bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suboptimal Weight Loss 13 Years After Roux-en-Y Gastric Bypass: Is Hedonic Hunger, Eating Behaviour and Food Reward to Blame?
Authors: Nymo Siren , Børresen Skjølsvold Oda , Aukan Marthe , Finlayson Graham , Græslie Hallvard , Mårvik Ronald , Kulseng Bård , Sandvik Jorunn , Martins Catia 
Published: May 2022

AbstractPurposeSuboptimal weight loss (SWL) and weight regain (WR) following bariatric surgery are common. The exact reasons for this phenomenon remain to be fully elucidated. To compare hedonic hunger, food preferences, food reward and eating behaviour traits between participants with SWL and optimal weight loss (OWL) 13 years after Roux-en-Y gastric bypass (RYGB).Materials and MethodCross-sectional case control study where participants experiencing SWL or OWL (< or ≥ 50% of excess weight, respectively) post-RYGB were compared to a non-surgical control group matched for pre-operative body mass index. Hedonic hunger (Power of Food Scale), implicit and explicit liking and wanting for high-fat and low-fat savoury and sweet food (Leeds Food Preference Questionnaire) and eating behaviour (Dutch Eating Behavior Questionnaire, Three-Factor Eating Questionnaire and the Food Cravings Questionnaires State and Trait-reduced) were assessed.ResultsIn total, 75 participants were recruited from the bariatric surgery observation study (BAROBS). Disinhibition, hunger, emotional, external and restrained eating, frequency of cravings and hedonic hunger were lower in the OWL, compared with the SWL and/or control groups. Implicit wanting and explicit liking and wanting for high-fat savoury and high-fat sweet food were lower, and implicit wanting for low-fat savoury food higher, in the OWL, compared with the SWL and/or control groups.ConclusionSWL 13 years after RYGB is associated with dysfunctional eating behaviours, increased preference and reward for high-fat food and increased hedonic hunger. Future longitudinal studies are needed to establish the cause-effect relationship between these variables.Graphical abstract
Management of Dyslipidemia in Patients with Non-Alcoholic Fatty Liver Disease
Authors: Martin Anna , Lang Sonja , Goeser Tobias , Demir Münevver , Steffen Hans-Michael , Kasper Philipp 
Published: May 2022

Abstract
Purpose of Review
Patients with non-alcoholic fatty liver disease (NAFLD), often considered as the hepatic manifestation of the metabolic syndrome, represent a population at high cardiovascular risk and frequently suffer from atherogenic dyslipidemia. This article reviews the pathogenic interrelationship between NAFLD and dyslipidemia, elucidates underlying pathophysiological mechanisms and focuses on management approaches for dyslipidemic patients with NAFLD.

Recent Findings
Atherogenic dyslipidemia in patients with NAFLD results from hepatic and peripheral insulin resistance along with associated alterations of hepatic glucose and lipoprotein metabolism, gut dysbiosis, and genetic factors.

Summary
Since atherogenic dyslipidemia and NAFLD share a bi-directional relationship and are both major driving forces of atherosclerotic cardiovascular disease (ASCVD) development, early detection and adequate treatment are warranted. Thus, integrative screening and management programs are urgently needed. A stepwise approach for dyslipidemic patients with NAFLD includes (i) characterization of dyslipidemia phenotype, (ii) individual risk stratification, (iii) definition of treatment targets, (iv) lifestyle modification, and (v) pharmacotherapy if indicated.
Vitamin D Regulation of Immune Function
Authors: Bikle Daniel D 
Published: May 2022

Abstract
Purpose of Review
To review the mechanisms by which vitamin D and its metabolites regulate the immune system to facilitate the ability of the body to prevent and/or treat SARS-CoV2 and other respiratory infections and encourage further research into the role that vitamin D supplementation plays in preventing/treating such infections.

