Miracle-dz/UniFAR-FTUs huggingface dataset:
High sensitivity LPG Mach–Zehnder sensor for real-time fuel conformity analysis

A high sensitivity refractive index sensor based on the combination of mechanically induced long period gratings (LPG) and fiber tapers was developed for real-time fuel quality analysis. The sensor was built in a Mach–Zehnder configuration by employing a pair of in-series gratings. In order to enhance sensor sensitivity, the region between both LPGs was tapered down from 125 to 10 µm. The system was tested by measuring water concentration in ethanol and ethanol concentration in commercial gasoline. The tapered sensor has shown an average sensitivity of 930 nm/RIU, 18 times higher than the non-tapered version. The resolution limit of the system using spectral interrogation was estimated to be 0.06% of ethanol dissolved in gasoline. For the purpose of real-time monitoring, an interrogation system based on white light interferometry (WLI) and virtual instrumentation was employed to evaluate ethanol evaporation in water, avoiding the use of spectral analysis. The WLI system, using phase tracking techniques, enabled us to record the evolution of the ethanol concentration in water with a resolution of 0.005% (v/v).
Visual Interaction Perceptual Network for Blind Image Quality Assessment

In observing images, the perception of the human visual system (HVS) is affected by both image contents and distortions. Obviously, the visual quality of the same image varies under different distortion types and intensities. Furthermore, the visual masking effects reveal that image content and distortion have a visual interaction, where the HVS presents different visibility of the identical distortion for different image contents. Based upon this, we propose a visual interaction perceptual network that can perceive both content and distortion of an image. The proposed model consists of three sub-modules: content perception module (CPM), distortion perception module (DPM), and visual interaction module (VIM). However, the subjective quality score cannot guide the model to explicitly learn the feature representations of image content and distortion. Thus, we perform a two-stage training procedure. In the first stage, we obtain CPM and DPM, where semantic features are extracted to recognize the image content in CPM, and distortion features are extracted to capture the image distortion type and intensity in DPM. In the second stage, the VIM is applied to model the interaction between semantic and distortion features, and the final predicted quality score is given by a fully connected layer. Experimental results demonstrate that the proposed method can achieve state-of-the-art performance on multiple benchmark databases, e.g., CSIQ, TID2013, KADID-10K, and KonIQ-10 K.
Effect of magnetic field geometry on the wave signature of the pickup of interstellar neutrals

By using the technique of Johnstone et al. (1991), the asymptotic wave spectrum induced by the pickup of interstellar ions in the heliosphere is derived. This approach is independent of quasi-linear theory. The asymptotic wave spectrum is calculated from the standard resonance condition by assuming that the asymptotic ion distribution is bispherical and by using conservation of energy. The calculation places no restriction on either the ratio of Alfven speed to solar wind flow speed or the particle pitch angle. Spectra for various geometries (relative orientations of the magnetic field and solar wind velocity) are calculated. Absolute upper limits to the expected wave enhancements are calculated. These upper limits are compared to the background fluctuation spectrum extrapolated from 0.87 AU, assuming a spectral index of −5/3 and radial dependences of −2 and −3. The heliocentric radial distances at which the peaks in the various geometry-dependent wave spectra are expected to be observable above the background are identified. Peaks due to pickup hydrogen at the proton gyrofrequency are found to be always stronger relative to the background in parallel than in perpendicular geometries. Depending on how the background varies with heliocentric radius, this peak should be observable at 5-10 AU in parallel geometries; 10-50 AU in perpendicular geometries. The parallel-geometry excitations consist only of sunward propagating waves. In perpendicular geometries a peak also occurs, this time near 0.1 of the proton gyrofrequency (corresponding to the peak calculated by Lee and Ip (1987)). However, the steep spectral dependence of the ambient wave field makes it unlikely that this peak will be observed inside 20 AU. A similar result holds for the case of pickup-helium induced excitation at the helium gyrofrequency. Inside 10 AU, peaks at these lower frequencies tend to be obscured by the steep frequency dependence (∝ −5/3) of the ambient spectrum and then are only observable in parallel geometries.
Ca2+- and Voltage-Activated K+ (BK) Channels in the Nervous System: One Gene, a Myriad of Physiological Functions

BK channels are large conductance potassium channels characterized by four pore-forming α subunits, often co-assembled with auxiliary β and γ subunits to regulate Ca2+ sensitivity, voltage dependence and gating properties. BK channels are abundantly expressed throughout the brain and in different compartments within a single neuron, including axons, synaptic terminals, dendritic arbors, and spines. Their activation produces a massive efflux of K+ ions that hyperpolarizes the cellular membrane. Together with their ability to detect changes in intracellular Ca2+ concentration, BK channels control neuronal excitability and synaptic communication through diverse mechanisms. Moreover, increasing evidence indicates that dysfunction of BK channel-mediated effects on neuronal excitability and synaptic function has been implicated in several neurological disorders, including epilepsy, fragile X syndrome, mental retardation, and autism, as well as in motor and cognitive behavior. Here, we discuss current evidence highlighting the physiological importance of this ubiquitous channel in regulating brain function and its role in the pathophysiology of different neurological disorders.
Very high-speed light-source module up to 40 Gb/s containing an MQW electroabsorption modulator integrated with a DFB laser

