interpreter for the Graph Programming Language GP 2

GP 2 is an experimental programming language for computing by graph transformation. An initial interpreter for GP 2, written in the functional language Haskell, provides a concise and simply structured reference implementation. Despite its simplicity, the performance of the interpreter is sufficient for the comparative investigation of a range of test programs. It also provides a platform for the development of more sophisticated implementations.
Mixed-Mode Analysis of Different Mode Silicon Nanowire Transistors-Based Inverter

In this paper, we focused on the comparison and analysis of the performance of inversion-mode (IM), accumulation-mode (AM), and junctionless (JL) silicon nanowire field-effect transistors (NWTs)-based inverter. The effects of the radius, equivalent oxide thickness and source/drain doping in the different mode nanowire device structure are investigated. The capacitance components and transient characteristics, which determine the behavior of devices in the circuits, are studied and compared among different mode nanowire devices. The mixed-mode circuit simulations have been performed for the inverter circuit and three-stage ring oscillator consist of n-type and p-type IM/AM/JL NWTs. JL NWTs show lower Miller capacitance which contributes to suppressing the overshoot effect in the circuits. Results of these simulations can give insights into the in-circuit behavior of these future generation devices.
A Systematic State-Based Approach to Regression Testing of Component Software

Today, component-based software engineering has been widely used in software construction to reduce project cost and speed up software development cycle. Due to software changes in new release or update of components, regression testing is needed to assure system quality. When changes made to a component, the component could be affected, moreover, the changes could bring impacts on the entire system. We firstly identify diverse changes made to components and system based on models, then perform change impact analysis, and finally refresh regression test suite using a state-based testing practice. Related existing research did not address the issue of systematic regression testing of component-based software, especially at system level. The paper also reports a case study based on a realistic component-based software system using a, which shows that the approach is feasible and effective.
Detection of Immunoglobulin G against E7 of Human Papillomavirus in Non-Small-Cell Lung Cancer

Background. A significant number of non-small-cell lung cancers (NSCLC) have human papillomavirus (HPV) DNA integrated in their genome. This study sought to further establish HPV's possible etiologic link to NSCLC by evaluating an immune response to HPV's oncogene, E7, in patients with NSCLC. Patients and Methods. Antibodies (IgG) in serum against E7 for HPV 16 and 18 in 100 patients with NSCLC were examined by enzyme-linked immunosorbent assay (ELISA). Results. Sixteen NSCLC patients were found to have a high titration of IgG for HPV oncogenic E7 protein. 23.5% of adenocarcinomas (AC,) and 15.4% of squamous cell carcinomas (SCC) were positive for IgG against HPV E7. HPV-18 (11%) had a slightly higher frequency than HPV-16 (6%). Of the six positive cases for HPV-16, 3 were AC, 2 SCC, and 1 NOS (not otherwise specified). For the 11 HPV-18 positives, 7 were AC, and 4 SCC. The one case with IgG against HPV 16 and 18 was AC. One case had high cross-reactive levels against E7 of HPV 16 and 18. Two (28%) of 7 patients who reported never smoking were positive for HPV, and 12 (13.6%) of 88 smokers were HPV positive. Conclusions. The study detected high levels of IgG against E7 in 16% of NSCLC patients. This adds evidence to a potential role of HPV in the pathogenesis of NSCLC.
Derivation of standard lactation curves for South African dairy cows

Standard Lactation Curves were derived for South African Holstein and Jersey cows, using 20 herd-, 18 age- and six season classes. Six herd classes were below and 13 above the average production level for both breeds. A standard lactation curve was estimated for each combination of herd-, age- and season class, which resulted in 2 160 curves per trait per breed. Variation in Holstein yields was much larger than that of Jerseys, causing different herd classes to be defined for both breeds. South African cows displayed more variation in yields compared to those of Holstein cows in the Netherlands and Ireland. Season of calving had a pronounced effect on the shape of the Standard Lactation Curve, while the combination of calving age and lactation affected both the shape and level of the curves. Expected yields were therefore higher during the whole lactation in higher compared to lower herd classes.The results of this study form the basis for inclusion of records in progress and short lactations in national genetic evaluation.
Substrate-specific Interactions with the Heme-bound Oxygen Molecule of Nitric-oxide Synthase*

We report the characterization by resonance Raman spectroscopy of the oxygenated complex (FeIIO2) of nitric-oxide synthases of Staphylococcus aureus (saNOS) and Bacillus subtilis (bsNOS) saturated with Nω-hydroxy-l-arginine. The frequencies of the νFe–O and νO–O modes were 530 and 1135 cm–, respectively, in both the presence and absence of tetrahydrobiopterin. On the basis of a comparison of these frequencies with those of saNOS and bsNOS saturated with l-arginine (νFe–O at 517 cm–1 and νO–O at 1123 cm–1) and those of substrate-free saNOS (νFe–O at 517 and νO–O at 1135 cm–1) (Chartier, F. J. M., Blais, S. P., and Couture, M. (2006) J. Biol. Chem. 281, 9953–9962), we propose two models that account for the frequency shift of νFe–O (but not νO–O) upon Nω-hydroxy-l-arginine binding as well as the frequency shift of νO–O (but not νFe–O) upon l-arginine binding. The implications of these substrate-specific interactions with respect to catalysis by NOSs are discussed.