Recent Findings
Vitamin D deficiency is associated with an increased risk of SARS-CoV2 and other respiratory infections. Clinical trials in general demonstrate that correction of vitamin D deficiency reduces the risk of hospitalization, ICU admission, and death from SARS-CoV2 infection. The airway epithelium and alveolar macrophages express the enzyme, CYP27B1, that produces the active metabolite of vitamin D, 1,25(OH)2D, and the vitamin D receptor, VDR. Vitamin D and its metabolites promote the innate immune response, which provides the first line of defense against viral and bacterial infections while restricting the adaptive immune response, which if unchecked promotes the inflammatory response leading to the acute respiratory distress syndrome and death.

Summary
The rationale for treating vitamin D deficiency to reduce the risk of SARS-CoV2 infection and supplementing patients with vitamin D early in the course of SARS-CoV2 infection rests primarily on the ability of vitamin D metabolites to promote an effective immune response to the infection.
Advanced land imager superiority in lithological classification utilizing machine learning algorithms
Authors: Shebl Ali , Kusky Timothy , Csámer Árpád 
Published: May 2022

AbstractDifferent types of remote sensing data are commonly used as inputs for lithological classification schemes, yet determining the best data source for each specific application is still unresolved, but critical for the best interpretations. In addition, various classifiers (i.e., artificial neural network (ANN), maximum likelihood classification (MLC), and support vector machine (SVM)) have proven their variable efficiencies in lithological mapping, yet determining which technique is preeminent is still questionable. Consequently, this study aims to test the potency of Earth observing-1 Advanced Land Imager (ALI) data with the frequently utilized Sentinel 2 (S2), ASTER, and Landsat OLI (L8) data in lithological allocation using the widely accepted ANN, MLC, and SVM, for a case study in the Um Salatit area, in the Eastern Desert of Egypt. This area has a recent geological map that is used as a reference for selecting training and testing samples required for machine learning algorithms (MLAs). The results reveal (1) ALI superiority over the most commonly used S2, ASTER, and L8; (2) SVM is much better than MLC and ANN in executing lithologic allocation; (3) S2 is strongly recommended for separating higher numbers of classes compared to ASTER, L8, and ALI. Model overfitting may negatively impact S2 results in classifying small numbers of targets; (4) we can significantly enhance the classification accuracy, to transcend 90% by blending different sensor datasets. Our new approach can help significantly in further lithologic mapping in arid regions and thus be fruitful for mineral exploration programs.
Density and occupancy of leopard cats across different forest types in Cambodia
Authors: Pin Chanratana , Phan Channa , Kamler Jan F. , Rostro-García Susana , Penjor Ugyen , In Visattha , Crouthers Rachel , Macdonald Ewan A. , Chou Sophark , Macdonald David W. 
Published: May 2022

AbstractThe leopard cat (Prionailurus bengalensis) is the most common wild felid in Southeast Asia, yet little is known about the factors that affect their population density and occupancy in natural habitats. Although leopard cats are highly adaptable and reportedly can attain high densities in human-modified habitats, it is not clear which natural habitat is optimal for the species. Also, this felid has been preyed upon by large carnivores in Southeast Asia, yet the intra-guild effects of large carnivore presence on leopard cats are almost unknown. To shed light on these fundamental questions, we used data from camera trap surveys for felids to determine the leopard cat densities in three different forest types within Cambodia: continuous evergreen, mosaic dominated by evergreen (hereafter evergreen mosaic), and mosaic dominated by open dry deciduous forests (hereafter DDF mosaic). We also conducted occupancy analyses to evaluate the interactions of the leopard cats with three large carnivores: leopards (Panthera pardus), dholes (Cuon alpinus), and domestic dogs (Canis familiaris). The estimated density (individuals/100 km2 ± SE) was highest in the continuous evergreen (27.83 ± 7.68), followed by evergreen mosaic (22.06 ± 5.35) and DDF mosaic (13.53 ± 3.23). Densities in all three forest types were relatively high compared to previous studies. Domestic dogs were detected on all 3 sites, and leopards and dholes had sufficient records on only one site each. The occupancy probability of leopard cats was not affected by the presence or absence of any large carnivore, indicating that large carnivores and leopard cats occurred independently of each other. Our findings support the claim that leopard cats are habitat generalists, but we show that evergreen forest is the optimum natural habitat for this species in the region. The DDF mosaic appears to sustain lower densities of leopard cats, probably due to the harsh dry season and wildfires that led to reduced prey base, although this generalist felid was still able to occupy DDF in relatively moderate numbers. Overall, the adaptability of leopard cats to various forest types, and lack of negative interaction with large carnivores, helps to explain why this species is the most common and widespread felid in Southeast Asia.
How to approximate the Dirac equation with the Mauser method
Authors: Renziehausen Klaus , Liu Kunlong , Barth Ingo 
Published: May 2022

