Rebecca Black, BApSc, Speech Pathologist(SP), Duy Duong Nguyen, MD PhD, Anna Miles, PhD
et al.
Background: Oropharyngeal dysphagia and laryngeal dysfunction are complications of lung and heart transplantation. However, there is a lack of understanding around pre-operative function and an absence of standardized assessment protocols. We aimed to trial a pre- and post-operative protocol for assessing voice and swallowing function. Method: A prospective, longitudinal study of 14 adults undergoing investigation for lung or heart transplantation was conducted at a tertiary referral hospital. Patients were assessed pre-surgery and up to 6 months afterwards. The protocol involved phonation tasks with auditory-perceptual and acoustic analysis, videolaryngostroboscopy, a flexible endoscopic examination of swallowing and patient reported quality of life measures. Risk factors and clinical outcomes were extracted from patient records. Results: Patient self-reports of swallowing and voice difficulties were elevated pre-operatively. No evidence of swallowing difficulty was observed under endoscopic examination pre-transplant (Penetration-Aspiration Scale score <2; no accumulated secretions) and only one patient presented with incomplete glottic closure. Auditory perceptual ratings revealed voices were largely within the healthy range at baseline. One out of five patients presented with severe dysphonia post-operatively. Completion of evaluation measures prior to transplantation was 79% but post- operative rates were low due to feasibility challenges with follow up in this complex population. Conclusion: Novel evidence of self-reported pre-transplant voice and swallowing changes indicate value in baseline screening. Discrepancies between patient-report and instrumental assessment results highlight the need for multi-faceted evaluation. Large cohort studies are needed to determine the salient evaluation measures and time points for voice and swallowing assessment in this population.
We consider a model of hard-core bosons on a lattice, half-filling a Chern band such that the system has a continuous transition between a fractional Chern insulator (FCI) and a superfluid state (SF) depending on the bandwidth to bandspacing ratio. We construct a parton-inspired trial wavefunction ansatz for the ground states that has remarkably high overlap with exact diagonalization in both phases and throughout the phase transition. Our ansatz is stable to adding some bosonic interactions beyond the on-site hard core constraint. We confirm that the transition is well described by a projective translation symmetry-protected multiple parton band gap closure, as has been previously predicted. However, unlike prior work, we find that our wavefunctions require anomalous (BCS-like) parton correlations to describe the phase transition and SF phase accurately.
We employ Born-Oppenheimer approximation to the $T_{c\bar s0}^a(2900)^0$ and $T_{c\bar s0}^a(2900)^{++}$ states observed by the LHCb Collaboration and study mass spectrum and root-mean-square radius values. For this purpose, we use dynamical diquark model. We assume that strange quark is a heavy for the usage of Born-Oppenheimer approximation. Our results strongly indicate that the $T_{c\overline{s}0}^{a}(2900)$ states are best described as composed of axial-vector (spin-1) diquark pairs. Furthermore, the calculated root-mean-square radius, $\langle r^{2}\rangle^{1/2} \approx 0.70-0.80$ fm, which is significantly less than 1 fm, provides compelling evidence that these are compact tetraquarks rather than loosely bound hadronic molecules.
Tamer Eliyan, Ali Saeed Almuflih, Z. M. S. Elbarbary
et al.
The new horizons for HVDC systems and their applications has intensified the research in HVDC protection systems. The HVDC circuit breakers (CB) has been the center of the protection systems with vacuum interrupters (VIs) showcasing a great potential for application as a part of HVDC-CBs. However, VIs still face the problem of arc-reignition with limited studies in this area. This paper tends to address this problem by investigating the impact of the parameters of VI and the shunt L-C branch upon the re-ignition occurrence during switching process. An HVDC testing system and VI-based HVDC-CB were modeled using ATP software. The testing included investigation of the impact of the rate of rise of dielectric strength (RRDS) of VI, the type of LC circuit either active or passive and its timing of injection. The results showed that active L-C circuits demanded a longer delay time before insertion to avoid re-ignitions and the increase in RRDS reduced the reignitions. The main contributions of this paper include; investigating the arc re-ignition in VI-based HVDC-CB; analyzing the combined effect of the VI and L-C parameters upon those reignitions and providing a co-relation between the re-ignition occurrence and these parameters. That co-relation is used to define the most suitable delay time for LC circuit to avoid re-ignitions. The co-relation shows that the delay time is inversely co-related to the RRDS and directly-correlated to active LC types with lower values for passive L-C. This was applied to the simulation results and showed agreement with that co-relation.
