Miracle-dz/UniFAR-FTUs huggingface dataset:
A drug–drug interaction study with letermovir and acyclovir in healthy participants

Letermovir inhibits renal tubular organic anion transporter 3 (OAT3) in vitro and is predicted to inhibit OAT3 in vivo. Acyclovir, a substrate for OAT3, is likely to be coadministered with letermovir; therefore, letermovir may increase acyclovir concentrations. A drug–drug interaction study was conducted in healthy participants (N = 16) to assess the effect of letermovir on acyclovir pharmacokinetics. On Day 1, participants received a single oral dose of 400 mg acyclovir; on Days 2–7, participants received oral doses of 480 mg letermovir once daily with a single oral dose of 400 mg acyclovir coadministered on Day 7. Coadministration with letermovir resulted in geometric mean ratios (90% confidence intervals) for acyclovir area under the concentration–time curve from administration to infinity and maximum plasma concentration of 1.02 (0.87–1.20) and 0.82 (0.71–0.93), respectively. No notable safety issues were reported. No clinically significant interaction was observed between letermovir and acyclovir in healthy participants and no dose adjustment is required for coadministration.
Negative association between high temperature-humidity index and milk performance and quality in Korean dairy system: big data analysis

Abstract The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.
‘Put in a room and left’: a qualitative study exploring the lived experiences of COVID-19 isolation and quarantine among rehabilitation inpatients

Abstract Background The SARS-CoV-2 (COVID-19) pandemic has resulted in significant changes to health care delivery and the patient’s experience in hospital. Changes for those who contracted COVID-19 or were close contacts included isolation and quarantine, visitor restrictions and changes to usual models of care to reduce viral transmission. Traditional models of inpatient rehabilitation utilise communal spaces (e.g. shared gyms and dining rooms) and involve a multidisciplinary team interacting with the patient daily. Objectives To report the experience of COVID-19 related isolation and quarantine among rehabilitation inpatients and their family members who experienced a nosocomial outbreak and to make recommendations for rehabilitation units. Methods A qualitative phenomenological methodology using semi-structured telephone interviews. Results 19 semi-structured interviews were conducted comprising of 13 general rehabilitation inpatients and 6 family members. Five themes were established: (1) the impact of social and physical isolation; (2) boredom and limited access to therapy; (3) the impact of technology; (4) inadequate information sharing and (5) positive experiences and things done well. Several novel insights were identified including: the desire for increased social interaction from staff to compensate for a lack of visitors; the impact of physical and cognitive deficits on a patient’s ability to reach basic items around their room or call for help, and the unique impact of isolation and quarantine on individuals who have a history of trauma, discrimination or mental illness. Conclusions This study establishes key areas that should be considered by rehabilitation units globally to adjust traditional models which are not suitable in this pandemic. Strategies to mitigate the impact of isolation include providing training to increase use of technologies such as tablet devices, increased staff social engagement to reduce isolation and tailoring the environment to suit specific patient groups. KEY MESSAGES COVID-19 related isolation and quarantine has a significant and unique impact on patients with cognitive and physical impairments such as those in inpatient rehabilitation. Patients who are required to isolate in inpatient settings expressed a desire for compensatory increased social interaction from staff and required specific assistance with basic daily tasks while isolated. The study makes key recommendations for other rehabilitation units to integrate into their approach for managing patients required to isolate or quarantine.
A review of techniques for morphological analysis in natural language processing

Natural language is a crucial tool to facilitate communication in our day-to-day activities. This can be achieved either in text or speech forms. Natural language processing (NLP) involves making computers understand and process natural language. NLP has enhanced the way humans interact with computers, from having computers use speech to talk to humans as well as having computers translate human speech. Apart from speech, computers also create and understand sentences in natural language in a process called morphological analysis. Morphological analysis is an important part in natural language processing, being applied as a preprocessing step in most NLP tasks. Morphological analysis consists of four subtasks, that is, lemmatization, part-of-speech (POS) tagging, word segmentation and stemming. In this paper, we explore in detail each of these tasks of morphological analysis. We then evaluate the techniques used in this NLP field. Finally, we give a summary of the results of each of these techniques
Diffusion Normalized Maximum Versoria Criterion Robust to Impulsive Noise

In this brief, we propose a new diffusion normalized maximum Versoria criterion (d-NMVC) algorithm, which is based on maximization of the normalized maximum Versoria criterion (MVC) cost function to enhance the performance of the distributed estimation over networks in the presence of non-Gaussian noise. Convergence of the proposed algorithm, in the mean square sense and evolution behavior, under impulsive noise environment is also analyzed. Simulation results show the robustness of the proposed algorithm under impulsive noise environment against various non-Gaussian noise distributions.
Reconciling the Context-Dependency and Domain-Generality of Executive Function Skills from a Developmental Systems Perspective