AbstractMauser and coworkers discussed in a series of papers an ansatz how to split the Dirac equation and the wave function appearing therein into a part related to a free moving electron and another part related to a free moving positron. This ansatz includes an expansion of these quantities into orders of the reciprocal of the speed of light $$\epsilon = 1/c$$

ϵ
=
1
/
c

. In particular, in Mauser (VLSI Design 9:415, 1999) it is discussed how to apply this expansion up to the second order in the reciprocal of the speed of light $$\epsilon $$
ϵ
. As an expansion of this analysis, we show in this work how all three well-known terms that appear in an expansion of the Dirac equation in second order on the reciprocal of the speed of light, namely, a relativistic correction to the kinetic energy, the Darwin term, and the spin-orbit interaction, can be found using the ansatz of Mauser—and doing so, we close a gap between this ansatz to approximate the Dirac equation and other approximative results found using the Foldy–Wouthuysen transformation.
Surroundings affect slip length dynamics in nanoscale friction through contact stiffness and damping
Authors: Skuratovsky Simona , Agmon Liron , Gnecco Enrico , Berkovich Ronen 
Published: May 2022

AbstractFriction force microscopy (FFM) explores the interaction in a sliding contact on the nanoscale, providing information on the frictional dynamics and lateral contact stiffness with lattice resolution. Recent FFM measurements on a NaCl crystal immersed in liquid (ethanol) surroundings displayed an increase of the effective contact stiffness, Keff, with the applied load, differently from similar measurements performed under ultra-high vacuum (UHV) conditions, where Keff showed negligible load dependency. Additionally, under UHV conditions multiple slip length friction with increasing load was reported, while in ethanol surroundings only single (lattice unit length) slips were observed. Our current understanding of this behavior relates the transition from single jumps to multiple jumps dynamics to the normal load (manifested through the amplitude of the interaction potential at the contact, U0) and to the damping of the system. Here we have incorporated the effect of the load dependency on both U0 and Keff within Prandtl—Tomlinson based simulations, accompanied by variations in the damping coefficient of the system. Introducing the experimentally observed load dependency to Keff resulted indeed in single slip jumps at critical damping, while multiple slip jumps were obtained at constant Keff. The average slip length increased with the normal load, particularly when the system became underdamped. Our work provides a glimpse on the relation between the characteristic observables in atomic-scale sliding friction (maximal slip forces, stiffness, and slip dynamics) with respect to their governing parameters (corrugation energy, effective stiffness, and damping). While common understanding in nanotribology relates the effect of surrounding media mainly to the interaction potential at the contact, here we show that the media can also greatly affect the elastic interaction, and consequently play an important role on the transition from single to multiple stick-slip.
Leveraging Technology and Gamification to Engage Learners in a Microbiology Curriculum in Undergraduate Medical Education
Authors: Walker Jeremey , Heudebert Jose Pablo , Patel Mukesh , Cleveland John D. , Westfall Andrew O. , Dempsey Donald M. , Guzman Alfredo , Zinski Anne , Agarwal Monica , Long Dustin , Willig James , Lee Rachael 
Published: May 2022

Abstract
Background
Microbiology is a critical and expansive topic that many medical schools’ curriculum must teach in a constrained time frame. We implemented a microbiology question bank smart phone app enhanced with game elements and clinical pearls during a microbiology course for first-year medical students. We hypothesized that these enhancements and clinical pearls would engage the students meaningfully and increase their knowledge base.