Purpose: Medical students of color (MSoC) regularly experience discrimination and mistreatment during medical school. Preceptors have the potential to provide meaningful support for MSoC while on their family medicine clerkship rotation. This mixed-method study explores family medicine clerkship preceptors’ challenges, current practices, and institutional needs related to welcoming and supporting MSoC.
Methods: Any lead preceptor at a University of Washington-affiliated Family Medicine clerkship teaching site was eligible for this study. From June to September 2022, 7 focus groups were conducted with a total of 32 participants. Study team members coded transcripts for key themes related to participants’ experiences of working with MSoC. All participants were asked to complete a short survey, which included both demographic questions and questions regarding their beliefs and abilities to welcome and support MSoC.
Results: Many preceptors felt underprepared and unsure about when and how to support MSoC. Current strategies employed by participants included adding a semi-scripted orientation conversation to discuss how they will be supported during the rotation and who they can talk to if they encounter any discrimination and/or microaggressions. Participants also suggested that the medical school should offer additional trainings for preceptors, such as mitigating microaggressions toward students.
Conclusions: Lead preceptors are well positioned to empower and support the students they teach. This exploratory, single-institution study offers some insights into the challenges, current practices, and suggestions for institutions to support MSoC during clinical rotations. We recommend additional research to help validate our findings.
Quoc Cuong Ngo, Nicole McConnell, Mohammod Abdul Motin
et al.
Objective: A change in handwriting is an early sign of Parkinson’s disease (PD). However, significant inter-person differences in handwriting make it difficult to identify pathological handwriting, especially in the early stages. This paper reports the testing of NeuroDiag, a software-based medical device, for the automated detection of PD using handwriting patterns. NeuroDiag is designed to direct the user to perform six drawing and writing tasks, and the recordings are then uploaded onto a server for analysis. Kinematic information and pen pressure of handwriting are extracted and used as baseline parameters. NeuroDiag was trained based on 26 PD patients in the early stage of the disease and 26 matching controls. Methods: Twenty-three people with PD (PPD) in their early stage of the disease, 25 age-matched healthy controls (AMC), and 7 young healthy controls were recruited for this study. Under the supervision of a consultant neurologist or their nurse, the participants used NeuroDiag. The reports were generated in real-time and tabulated by an independent observer. Results: The participants were able to use NeuroDiag without assistance. The handwriting data was successfully uploaded to the server where the report was automatically generated in real-time. There were significant differences in the writing speed between PPD and AMC (P<0.001). NeuroDiag showed 86.96% sensitivity and 76.92% specificity in differentiating PPD from those without PD. Conclusion: In this work, we tested the reliability of NeuroDiag in differentiating between PPD and AMC for real-time applications. The results show that NeuroDiag has the potential to be used to assist neurologists and for telehealth applications. Clinical and Translational Impact Statement — This pre-clinical study shows the feasibility of developing a community-wide screening program for Parkinson’s disease using automated handwriting analysis software, NeuroDiag.
Computer applications to medicine. Medical informatics, Medical technology
Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited due to the transparency issue, which is considered a significant obstacle. To achieve the trust of end users, it is necessary to explain the AI models' output. Therefore, explainable AI (XAI) has become apparent as a potential solution by providing transparent explanations of the AI models' output. In this review paper, the primary aim is to review articles that are mainly related to machine learning (ML) or deep learning (DL) based human disease diagnoses, and the model's decision-making process is explained by XAI techniques. To do that, two journal databases (Scopus and the IEEE Xplore Digital Library) were thoroughly searched using a few predetermined relevant keywords. The PRISMA guidelines have been followed to determine the papers for the final analysis, where studies that did not meet the requirements were eliminated. Finally, 90 Q1 journal articles are selected for in-depth analysis, covering several XAI techniques. Then, the summarization of the several findings has been presented, and appropriate responses to the proposed research questions have been outlined. In addition, several challenges related to XAI in the case of human disease diagnosis and future research directions in this sector are presented.
Mind-wandering (MW) is when an individual’s concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data to examine the harmful effects of MW is time-consuming. This study proposes a multi-resolution assessment of EEG signals using the flexible analytic wavelet transform (FAWT). The FAWT algorithm decomposes raw EEG data into more representative sub-bands (SBs). Several statistical characteristics are derived from the obtained SBs, and the effects of MW during meditation on the EEG signals are investigated. A set of significant characteristics is chosen and fed into the machine learning modules using a 10-fold validation approach to detect MW subjects automatically. Our proposed framework attained the highest classification accuracy of 92.41%, the highest sensitivity of 93.56%, and the highest specificity of 91.97%. The proposed framework can be used to design a suitable brain-computer interface (BCI) system to reduce MW and increase meditation depth for holistic and long-term health in society.
