Miracle-dz/UniFAR-FTUs huggingface dataset:
Conversion of Biomass-Derived Furfuryl Alcohol into Ethyl Levulinate Catalyzed by Solid Acid in Ethanol

A green and efficient process was developed for the conversion of biomass-derived furfuryl alcohol to ethyl levulinate using eco-friendly solid acid catalysts (zeolites and sulfated oxides) in ethanol. Studies for optimizing the reaction conditions such as the substrate concentration, the reaction time, the temperature, and the catalyst loading dosage were performed. With SO42−/TiO2 as the catalyst, a high ethyl levulinate yield of 74.6 mol% was achieved using a catalyst load of 5 wt% at 398 K for 2.0 h. The catalyst recovered through calcination was found to maintain good catalytic activity (47.8 mol%) after three cycles, and it was easily reactivated by re-soaking in H2SO4 solution. Catalyst characterization was based on BET surface area, NH3-TPD, and elemental analysis techniques.
Towards a self-organizing Universe

In this work we show that the large scale structure of the Universe is naturally linked to the E-infinity theory and to the concept of a self-structured Universe. The key idea is that the nonlinear evolution of the Universe towards a fixed point located at 4 + 3(where is the golden mean) must be reflected by the evolution of matter structures. Using data from 2dFGRS we show that the fractal dimension of the large scale galaxy distribution seems to depend on the redshift. This dependence suggests that the Universe has started to form structures about thirteen billions years ago and is evolving towards a Cantorian structure.
A Feature Gene Selection Method Based on ReliefF and PSO

Due to the shortcomings of low efficiency and low accuracy of DNA microarray data, the paper proposes a feature gene selection algorithm based on ReliefF and PSO (RefFPSO). Firstly, ReliefF is used as the feature pre-filter to delete the genes with low correlation with the classification target. Then PSO is used as the search algorithm. Finally, the classification accuracy of SVM is used as the evaluation function of the feature subset to get the final optimal gene subset. Experiments show that this method can effectively put forward irrelevant genes and use fewer characteristic genes to obtain higher classification accuracy.
Effects of Solar Scintillation on Deep Space Communications: Challenges and Prediction Techniques

A reliable deep space communications system plays a key role in extending the range of space communications and has become an indispensable part of space information networks. With the emergence of many deep space exploration projects, it can be envisioned that a new era of research on deep space communications has arrived. However, the performance of deep space communications is severely degraded by solar scintillation, which occurs frequently during superior solar conjunction. In this article, we first review the state of the art of solar scintillation research, including the definition of solar scintillation, influencing factors, assessment methods, and scintillation models. Then an effective solar scintillation prediction model is proposed to overcome the challenges related to solar scintillation for deep space communications. After that, a coronal turbulence channel model is investigated and discussed. Based on this coronal channel model and our proposed solar scintillation model, the link bit error rate performance is further analyzed. Finally, we identify some open problems and research directions that could be investigated for a deep space communications system during superior solar conjunctions, which will support space information networks.
Variable kernel‐based computing algorithms for estimating sparse multipath channels

Accurate channel estimation algorithms are required to mitigate the frequency‐selective fading in the broadband wireless communication systems. Many physical experiments revealed that finite impulsive responses are distributed as sparse in delayed time domain. Hence, the inherent sparse information can be exploited by state‐of‐the‐art computing algorithms, in order to improve channel accuracy. Existing computing algorithms, zero‐attracting recursive least square (ZA‐RLS) and reweighted ZA‐RLS (RZA‐RLS), have been developed to exploit channel sparsity. However, optimization theory implies that accuracy of the computing algorithms can be further improved to exploit more sparsity information. To further improve the estimation performance, this paper proposes a correntropy induced metric (CIM)‐penalized RLS (CIM‐RLS) based sparse channel estimation algorithm. Here, sparse constraint is performed by CIM function, while error constraint term is computed by RLS. In particular, Gaussian kernel is adopted for computing the CIM, and its variable kernel width (VKW) is computed for adaptively exploiting the channel sparsity. Monte Carlo simulation results are conducted to verify the proposed algorithm in different scenarios.
Health-Related Outcomes of Adverse Childhood Experiences in Texas, 2002