Methods
Though use was optional, students’ game play was recorded through the app, which was compared to test grades retrospectively. A player efficiency rating (PER) was calculated as a function of question response, accuracy, and engagement. Students were separated into tertiles of PER and median exam grades were compared using a non-parametric Kruskal–Wallis (KW) test. An anonymous satisfaction and usability feedback survey was also administered.

Results
One hundred eighty-one of the 189 students (96%) answered at least one question, and 165 (87%) completed all 56 questions. The average PER was 84.75. We received feedback surveys from 61 (34%) students in the course, with positive responses regarding the perceived impact on learning microbiology. The KW test found a positive correlation for median exam scores of the player groups when divided into tertiles by PER (p = 0.0002).

Conclusions
We leveraged gamification and clinical pearls to design a supplemental microbiology question bank. We found high engagement overall and higher class exam scores associated with greater use of the question bank.
Feasibility of Mindful After Cancer: Pilot Study of a Virtual Mindfulness-Based Intervention for Sexual Health in Cancer Survivorship
Authors: Gorman Jessica R. , Drizin Julia H. , Smith Ellie , Corey Stephanie , Temple Madison , Rendle Katharine A. 
Published: May 2022

ABSTRACTBackgroundMindfulness-based interventions (MBIs) are increasingly recognized as an effective strategy for supporting female cancer survivors experiencing sexual health concerns.AimTo examine the feasibility of a sexual health MBI, Mindful After Cancer, which was adapted to meet the needs of breast and gynecologic cancer survivors in a community setting and for delivery via videoconference.MethodsA mixed-methods approach was used to evaluate the acceptability, feasibility, and appropriateness of the 8-week virtual MBI. Weekly sessions were 1.5–2 hours in duration and included guided meditations and group discussion about sexuality after cancer and mindfulness in daily life. Home practice activities related to both mindfulness practice and sexual health. Participants completed online surveys at baseline and 1-month post-intervention. A purposive sample of 10 participants were invited to complete a follow-up interview 2–3 months post-intervention.OutcomesPrimary outcomes included both qualitative and quantitative assessments of acceptability, appropriateness, and feasibility of the Mindful After Cancer intervention for sexual health in cancer survivorship.ResultsTwenty-two women completed the intervention (Mean age 53.2 years, SD = 9.4, Range= 39–73), with time since diagnosis ranging from 1 to 27 years (Mean 6.0 years, SD = 5.9). Participants completed 6.8 sessions on average (Range = 2 – 8) and 77% reported that the time commitment was manageable. Both qualitative and quantitative findings support the feasibility, acceptability, and appropriateness of the intervention.Clinical ImplicationsMany cancer survivors experience sexual dysfunction and related distress after diagnosis and well after treatment ends, yet there are few interventions available. Improved access to effective interventions can improve the delivery of survivorship care and patient outcomes.Strengths & LimitationsThe sample size is small for this pilot study, and a control group was not included. The intervention was offered over two time periods, one prior to COVID-19 pandemic and one during the pandemic, resulting in both limitations associated with potential differences between the experiences of participants and the opportunity to learn more about the feasibility of the intervention during times of crisis.ConclusionResults suggest that virtual delivery of the MBI is feasible, acceptable, and appropriate for breast and gynecologic cancer survivors.
Derivation of control inputs for deep stall recovery using nonlinear frequency analysis
Authors: Nguyen D. H. , Lowenberg M. H. , Neild S. A. 
Published: May 2022