A very high-speed integrated light source up to 40 Gb/s has been developed. The InGaAsP MQW integrated light source consists of an multiple-quantum-well (MQW) electroabsorption (EA) modulator and a distributed-feedback (DFB) laser. After optimizing the structure of the integrated modulator, the device is packaged in a compact module with a single-mode fiber (SMF). While the DFB laser is injected with a constant current, the integrated MQW electroabsorption modulator is driven with a 40-Gb/s electrical NRZ signal. A clearly-open eye diagram is observed in the modulated light from the modulator. Further, a receiver sensitivity of -27.2 dBm at 10/sup -9/ is experimentally confirmed in bit-error-rate (BER) performance. Highly resolved optical short pulse is also generated at a repetition rate of 40 GHz using the new light-source module.
The EM algorithm and extensions

The first unified account of the theory, methodology, and applications of the EM algorithm and its extensionsSince its inception in 1977, the Expectation-Maximization (EM) algorithm has been the subject of intense scrutiny, dozens of applications, numerous extensions, and thousands of publications. The algorithm and its extensions are now standard tools applied to incomplete data problems in virtually every field in which statistical methods are used. Until now, however, no single source offered a complete and unified treatment of the subject.The EM Algorithm and Extensions describes the formulation of the EM algorithm, details its methodology, discusses its implementation, and illustrates applications in many statistical contexts. Employing numerous examples, Geoffrey McLachlan and Thriyambakam Krishnan examine applications both in evidently incomplete data situations-where data are missing, distributions are truncated, or observations are censored or grouped-and in a broad variety of situations in which incompleteness is neither natural nor evident. They point out the algorithm's shortcomings and explain how these are addressed in the various extensions.Areas of application discussed include: Regression Medical imaging Categorical data analysis Finite mixture analysis Factor analysis Robust statistical modeling Variance-components estimation Survival analysis Repeated-measures designs For theoreticians, practitioners, and graduate students in statistics as well as researchers in the social and physical sciences, The EM Algorithm and Extensions opens the door to the tremendous potential of this remarkably versatile statistical tool.
Potentials from the Polynomial Solutions of the Confluent Heun Equation

Polynomial solutions of the confluent Heun differential equation (CHE) are derived by identifying conditions under which the infinite power series expansions around the z=0 singular point can be terminated. Assuming a specific structure of the expansion coefficients, these conditions lead to four non-trivial polynomials that can be expressed as special cases of the confluent Heun function Hc(p,β,γ,δ,σ;z). One of these recovers the generalized Laguerre polynomials LN(α), and another one the rationally extended X1 type Laguerre polynomials L^N(α). The two remaining solutions represent previously unknown polynomials that do not form an orthogonal set and exhibit features characteristic of semi-classical orthogonal polynomials. A standard method of generating exactly solvable potentials in the one-dimensional Schrödinger equation is applied to the CHE, and all known potentials with solutions expressed in terms of the generalized Laguerre polynomials within, or outside the Natanzon confluent potential class, are recovered. It is also found that the potentials generated from the two new polynomial systems necessarily depend on the N quantum number. General considerations on the application of the Heun type differential differential equations within the present framework are also discussed.
The Emotional Resilience Scale (ERS): Measuring employee well-being

Abstract The COVID-19 pandemic has had a severe impact on employees’ well-being and business outcomes throughout the world. The purpose of the present study was to develop a short measure of well-being to identify vulnerable employees. The Emotional Resilience Scale (ERS) was validated in a longitudinal design, using a sample of 193 participants. Results revealed high internal and test-retest reliability. Factor Analysis showed that the ERS is best viewed as unidimensional. The ERS exhibited a strong association with the mental health continuum (short form) measure, and moderate associations with emotional exhaustion and job satisfaction. Implications and limitations for future research are discussed.
3D-Printed, Liquid-Filled Capsules of Concentrated and Stabilized Polyphenol Epigallocatechin Gallate, Developed in a Clinical Trial