ABSTRACT Executive function (EF) skills are a set of attention-regulation skills involved in intentional, goal-directed behavior that include (but are not limited to) the cool EF skills of working memory, cognitive flexibility, and inhibitory control, and also the hot EF skill of intentional reevaluation. These skills are inevitably expressed in goal- and context-dependent ways, leading some to view EF skills as specific adaptations to particular problems and reinforcing interest in the use of more ecologically contextualized assessments. Appreciation of the context-dependency of EF skills adds to our understanding of how EF skills develop as a consequence of particular experiences and how they contribute to key developmental outcomes. There are good reasons, however, to view EF skills as relatively domain-general neurocognitive skills. Measured using standardized direct behavioral assessments, these skills are associated reliably with well-defined but distinct neural networks; they predict long-term developmental outcomes; and they can be trained in ways that produce far transfer. We argue that developmental systems models of EF skills can reconcile views of EF skills as relatively domain-general and views that emphasize the context-dependency of these skills. Ecologically adapted measures of EF skills can complement standardized measures that capture important age-related and individual differences and should remain a cornerstone of research on the topic. We believe this type of model will facilitate a deeper understanding of how multiple, simultaneous, and interacting causal influences, operating at many levels of analysis (cultural, social, cognitive, neural, and molecular), work together to produce conscious control.
Wave interactions with continuous fractal layers

Many natural structures possess self-similar multiscales which can be characterized by power law spectra. Under appropriate conditions, knowledge of the strength of these scale sizes provides information on the physical processes which form these objects. In this paper, we investigate wave interactions with continuous fractal layers which model geological and variegated structures. Since fractal characteristics of the layers are embedded in the scattered field, they can be retrieved under appropriate conditions. This inversion can be performed in either the frequency or the time domain as desired.
Random networks of carbon nanotubes as an electronic material

We report on the transport properties of random networks of single-wall carbon nanotubes fabricated into thin-film transistors. At low nanotube densities (∼1 μm−2) the networks are electrically continuous and behave like a p-type semiconductor with a field-effect mobility of ∼10 cm2/V s and a transistor on-to-off ratio ∼105. At higher densities (∼10 μm−2) the field-effect mobility can exceed 100 cm2/V s; however, in this case the network behaves like a narrow band gap semiconductor with a high off-state current. The fact that useful device properties are achieved without precision assembly of the nanotubes suggests the random carbon nanotube networks may be a viable material for thin-film transistor applications.
Improved PLS algorithms

In this paper a proof is given that only one of either the X‐ or the Y‐matrix in PLS algorithms needs to be deflated during the sequential process of computing latent vectors. With the aid of this proof the original kernel algorithm developed by Lindgren et al. (J. Chemometrics, 7, 45 (1993)) is modified to provide two faster and more economical algorithms. The performances of these new algorithms are compared with that of De Jong and Ter Braak's (J. Chemometrics, 8, 169 (1994)) modified kernel algorithm in terms of speed and the new algorithms are shown to be much faster. A very fast kernel algorithm for updating PLS models in a recursive manner and for exponentially discounting past data is also presented. © 1997 John Wiley & Sons, Ltd.
Beam hardening and partial beam hardening of the bowtie filter: Effects on dosimetric applications in CT

Purpose: To estimate the consequences on dosimetric applications when a CT bowtie filter is modeled by means of full beam hardening versus partial beam hardening. Method: A model of source and filtration for a CT scanner as developed by Turner et. al. [1] was implemented. Specific exposures were measured with the stationary CT X-ray tube in order to assess the equivalent thickness of Al of the bowtie filter as a function of the fan angle. Using these thicknesses, the primary beam attenuation factors were calculated from the energy dependent photon mass attenuation coefficients and used to include beam hardening in the spectrum. This was compared to a potentially less computationally intensive approach, which accounts only partially for beam hardening, by giving the photon spectrum a global (energy independent) fan angle specific weighting factor. Percentage differences between the two methods were quantified by calculating the dose in air after passing several water equivalent thicknesses representative for patients having different BMI. Specifically, the maximum water equivalent thickness of the lateral and anterior-posterior dimension and of the corresponding (half) effective diameter were assessed. Results: The largest percentage differences were found for the thickest part of the bowtie filter and they increased with patient size. For a normal size patient they ranged from 5.5% at half effective diameter to 16.1% for the lateral dimension; for the most obese patient they ranged from 7.7% to 19.3%, respectively. For a complete simulation of one rotation of the x-ray tube, the proposed method was 12% faster than the complete simulation of the bowtie filter. Conclusion: The need for simulating the beam hardening of the bow tie filter in Monte Carlo platforms for CT dosimetry will depend on the required accuracy.
3‐D spatio–temporal structures of biofilms in a water channel