AbstractAlthough the problem of locked-in deep stall is well documented over many years, there currently exists no consistent procedure that can guarantee recovery. Past studies have suggested that it might be possible to rock the aircraft in pitch to destabilise the statically stable deep stall trim point, thereby gaining enough momentum to push the nose down. However, the methods used in these studies are either of preliminary or empirical nature and cannot guarantee recovery. In this paper, we use bifurcation analysis to derive a recovery manoeuvre, specifically by assessing the aircraft’s nonlinear frequency response under an elevator forcing. The ensuing nonlinear Bode plot detects unstable (divergent) solutions near resonance that contribute to a successful deep stall recovery. Moreover, the nonlinear resonant frequency is slightly lower than the result obtained using linear analysis, and time simulation shows that relying on the linear result does not lead to a successful recovery. It is also found that at the high angles of attack associated with deep stall, the frequency separation between the short period and phugoid mode is significantly reduced, leading to only one visible peak in the frequency response. This feature is also reflected in the time-domain step response.
System identification of cropped delta UAVs from flight test methods using particle Swarm-Optimisation-based estimation
Authors: Kumar N. , Saderla S. , Kim Y. 
Published: May 2022

AbstractIn the era of Unmanned Aerial Systems (UAS), an onboard autopilot occupies a prominent place and is inevitable for many of their modern applications. The efficacy of autopilot heavily relies upon the accuracy of the sensors employed and the capability of the onboard flight controller. In general, aerodynamic behaviour and flight dynamic capabilities of Unmanned Aerial Vehicles (UAVs) govern the selection and the design of flight controllers. Precise modeling of linear aerodynamic characteristics from flight data can be achieved using many of the existing classical parameter estimation techniques such as Output Error Method (OEM), Equation Error Method (EEM), and Filter Error Method (FEM). However, all the classical methods may not be readily applicable for aerodynamic modeling in nonlinear flight envelopes. The current manuscript is an attempt to exploit the capabilities of the Artificial Intelligence (AI) technique, named Particle Swarm Optimisation (PSO), in combination with Least Squares (LS) cost function to perform linear as well as nonlinear aerodynamic parameter estimation. The aforementioned task is accomplished by considering flight data from manoeuvers pertaining to linear angles of attack, moderate and near stall flight envelopes of two different UAVs with cropped delta planform geometry. Parameters estimated using the proposed LS-PSO method are consistent with minimum standard deviation and are on a par with OEM estimates. The proposed LS-PSO method enhances the capabilities of LS-based EEM while estimating stall characteristic parameters, which was not possible with LS alone. The longitudinal and lateral-directional static parameters estimated from the full-scale wind tunnel testing of the two UAVs were also used to corroborate the results obtained from the flight data using the LS-PSO method.
Thoughts and beliefs of healthcare workers regarding the coronavirus disease 2019 (COVID-19) vaccine and which messaging themes might affect vaccine confidence and recommendation of the vaccine
Authors: Spires S. Shaefer , Clark Jenna L. , Rayburn-Reeves Rebecca , Ashley Elizabeth Dodds , Desai Avani , Lindemans Jan 
Published: May 2022

Abstract
We surveyed healthcare workers within the Duke Antimicrobial Stewardship Outreach Network (DASON) to describe beliefs regarding coronavirus disease 2019 (COVID-19) vaccination and their decision-making process behind vaccination recommendations. In contrast to the type of messaging that appealed most on a personal level to the healthcare workers, they preferred a more generic message emphasizing safety and efficacy when making vaccination recommendations.
UNIVERSAL CODING AND PREDICTION ON ERGODIC RANDOM POINTS
Authors: DĘBOWSKI ŁUKASZ , STEIFER TOMASZ 
Published: May 2022

AbstractSuppose that we have a method which estimates the conditional probabilities of some unknown stochastic source and we use it to guess which of the outcomes will happen. We want to make a correct guess as often as it is possible. What estimators are good for this? In this work, we consider estimators given by a familiar notion of universal coding for stationary ergodic measures, while working in the framework of algorithmic randomness, i.e., we are particularly interested in prediction of Martin-Löf random points. We outline the general theory and exhibit some counterexamples. Completing a result of Ryabko from 2009 we also show that universal probability measure in the sense of universal coding induces a universal predictor in the prequential sense. Surprisingly, this implication holds true provided the universal measure does not ascribe too low conditional probabilities to individual symbols. As an example, we show that the Prediction by Partial Matching (PPM) measure satisfies this requirement with a large reserve.