Introduction We assessed the prevalence of 7 childhood adversities (psychological, physical, and sexual abuse; household mental illness; household substance abuse; maternal battery; and incarceration of a household member) and the associations of those adversities with health outcomes. Methods Using data from 5,378 people who responded to the 2002 Texas Behavioral Risk Factor Surveillance System survey (which included questions about childhood adversity), we created 4 groups: no childhood abuse or household dysfunction, childhood abuse only, household dysfunction only, and both childhood abuse and household dysfunction. We examined groups by sociodemographic variables and the association with current smoking, obesity, and self-rated health. Results Among adult respondents, 46% reported at least 1 childhood adversity. Reports of both household dysfunction and abuse were significantly lower for college graduates than for people with less education. For those with both abuse and household dysfunction, the odds of current smoking were 1.9 and for obesity were 1.3. Compared to people without childhood adversities, people who experienced childhood adversities more frequently reported having fair or poor general health status. Conclusion Childhood adversities are common among Texas adults. People with childhood adversities are more likely to be socioeconomically disadvantaged, less educated, and have difficulties maintaining employment in adulthood compared to people with no adversities. Moreover, childhood adversities appear to be associated with health problems such as current smoking, obesity, and poor or fair general health among Texas adults.
Control of voluntary and optogenetically perturbed locomotion by spike rate and timing of neurons of the mouse cerebellar nuclei

Neurons of the cerebellar nuclei (CbN), which generate cerebellar output, are inhibited by Purkinje cells. With extracellular recordings during voluntary locomotion in head-fixed mice, we tested how the rate and coherence of inhibition influence CbN cell firing and well-practiced movements. Firing rates of Purkinje and CbN cells were modulated systematically through the stride cycle (~200–300 ms). Optogenetically stimulating ChR2-expressing Purkinje cells with light steps or trains evoked either asynchronous or synchronous inhibition of CbN cells. Steps slowed CbN firing. Trains suppressed CbN cell firing less effectively, but consistently altered millisecond-scale spike timing. Steps or trains that perturbed stride-related modulation of CbN cell firing rates correlated well with irregularities of movement, suggesting that ongoing locomotion is sensitive to alterations in modulated CbN cell firing. Unperturbed locomotion continued more often during trains than steps, however, suggesting that stride-related modulation of CbN spiking is less readily disrupted by synchronous than asynchronous inhibition.
A Deep Learning-Based Approach to Non-Intrusive Objective Speech Intelligibility Estimation

This paper proposes a deep learning-based non-intrusive objective speech intelligibility estimation method based on recurrent neural network (RNN) with long short-term memory (LSTM) structure. Conventional non-intrusive estimation methods such as standard P.563 have poor estimation performance and lack of consistency, especially, in various noise and reverberation environments. The proposed method trains the LSTM RNN model parameters by utilizing the STOI that is the standard intrusive intelligibility estimation method with reference speech signal. The input and output of the LSTM RNN are the MFCC vector and the frame-wise STOI value, respectively. Experimental results show that the proposed objective intelligibility estimation method outperforms the conventional standard P.563 in various noisy and reverberant environments. key words: non-intrusive, speech intelligibility, LSTM, RNN, STOI
The effect of pulsation frequency on transition in pulsatile pipe flow