Computer applications to medicine. Medical informatics
Female breast cancer (FBC) incidence rate (IR) varies greatly by counties across the United States (US). Factors responsible for such high spatial disparities are not well understood, making it challenging to design effective intervention strategies. We predicted FBC IRs using prevailing machine learning techniques for 1,754 US counties with a female population over 10,000. Outlier counties with the unexpectedly high or low FBC IRs were identified by controlling the non-modifiable factors (demographics and socioeconomics). Impacts of the modifiable factors (lifestyle, healthcare accessibility, and environment) were mapped. Our study also shed light on hidden FBC risk factors at the regional scale. Methods developed in our study may be used to discover the place-specific, population-level, modifiable factors for the intervention of other types of cancer or chronic diseases.
Andrew Deas, Adam Spannaus, Dakotah D. Maguire
et al.
The opioid crisis remains a critical public health challenge in the United States. Despite national efforts which reduced opioid prescribing rates by nearly 45\% between 2011 and 2021, opioid-related overdose deaths more than tripled during the same period. This alarming trend reflects a major shift in the crisis, with illegal opioids now driving the majority of overdose deaths instead of prescription opioids. Although much attention has been given to supply-side factors fueling this transition, the underlying structural conditions that perpetuate and exacerbate opioid misuse remain less understood. Moreover, the COVID-19 pandemic intensified the opioid crisis through widespread social isolation and record-high unemployment; consequently, understanding the underlying drivers of this epidemic has become even more crucial in recent years. To address this need, our study examines the correlation between opioid-related mortality and thirteen county-level characteristics related to population traits, economic stability, and infrastructure. Leveraging a nationwide county-level dataset spanning consecutive years from 2010 to 2022, this study integrates empirical insights from exploratory data analysis with feature importance metrics derived from machine learning models. Our findings highlight critical regional characteristics strongly correlated with opioid-related mortality, emphasizing their potential roles in worsening the epidemic when their levels are high and mitigating it when their levels are low.
Jasmine Muradchanian, Rink Hoekstra, Henk Kiers
et al.
<h4>Background</h4>Publishing study results in scientific journals has been the standard way of disseminating science. However, getting results published may depend on their statistical significance. The consequence of this is that the representation of scientific knowledge might be biased. This type of bias has been called publication bias. The main objective of the present study is to get more insight into publication bias by examining it at the author, reviewer, and editor level. Additionally, we make a direct comparison between publication bias induced by authors, by reviewers, and by editors. We approached our participants by e-mail, asking them to fill out an online survey.<h4>Results</h4>Our findings suggest that statistically significant findings have a higher likelihood to be published than statistically non-significant findings, because (1) authors (n = 65) are more likely to write up and submit articles with significant results compared to articles with non-significant results (median effect size 1.10, BF10 = 1.09*107); (2) reviewers (n = 60) give more favourable reviews to articles with significant results compared to articles with non-significant results (median effect size 0.58, BF10 = 4.73*102); and (3) editors (n = 171) are more likely to accept for publication articles with significant results compared to articles with non-significant results (median effect size, 0.94, BF10 = 7.63*107). Evidence on differences in the relative contributions to publication bias by authors, reviewers, and editors is ambiguous (editors vs reviewers: BF10 = 0.31, reviewers vs authors: BF10 = 3.11, and editors vs authors: BF10 = 0.42).<h4>Discussion</h4>One of the main limitations was that rather than investigating publication bias directly, we studied potential for publication bias. Another limitation was the low response rate to the survey.
The inchworm in-pipe robot has the advantages of stable support, low walking resistance, and high flexibility. However, the gait motion of in-pipe robots relies on the precise coordination of three motors, which greatly increases the complexity of control. To solve this problem, an inchworm in-pipe robot based on a multi-cam combination is proposed. The robot needs only one motor to achieve active support and bidirectional crawling for the pipe wall, mainly used for detecting straight pipelines, such as the main drainage pipeline. In order to obtain the periodic motion law and characteristics of the inchworm in-pipe robot, structure design, constraint analysis, and dynamic simulation were carried out on the robot. Finally, the principle prototype was tested in the transparent pipe, the test results indicate that the robot can achieve bidirectional creep under a single motor drive, which can simplify the control of gait motion for inchworm in-pipe robots. The average displacement errors for horizontal walking and vertical walking are 2.0% and 11.3%, respectively, due to factors such as gravity. Therefore, the robot can achieve a more accurate step distance in the horizontal pipe.