We develop a numerical predictive tool for multiphase fluid mixtures consisting of biofilms grown in a viscous fluid matrix by implementing a second‐order finite difference discretization of the multiphase biofilm model developed recently on a general purpose graphic processing unit. With this numerical tool, we study a 3‐D biomass–flow interaction resulting in biomass growth, structure formation, deformation, and detachment phenomena in biofilms grown in a water channel in quiescent state and subject to a shear flow condition, respectively. The numerical investigation is limited in the viscous regime of the biofilm–solvent mixture. In quiescent flows, the model predicts growth patterns consistent with experimental findings for single or multiple adjacent biofilm colonies, the so‐called mushroom shape growth pattern. The simulated biomass growth both in density and thickness matches very well with the experimentally grown biofilm in a water channel. When shear is imposed at a boundary, our numerical studies reproduce wavy patterns, pinching, and streaming phenomena observed in biofilms grown in a water channel. Copyright © 2014 John Wiley & Sons, Ltd.
GRMHD Evolution of Interacting Double Accretion Tori Orbiting a Central Black Hole

The matter orbiting black holes (BHs) in microquasars or active galactic nuclei forms toroidal accretion disk structures, and multiple torus structures have been recently described as ringed accretion disks (RADs) in a full general relativistic approach. Here we realize full general relativistic magnetohydrodynamic (GRMHD) numerical simulations related to double toroidal structure immersed in the equatorial plane of the gravitomagnetic field of a central Schwarzschild BH in an asymptotically uniform magnetic field. We study the merging dynamics of an initial RAD structure constructed by two corotating or counterrotating tori, where accretion of matter from the outer torus is assumed onto the inner torus, using the 2.5D GRMHD simulation schemes with the HARM numerical code. We study the dynamics of the system assuming various initial conditions, and we have demonstrated that the initial matter density is the relevant factor governing the system evolution.
Efficient Reduced-Order System Identification for Linear Systems with Multiple Inputs

A new, efficient discrete-time-domain system identification and model reduction method for a large-scaled linear dynamic system with multiple inputs is presented. The method is based on a modification of the classical eigensystem realization algorithm and a simultaneous injection of multiple inputs, so called the single-composite-input method. Because the system response is sampled almost exclusively for the single representative input, this technique can significantly reduce the model construction time as well as the amount of the sampled data. For derivation of the new algorithm, the singular value decomposition is performed using output measurements that are not necessarily attributed to pulse inputs. Application to general computational-fluid-dynamic systems and formulation of reduced-order aeroelastic models are also presented. The efficiency and accuracy of the method is demonstrated via a simple aeroelastic system, which is modeled by the three-dimensional vortex lattice and a six-degrees-of-freedom plate-like structure.
Geometric optimization of an active magnetic regenerative refrigerator via second-law analysis

Previous analyses [Z. Yan and J. Chen, J. Appl. Phys. 72, 1 (1992); J. Chen and Z. Yan, ibid., 84, 1791 (1998); Lin et al., Physica B 344, 147 (2004); Yang et al., ibid., 364, 33 (2005); Xia et al., ibid., 381, 246 (2006). ] of irreversibilities in magnetic refrigerators overlooked several important losses that could be dominant in a real active magnetic regenerative refrigerator (AMRR). No quantitative expressions have been provided yet to estimate the corresponding entropy generations in real AMRRs. The important geometric parameters of AMRRs, such as the aspect ratio of the active magnetic regenerator and the refrigerant diameter, are still arbitrarily chosen. Expressions for calculating different types of entropy generations in the AMRR were derived and used to optimize the aspect ratio and the refrigerant diameter. An optimal coefficient of performance (15.54) was achieved at an aspect ratio of 6.39 and a refrigerant diameter of 1.1mm for our current system. Further study showed that the dissipative s.
Development and validation of the Behavioral Health Acuity Risk model: a predictive model for suicide prevention through clinical interventions