Pulsatile flows are common in nature and in applications, but their stability and transition to turbulence are still poorly understood. Even in the simple case of pipe flow subject to harmonic pulsation, there is no consensus among experimental studies on whether pulsation delays or enhances transition. We here report direct numerical simulations of pulsatile pipe flow at low pulsation amplitude $A\leqslant 0.4$ . We use a spatially localized impulsive disturbance to generate a single turbulent puff and track its dynamics as it travels downstream. The computed relaminarization statistics are in quantitative agreement with the experiments of Xu et al. (J. Fluid Mech., vol. 831, 2017, pp. 418–432) and support the conclusion that increasing the pulsation amplitude and lowering the frequency enhance the stability of the flow. In the high-frequency regime, the behaviour of steady pipe flow is recovered. In addition, we show that, when the pipe length does not permit the observation of a full cycle, a reduction of the transition threshold is observed. We obtain an equation quantifying this effect and compare it favourably with the measurements of Stettler & Hussain (J. Fluid Mech., vol. 170, 1986, pp. 169–197). Our results resolve previous discrepancies, which are due to different pipe lengths, perturbation methods and criteria chosen to quantify transition in experiments.
Hashing of personally identifiable information is not sufficient

It is common practice of web tracking services to hash personally identifiable information (PII), e. g. , e-mail or IP addresses, in order to avoid linkability between collected data sets of web tracking services and the corresponding users while still preserving the ability to update and merge data sets associated to the very same user over time. Consequently, these services argue to be complying with existing privacy laws as the data sets allegedly have been pseudonymised. In this paper, we show that the finite pre-image space of PII is bounded in such a way, that an attack on these hashes is significantly eased both theoretically as well as in practice. As a result, the inference from PII hashes to the corresponding PII is intrinsically faster than by performing a naive brute-force attack. We support this statement by an empirical study of breaking PII hashes in order to show that hashing of PII is not a sufficient pseudonymisation technique.
To Evaluate the Effect of Light Curable Fluoride Varnish on Enamel Demineralization during Orthodontic Treatment

AIM : To evaluate the effect of a single application of light curable fluoride varnish (Clinpro XT) on enamel demineralization adjacent to orthodontic brackets during fixed orthodontic treatment at different time intervals using scanning electron microscopy (SEM) and Electron Dispersive X ray analysis (EDAX) MATERIALS AND METHODS : The study and controls were randomly allotted on either side of both arches. After conventional bonding procedure, light curable fluoride varnish was applied around the bracket on the buccal surface of the study side premolars. A 0.014NiTi arch wire were placed immediately. Brackets were debonded at 60 days in mandible and 90 days in the maxilla. The samples were then subjected to scanning electron microscopy (SEM) and electron dispersive X-ray analysis (EDAX) analysis. RESULTS : SEM examination of the enamel surface of the study group revealed almost normal topographic features of enamel. There were globules of calcium fluoride like material irregularly distributed over enamel surface. SEM observation of the enamel surface in control groups revealed roughened enamel surface with multiple areas of enamel erosion. Various patterns of enamel decalcification were observed in the form of open focal holes and demineralization of enamel rod core. A statistically significant increase in the weight percentage of sodium, aluminum, fluoride, magnesium and iron was noted in the study group when compared to that of the control group. The difference in weight percentage of elemental oxygen, chlorine, silicon and Calcium -Phosphorus ration was statistically insignificant. CONCLUSION : The results of our study showed that a single application of light curable fluoride varnish (Clinpro -XT) may prevent demineralization. The light curable fluoride varnish (LCFV)may be used in non-compliant patients as a cariostatic agent in long term clinical situation.
A new spatially constrained NMF with application to fMRI

In this paper the problem of BOLD detection is addressed. The focus here is on non-negative matrix factorization (NMF), which is a data driven method and able to provide part-based representation of data. A new constrained optimization problem is proposed for the purpose of BOLD detection. The proposed constraint imposes some prior spatial information of active area inside the brain, on the decomposition process. The constraint is built up based on the type of stimulus and available physiological knowledge of the brain performance. The simulation results on both synthetic and real fMRI data show that applying the proposed constraint improves the BOLD detection performance.
Effect of Adaptive Compression and Fast-Acting WDRC Strategies on Sentence Recognition in Noise in Mandarin-Speaking Pediatric Hearing Aid Users