Background Ongoing exercise intolerance of unclear cause following COVID‐19 infection is well recognized but poorly understood. We investigated exercise capacity in patients previously hospitalized with COVID‐19 with and without self‐reported exercise intolerance using magnetic resonance–augmented cardiopulmonary exercise testing. Methods and Results Sixty subjects were enrolled in this single‐center prospective observational case‐control study, split into 3 equally sized groups: 2 groups of age‐, sex‐, and comorbidity‐matched previously hospitalized patients following COVID‐19 without clearly identifiable postviral complications and with either self‐reported reduced (COVIDreduced) or fully recovered (COVIDnormal) exercise capacity; a group of age‐ and sex‐matched healthy controls. The COVIDreducedgroup had the lowest peak workload (79W [Interquartile range (IQR), 65–100] versus controls 104W [IQR, 86–148]; P=0.01) and shortest exercise duration (13.3±2.8 minutes versus controls 16.6±3.5 minutes; P=0.008), with no differences in these parameters between COVIDnormal patients and controls. The COVIDreduced group had: (1) the lowest peak indexed oxygen uptake (14.9 mL/minper kg [IQR, 13.1–16.2]) versus controls (22.3 mL/min per kg [IQR, 16.9–27.6]; P=0.003) and COVIDnormal patients (19.1 mL/min per kg [IQR, 15.4–23.7]; P=0.04); (2) the lowest peak indexed cardiac output (4.7±1.2 L/min per m2) versus controls (6.0±1.2 L/min per m2; P=0.004) and COVIDnormal patients (5.7±1.5 L/min per m2; P=0.02), associated with lower indexed stroke volume (SVi:COVIDreduced 39±10 mL/min per m2 versus COVIDnormal 43±7 mL/min per m2 versus controls 48±10 mL/min per m2; P=0.02). There were no differences in peak tissue oxygen extraction or biventricular ejection fractions between groups. There were no associations between COVID‐19 illness severity and peak magnetic resonance–augmented cardiopulmonary exercise testing metrics. Peak indexed oxygen uptake, indexed cardiac output, and indexed stroke volume all correlated with duration from discharge to magnetic resonance–augmented cardiopulmonary exercise testing (P<0.05). Conclusions Magnetic resonance–augmented cardiopulmonary exercise testing suggests failure to augment stroke volume as a potential mechanism of exercise intolerance in previously hospitalized patients with COVID‐19. This is unrelated to disease severity and, reassuringly, improves with time from acute illness.
Diseases of the circulatory (Cardiovascular) system
Patrick H. Wightman, James A. Martin, John C. Kilgo
et al.
Abstract Gobbling activity of Eastern wild turkeys (Meleagris gallopavo silvestris; hereafter, turkeys) has been widely studied, focusing on drivers of daily variation. Weather variables are widely believed to influence gobbling activity, but results across studies are contradictory and often equivocal, leading to uncertainty in the relative contribution of weather variables to daily fluctuations in gobbling activity. Previous works relied on road‐based auditory surveys to collect gobbling data, which limits data consistency, duration, and quantity due to logistical difficulties associated with human observers and restricted sampling frames. Development of new methods using autonomous recording units (ARUs) allows researchers to collect continuous data in more locations for longer periods of time, providing the opportunity to delve into factors influencing daily gobbling activity. We used ARUs from 1 March to 31 May to detail gobbling activity across multiple study sites in the southeastern United States during 2014–2018. We used state‐space modeling to investigate the effects of weather variables on daily gobbling activity. Our findings suggest rainfall, greater wind speeds, and greater temperatures negatively affected gobbling activity, whereas increasing barometric pressure positively affected gobbling activity. Therefore, when using daily gobbling activity to make inferences relative to gobbling chronology, reproductive phenology, and hunting season frameworks, stakeholders should recognize and consider the potential influences of extended periods of inclement weather.
In this paper, we study strong converse properties for both visible and blind compression of mixed states. The optimal rate of a visible compression scheme is obtained in terms of the entanglement of purification, whose additivity remains unknown so far. For a variation of extendible states, we prove that the entanglement of purification is additive and apply this to obtain a "pretty strong" converse bound for the blind and visible compression of such states. Namely, when the rate decreases below the optimal rate, the error exhibits a discontinuous jump from 0 to at least $\frac{1}{3\sqrt{2}}$. To deal with the visible case for general states, we define a new quantity $E_{α,p}(A:R)_ρ$ for a bipartite state $ρ^{AR}$ and $α\in (0,1)\cup (1,\infty)$ as the $α$-Rényi generalization of the entanglement of purification $E_{p}(A:R)_ρ$. For $α=1$, we define $E_{1,p}(A:R)_ρ:=E_{p}(A:R)_ρ$. We show that for any rate below the regularization $\lim_{α\to 1^+}E_{α,p}^{\infty}(A:R)_ρ:=\lim_{α\to 1^+} \lim_{n \to \infty} \frac{E_{α,p}(A^n:R^n)_{ρ^{\otimes n}}}{n}$ the fidelity for the visible compression exponentially converges to zero. Moreover, we consider blind compression of a general mixed-state source $ρ^{AR}$ shared between an encoder and an inaccessible reference system $R$. We obtain a strong converse bound for the compression of this source by assuming that the decoder is a super-unital channel. This immediately implies a strong converse for the blind compression of ensembles of mixed states, by assuming a super-unital decoder, as this is a special case of the general mixed-state source $ρ^{AR}$ where the reference system $R$ has a classical structure.