In vitro studies have shown that epigallocatechin gallate (EGCG), the most potent antioxidant of the green tea polyphenol catechins, is able to effectively prevent the formation of amyloid plaques and induce their clearance. However, its high chemical reactivity promotes high chemical instability, which represents a major obstacle for the development of pharmaceutical forms containing solubilized EGCG, an essential condition for a better systemic passage via the oral route. After discovering that EGCG forms a deep eutectic with choline chloride, we exploited this property to formulate and patent liquid-filled capsules containing 200–800 mg of soluble EGCG in easy-to-administer sizes. The gelatin envelopes used are of the conventional type and their filling has been achieved using 3D printing technology. Not only did the EGCG-choline complex allow the formulation of hydrophilic solutions with a high concentration of active substance but it also contributed significantly to its chemical stability, since after at least 18 months of storage at 25 °C/60% RH and one year at 40 °C/75% RH, the capsules show unchanged hardness, chromatographic profiles and antioxidant activity compared to T0. Preclinical studies in monkeys showed that bioavailability was increased by a factor of 10 compared to marketed capsules comprising EGCG powder. This pharmaceutical development was conducted in the context of upcoming clinical trials to evaluate EGCG alone or in combination when treating transthyretin and light-chain cardiac amyloidosis.
Markov Random Fields with Higher‐order Interactions

Discrete‐state Markov random fields on regular arrays have played a significant role in spatial statistics and image analysis. For example, they are used to represent objects against background in computer vision and pixel‐based classification of a region into different crop types in remote sensing. Convenience has generally favoured formulations that involve only pairwise interactions. Such models are in themselves unrealistic and, although they often perform surprisingly well in tasks such as the restoration of degraded images, they are unsatisfactory for many other purposes. In this paper, we consider particular forms of Markov random fields that involve higher‐order interactions and therefore are better able to represent the large‐scale properties of typical spatial scenes. Interpretations of the parameters are given and realizations from a variety of models are produced via Markov chain Monte Carlo. Potential applications are illustrated in two examples. The first concerns Bayesian image analysis and confirms that pairwise‐interaction priors may perform very poorly for image functionals such as number of objects, even when restoration apparently works well. The second example describes a model for a geological dataset and obtains maximum‐likelihood parameter estimates using Markov chain Monte Carlo. Despite the complexity of the formulation, realizations of the estimated model suggest that the representation is quite realistic.
Ethnic-Regional Differences in the Allocation of High Complexity Spending in Brazil: Time Analysis 2010–2019

The following paper presents as a research problem the ethnic-regional differences in the allocation of high complexity spending in Brazil in an analysis from 2010 to 2019. This is a descriptive research in which a generalized linear model (GLM) was developed to analyze these hospital expenditures with high complexity procedures. The total spending on high complexity procedures in Brazil has increased over the past decade. The study shows that the lowest average expenditures are found in the North and Northeast regions. When comparing the spending between different ethnicities, it was observed that the only decrease between the years 2010 and 2019 was in the amount spent on procedures in indigenous people. The spending on male patients was significantly higher compared to female patients. The highest expenditures, on the other hand, are concentrated in the regions of state capitals favoring the strengthening of hub municipalities. Geographic inequalities in access still persist, even with most states already offering almost all procedures. The Brazilian territory is very heterogeneous and needs to organize its health system by regions, therefore integrated public policies and economic and social development are urgently needed.
Intelligent Reflecting Surfaces for Sum-Rate Maximization in Cognitive Radio Enabled Wireless Powered Communication Network

In this paper, we study a cognitive radio (CR)-enabled wireless powered communication network (WPCN) with an intelligent reflecting surface (IRS). A cognitive wireless powered communication network (CWPCN) consisting of one secondary wireless powered communication network, in which a hybrid access point broadcasts wireless energy to multiple users on downlink and receives information signals on uplink, shares the same spectrum with the existing primary wireless communication network. In this paper, we consider an underlay CWPCN in which the secondary network is regulated by a given interference temperature constraint (ITC) such that interference with the primary network is kept no greater than a predefined threshold. To enhance the performance of the CWPCN, we consider an IRS-assisted network in which multiple passive reflection elements are configured to reflect the signals in any desired phase/direction. Our main goal is to maximize the sum throughput of secondary users while managing the interference constraint. For this, we jointly optimize the uplink and downlink phase shift matrices of the IRS elements with optimal time slots for wireless energy transfer (WET) on downlink and wireless information transfer on uplink. In finding the optimal solution, the formulated optimization problem is non-convex, complex, and intractable. In this paper, we propose an alternating optimization (AO)-based solution with a successive convex approximation (SCA) technique. We show through simulation results that the proposed IRS-assisted network provides a significant enhancement in performance over the conventional CWPCN.
On the acceleration of convergence of many-body perturbation theory. I: General theory

The theoretical background of schemes for accelerating convergence of Moller-Plesset-Goldstone perturbation theory is discussed. Aiming at practical applications the authors consider approximate formulations of the many-body theory of atoms and molecules in finite-dimensional Hilbert spaces. A key role is played by nearby singularities of energy levels and eigenfunctions considered as functions of a suitably chosen coupling parameter. Infinite subsummations in the perturbation series are performed such that the influence of these singularities is eliminated or, at least, sufficiently attenuated. The danger of double counting of diagrammatic contributions already included in these infinite subsummations is avoided by the very construction of the authors' scheme.
280. Accuracy of genomic prediction of dry matter intake in Dutch Holsteins using sequence variants from meta-analyses