Abstract Background: Wide dynamic range compression (WDRC) has been widely used in hearing aid technology. However, several reports indicate that WDRC may improve audibility at the expense of speech intelligibility. As such, a modified amplification compression scheme, named adaptive compression, was developed. However, the effect of compression strategies on speech perception in pediatric hearing aid users has not been clearly reported. Purpose: The purpose of the present study was to investigate the effect of adaptive compression and fast-acting WDRC processing strategies on sentence recognition in noise with Mandarin, pediatric hearing aid users. Research Design: This study was set up using a double-blind, within-subject, repeated-measures design. Study Sample: Twenty-six children who spoke Mandarin Chinese as their primary language and had bilateral sensorineural hearing loss participated in the study. Data Collection and Analysis: Sentence recognition in noise was evaluated in behind-the-ear technology with both adaptive compression processing and fast-acting WDRC processing and was selected randomly for each child. Percent correct sentence recognition in noise with fast-acting WDRC and adaptive compression was collected from each participant. Correlation analysis was performed to examine the effect of gender, age at assessment, and hearing threshold of the better ear on signal-to-noise ratio, and a paired-samples t test was employed to compare the performance of the adaptive compression strategy and fast-acting WDRC processing. Results: The mean percentage correct of sentence recognition in noise with behind-the-ear technology with fast-acting WDRC and adaptive compression processing were 62.24% and 68.71%, respectively. The paired-samples t test showed that the performance of the adaptive compression strategy was significantly better than the fast-acting WDRC processing (t = 3.190, p = 0.004). Conclusions: Compared with the fast-acting WDRC, adaptive compression provided better sentence recognition in noise for Mandarin pediatric hearing aid users.
Spin-polarized multi-photon photoemission and surface electronic structure of Cu(001)

We have investigated the influence of controlled modifications of the surface electronic structure of Cu(001) on the spin polarization of photoelectrons emitted via multi-photon excitation. Using ultrashort, circularly polarized laser pulses with ∼3 eV photon energy, spin-polarized electrons can be selectively excited from the spin–orbit (SO) coupled d-bands of Cu into the unoccupied n=1 image potential (IP) state on the Cu(001) surface. Upon lowering the IP state energy level by submonolayer Cs deposition, we show that the IP energy can be tuned into two-photon resonance with initial state d-bands of different double group symmetry, leading to a sign reversal of the spin polarization that is observed at the IP state level. Similarly, exploiting the parallel-momentum IP state dispersion, the resonant tuning of the IP state energy level to different branches of the SO split d-bands is demonstrated. Our results highlight the role of resonant and off-resonant excitation pathways in determining the spin polarization in the excited states. The additional information contained in spin-resolved multi-photon photoemission experiments can be exploited to obtain insights into the mechanism of population of excited states.
Design and Analysis of Anytime Codes for Relay Channels

Anytime codes are known to be useful for tracking and controlling unstable systems over noisy channels. Although practical anytime codes have been developed for point-to-point communication, to date no practical code constructions and tractable analysis of anytime codes are known to exist for relay networks. In this paper, we study the design and theoretical analysis of anytime codes for a three-terminal relay network. We propose bilayer codes for anytime transmission over the relay network and consider two transmission schemes for the relay-destination link. For both schemes, we analytically derive the delay-exponents and show that they closely match the corresponding numerical results obtained from density evolution. Through simulation, we also show the finite-length performance of the proposed bilayer anytime code.
Accounting for patient heterogeneity in phase II clinical trials