Matthew Borden, Kelly Laplante, Juanita Popenoe
et al.
This series of Key Plant, Key Pests publications are designed for Florida gardeners, horticulturalists, and landscape professionals to help identify common pests associated with regional flora. This new 6-page publication of the UF/IFAS Environmental Horticulture Department helps identify the most common pests found on trees in the sycamore group, Platanus spp., and it provides information and general management recommendations for sycamore lace bug, bacterial leaf scorch, powdery mildew, anthracnose, and canker stain. Written by Matthew Borden, Kelly Laplante, Juanita Popenoe, Adam Dale, Caroline R. Warwick, and Brian Pearson.
https://edis.ifas.ufl.edu/ep601
Accessibility Summary:
In accordance with Title II regulations this content meets all points of exemption as Archived web content and/or Preexisting conventional electronic documents.
The relations between the resource theoretic measures of quantum coherence are rigorously investigated for various Markovian and non-Markovian channels for the two-qubit $X$ states with specific attention to the maximum and minimum attainable coherence and usefulness of these states in performing quantum teleportation in noisy environment. The investigation has revealed that under both dephasing and dissipative type noises the maximally entangled mixed states and Werner states lose their form and usefulness. However, maximally non-local mixed states (MNMSs) lose their identity in dissipative noise only. Thus, MNMSs are established to be useful in teleporting a qubit with fidelity greater than the classical limit in the presence of dephasing noise. MNMSs also remain useful for device independent quantum key distribution in this case as they still violate Bell's inequality. In the presence of noise, coherence measured by relative entropy of coherence is found to fall faster than the same measured using $l_1$ norm of coherence. Further, information back-flow from the environment to the system is observed over non-Markovian channels which leads to revival in coherence. Additionally, sequential interaction of two qubits with the same environment is found to result in correlated noise on both qubits, and coherence is observed to be frozen in this case under dephasing channel. Under the effect of Markovian and non-Markovian dephasing channels studied here, we observed that MNMSs have maximum relative coherence, i.e., they have the maximum amount of $l_1$ norm of coherence among the states with the same amount of relative entropy of coherence. However, this feature is not visible in any $X$ state evolving over dissipative channels.
Chimera states, states of coexistence of synchronous and asynchronous motion, have been a subject of extensive research since they were first given a name in 2004. Increased interest has lead to their discovery in ever new settings, both theoretical and experimental. Less well-discussed is the fact that successive results have also broadened the notion of what actually constitutes a chimera state. In this article, we critically examine how the results for different model types and coupling schemes, as well as varying implicit interpretations of terms such as coexistence, synchrony and incoherence, have influenced the common understanding of what constitutes a chimera. We cover both theoretical and experimental systems, address various chimera-derived terms that have emerged over the years and finally reflect on the question of chimera states in real-world contexts.
Ali Davoodi, Homayoun H. Zadeh, Morteza Daliri Joupari
et al.
Plasma surface treatment has a wide range of applications in biomedicine. In the present study, flat polylactic acid (PLA) films were treated with oxygen and nitrogen, low-pressure, non-thermal plasma. The water contact angle of the PLA films dramatically decreased from 67° in the untreated surface to 34° and 38° in surfaces treated with nitrogen and oxygen plasma, respectively. Conversely, after the plasma treatment, the surface free energy of the films increased considerably from 45.73 mN/m to 66.51 mN/m. The hydrophilicity potential variations following the plasma treatment were measured by the x-ray photoelectron spectroscopy examination of polar functional groups. Furthermore, surface changes after plasma treatment were examined using atomic force microscopy. The MTT assay showed no changes in cell viability cytotoxicity following the PLA films’ plasma treatment. Moreover, as evidenced by SEM analysis, plasma treatment was found to promote cell growth and adhesion to polymer surfaces. The results were suggestive of modifications due to the PLA’s plasma treatment that may enhance the biological properties of PLA as a scaffold.