We evaluated the accuracy of biology informed genomic prediction for dry matter intake in 2,162 Dutch Holstein cows. Sequence variants were selected from meta-analyses including GWAS summary statistics for QTL and metabolomic QTL in several dairy and crossbred beef populations. Selected variants were prioritized in GBLUP models in a five-fold cross-validation. The accuracies were compared to genomic prediction based on routine 50k genotype data. The average accuracy for the 50k scenario was 0.683. Adding selected sequence variants in the GBLUP model did not improve the accuracies for dry matter intake. Next steps will include testing Bayesian variable selection methods to prioritize variants in genomic prediction for dry matter intake.
Designing Measurement Studies Under Budget Constraints: Controlling Error of Measurement and Power

When designing measurement studies, one generally needs to consider two statistical issues: power and measurement error. The mean error variance-covariance component is introduced as an estimate that takes into account both of these statistical issues. This article presents a methodology for minimizing the mean error variance-covariance component in studies with resource constraints. The method is illustrated using a one-facet multivariate design, and extensions to other designs are discussed.
Effects of adult ADHD on intimate partnerships

ABSTRACT Although research on adult ADHD has become more prevalent since the condition’s recognition in the 1990s, information remains scarce about if and how it impacts functionality in relationships. Adults with ADHD can experience interpersonal relationship difficulties due to the disorder’s signature symptoms of hyperactivity, impulsivity, and inattentiveness, as well as due to adult ADHD’s oft-observed dimension of emotional lability. Adults with ADHD tend to have more trouble navigating romantic relationships and are more likely to be divorced than adults without ADHD. The purpose of this paper is to perform a systematic literature review of empirically based studies of integrative couples therapy wherein at least one partner struggles with adult ADHD. Future research, gaps in the literature, and practice implications also are discussed, including hope for focus on the positive aspects of ADHD for individuals and partnerships.
The Clinical Predictive Score for Prehospital Large Vessel Occlusion Stroke: A Retrospective Cohort Study in the Asian Country

Background Large vessel occlusive (LVO) stroke causes severe disabilities and occurs in more than 37% of strokes. Reperfusion therapy is the gold standard of treatment. Studies proved that endovascular thrombectomy (EVT) is more beneficial and decreases mortality. This study aimed to evaluate the factor associated with LVO stroke in an Asian population and to develop the scores to predict LVO in a prehospital setting. The score will hugely contribute to the future of stroke care in prehospital settings in the aspect of transferal suspected LVO stroke patients to appropriate EVT-capable stroke centers. Methods This study was a retrospective cohort study using an exploratory model at the emergency department of Ramathibodi Hospital, Bangkok, Thailand, between January 2018 and December 2020. We included the stroke patients aged >18 who visit ED and an available radiologic report representing LVO. Those whose stroke onset was >24 hours and no radiologic report were excluded. Multivariable logistic regression analysis developed the prediction model and score for LVO stroke. Results A total of 252 patients met the inclusion criteria; 61 cases (24%) had LVO stroke. Six independent factors were significantly predictive: comorbidity with atrial fibrillation, clinical hemineglect, gaze deviation, facial palsy, aphasia, and cerebellar sign abnormality. The predicted score had an accuracy of 92.5%. The LVO risk score was categorized into three groups: low risk (LVO score <3), moderate risk (LVO score 3–6), and high risk (LVO score >6). The positive likelihood ratio to predicting LVO stroke were 0.12 (95% CI 0.06–0.26), 2.33 (95% CI 1.53–3.53) and 45.40 (95% CI 11.16–184.78), respectively. Conclusion The Large Vessel Occlusion (LVO) Risk Score provides a screening tool for predicting LVO stroke. A clinical predictive score of ≥3 appears to be associated with LVO stroke.
A three-group discrimination using new linear programming model

The applications that are related to classification problem are wide-ranging. In fact, differentiating between patients with strong prospects for recovery and those highly at risk, between good credit risks and poor ones, or between promising new firms and those likely to fail are among the most known of these applications. To solve such classification problem, several approaches have been applied, such as the parametric procedures and the non-parametric procedures. This paper aims at developing a new technique to resolve the three-group classification problems. This approach is based on the linear programming models. To evaluate the efficiency of our model, the three-group classification problems were compared with two other traditional classification methods, namely, linear discriminant analysis and classification tree. The results obtained are found to be satisfactory. The performance of the new approach, a parametric statistical technique and a non-parametric method is then evaluated on a data set.