Common suicidal ideation screening tools used in healthcare settings rely on the willingness of the patient to express having suicidal thoughts. We present an automatic and data-driven risk model that examines information available in the medical record captured during the normal course of care. This model uses random forests to assess the likelihood of suicidal behavior in patients aged seven or older presenting at any healthcare setting. The Behavioral Health Acuity Risk (BHAR) model achieves an area under the receiver operating curve (AUC) of 0.84 and may be used on its own or as a component of a comprehensive suicidal behavior risk assessment.
Aberrational weight adjustment by tolerance-based weighting in damped least squares optimization

This paper presents a method of automatically adjusting aberrational weighting factors in a damped least squares optimization program, based on tolerance data provided for each aberration site. The method which is based on previous work by the authors and that of Yao has been developed into a tolerance-based method for aberrational weight adjustment. This enhanced method allows the user to set and adjust weights by a new tolerance-based method. The use of a power index ((rho) ) in the tolerance-based method provides continuously variable control over the amount by which the aberrational weights are adjusted. The practical use of the tolerance-based method is demonstrated using simple and well understood test lenses to reveal the modifications that take place within the iterative design progress, that result from aberrational weight adjustment. Suggestions for suitable tolerance schemes have also been investigated as an integral part of this work, based on the work of Hopkins.
Comparing Autobiographical Brand Images and Neutral Images Regarding False Memory Formation

Introduction: Consumers’ prior experiences form an episodic memory that largely influences their decision-making process. This episodic memory is mainly linked to cognitive and emotional perception and we know that brand image influences our cognitive and emotional perception. Nevertheless, it has not been well described how autobiographical memories of brand images differ from other types of images. Methods: In this study, we hypothesized that brand pictures have a higher chance to create false memories as compared to neutral ones. Results: We investigated this hypothesis using the Deese–Roediger–McDermott paradigm with lists of brand pictures from the local market and associated neutral images from the international affective picture system. Thirty graduate students were exposed to image stimuli, followed by a distractor task and a recognition task. After the normality test, reaction times (RT), and false recognition rate of brands and neutral images were statistically compared using a pairwise t-test. Conclusion: The results showed a significant decrease in reaction time (RT) and an increase in the false recognition rate of brand pictures compared to neutral images. Interestingly, the effect of gender on the creation of false memory by autobiographical brand images was not significant. We hope these findings can pave the way for a better understanding of the false memory mechanism. Highlights Autobiographical brand images give a higher chance of false memory as compared to neutral images Men and women do not differ in the formation of false memory Reaction time in false memory is longer than in true memory. False positives create more cognitive load. Plain Language Summary We see many images around us every day, such as the image of different brands in our daily shopping, which puts us in front of different types of images, many of which are old, these brands become part of our life memories, and their images are aspects of autobiography. Therefore, these brands can form false memories for people. The image stimuli of this study are to investigate whether these images can form false memories or not. The results showed that the images that we see every day in the street of the supermarket and can change our memories.
Preferred music-listening level in musicians and non-musicians

The purpose of this study was to establish whether preferred music-listening level differed between musicians and non-musicians, and whether preferred music-listening level was related to music genre preference and lifetime noise exposure. Seventeen musicians (mean age = 29.06 years, SD = 4.74; female n = 9) and 17 non-musicians (mean age = 28.94 years, SD = 4.63; female n = 9) with clinically normal hearing were recruited to listen to six music samples from different genres and one sample of environmental sounds. Participants adjusted the listening level [dB(A)] until the music was loud and enjoyable. This was repeated three times and an average was taken. Lifetime noise exposure was estimated using the Noise Exposure Structured Interview. Preferred music-listening levels of musicians were significantly higher than non-musicians. The preferred music-listening level differed with genre preference, with the participants’ favorite tracks being played at 11 dB higher level than the least favorite tracks. There was also a positive correlation between lifetime noise exposure and preferred music-listening level. Musicians prefer to listen to music at higher level than non-musicians and thus may be more susceptible to noise induced hearing loss than non-musicians. As such, musicians in particular would benefit from simple changes in lifestyle and listening habits, including increased awareness of the risks of higher listening levels, as well as the use of hearing protection.
Tailoring freeform lenses for illumination

The general problem to find the shape of a refractive surface such as to produce a desired brightness distribution on a given target surface from a known point source leads to a boundary value problem with an elliptic partial differential equation of the Monge-Ampere type. This equation has been described and analyzed in the literature. The purpose of our contribution is to present a venue for a numerical solution as well as several solved examples. The essence of our algorithm for a numerical solution appears to be the explicit incorporation of the condition for the existence of a pseudopotential for a normal vector field.