Phase II clinical trials typically are single‐arm studies conducted to decide whether an experimental treatment is sufficiently promising, relative to standard treatment, to warrant further investigation. Many methods exist for conducting phase II trials under the assumption that patients are homogeneous. In the presence of patient heterogeneity, however, these designs are likely to draw incorrect conclusions. We propose a class of model‐based Bayesian designs for single‐arm phase II trials with a binary or time‐to‐event outcome and two or more prognostic subgroups. The designs' early stopping rules are subgroup specific and allow the possibility of terminating some subgroups while continuing others, thus providing superior results when compared with designs that ignore treatment–subgroup interactions. Because our formulation requires informative priors on standard treatment parameters and subgroup main effects, and non‐informative priors on experimental treatment parameters and treatment–subgroup interactions, we provide an algorithm for computing prior hyperparameter values. A simulation study is presented and the method is illustrated by a chemotherapy trial in acute leukemia. Copyright © 2007 John Wiley & Sons, Ltd.
Are there HLA combinations typical supporting for or making resistant against aggressive and/or chronic periodontitis?

OBJECTIVE AND BACKGROUND Human leukocyte antigens (HLA)/alleles have been considered as risk factors for periodontal disease. However, data from HLA associations is not consistent. Diversity of HLA antigen combinations and en bloc inherited HLA alleles (haplotypes), as known in systemic diseases, can be variable factors in disease association. Therefore, the aim of this study was to investigate the incidence of HLA homozygosities, heterozygosities and estimated haplotypes in German Caucasian groups with generalized aggressive (N = 50) and chronic (N = 102) periodontitis in comparison to control probands without periodontitis (N = 102). METHODS HLA-A, -B, -Cw, -DRB1, -DRB3/4/5, -DQB1 typing was carried out using both serologic (microlymphocytotoxicity test) and genomic (PCR-SSP: PCR with sequence specific primers) techniques. Frequencies of all homozygosities, heterozygosities and haplotypes were determined in all patients and controls. RESULTS In both patient groups, associations to HLA homozygosities and heterozygosities were found. Most striking was the significantly lower frequency of HLA-DRBblank* homozygosity (non-DRB3*/DRB4*/DRB5*) in chronic periodontitis (p < 0.05), whereas HLA-DRB1*15 : DRB5*(DR51) : DQB1*06 showed a slightly higher homozygosity rate in all patients. As the combination HLA-A*02,A*03 was significantly decreased in aggressive periodontitis (p < 0.05), HLA-A*01,A*03 heterozygosity was significantly lowered in chronic periodontitis (p < 0.05). Among others, the known positive associations for HLA-A*68/69 (A28) and HLA-DRB1*04 were confirmed by the haplotypes HLA-A*68/69 : Cw*07 : B*18 in aggressive periodontitis (p < 0.05) and HLA-Cw*08 : B*14 : DRB1*04 in chronic periodontitis (p < 0.05). CONCLUSION The present study elucidates the variety of HLA associations and therefore the difficulty to assign single HLA markers to periodontal disease. Susceptibility/resistance of both aggressive and chronic periodontitis may rather be influenced by particular HLA marker combinations. Associated HLA haplotypes may be of further importance for unknown gene loci representing a part of the genetic background for periodontitis. The different associations in aggressive and chronic periodontitis indicate different susceptibility/resistance factors for both diseases.
A systematic approach to local stability analysis of cardiovascular baroreflex

This paper presents a novel systematic approach to the stability analysis of the cardiovascular (CV) baroreflex. The proposed approach determines the equilibrium state and the system stability in its neighbourhood with computational efficiency, once the parameters of the CV baroreflex model are specified for an individual. We first propose a linearization-based analytical method for determining the equilibrium state of the CV baroreflex. We then present a Lyapunov-based systematic approach to analyze the system stability in the neighbourhood of the equilibrium state. The results of simulation experiments suggest that the performance of the proposed approach is encouraging: it was able to accurately determine the equilibrium state and quantify the stability of the CV baroreflex. The proposed approach is also powerful in exploring the relationship between the CV baroreflex stability and its parameter configurations.