bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multivariable closed-loop control of deep brain stimulation for Parkinson’s disease
Authors: Fleming John E , Senneff Sageanne , Lowery Madeleine M 
Published: September 2023

Abstract

Objective. Closed-loop deep brain stimulation (DBS) methods for Parkinson’s disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered. Approach. A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals. Main results. Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered. Significance. Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.
Laser Injection Technique for Liquid Crystal Droplets with Arbitrary Shape
Authors: Chang Fengjiao , Guo Jin-Kun , Ling Jinzhong , Yuan Ying , Wang Xiaorui 
Published: September 2023

Abstract
We propose a simple and precise method for processing three-dimensional droplet structures of liquid crystal with arbitrary shapes. By irradiating liquid crystal emulsions with a laser beam, a photothermally induced Marangoni effect is introduced. This leads to the injection of water solution into the liquid crystal droplets. With the help of the elasticity of liquid crystal, the injected water solution spontaneously forms into monodispersed guest droplets which latterly self-assemble into branched droplet chains. This method enjoys great flexibility due to its non-contact and in-situ processing manner, allows the simultaneous and multiple processing of all liquid crystal droplets under the irradiation region, and offers excellent compatibility with technologies such as microfluidics. The proposed method is applicable in material science, photonics, and sensors.
Gouy Phase in the Presence of a Dielectric Interface
Authors: Zhao Xinying , Liang Huijian , Zhang Han , Pang Xiaoyan 
Published: September 2023

Abstract
The Gouy phase is investigated in the dielectric interface in the present paper. It is shown that the maximum intensity and wavefront spacing are closely related to the Gouy phase and are influenced by the parameters refractive indices, the distance between the interface and the geometric focus and semi-aperture angle. Our findings demonstrate that even small changes in refractive indices have a significant impact on the Gouy phase and offer an alternative perspective on how accurate the Gouy phase is. The results may have applications in optical microscope, in optical recording and in the high-resolution optical sensing system.
A Partial Discharge Acoustic Detection Method of the Switchgear Based on Wavelet Denoising
Authors: Shi Xin , Yu Hao , Mo Zhongyue 
Published: September 2023

Abstract
To ensure the safe operation of the power grid and accurately identify the acoustic signal of the partial discharge of the switchgear, a partial discharge acoustic detection method for switchgear based on wavelet denoising is proposed in this paper. First, the Gaussian mixture algorithm model is used to denoise the discharge acoustic signal; then, the feature extraction and training of the acoustic signal samples are carried out; finally, a classifier is used to complete the discharge state recognition. The experimental results show that the detection accuracy of the proposed detection algorithm can reach more than 90%, and the robustness is good in different noise environments.
Integrated Energy Scheduling Optimization Based on Improved Gray Wolf Algorithm
Authors: Shang Jiawei , Wang Chenxu , Zhang Shijun , Gong Xu , Kang Qinyu 
Published: September 2023

Abstract
An integrated energy system contains a lot of distributed energy resources, and various energy sources complement each other, which greatly improves energy and has a significant advantage in energy conservation and emissions reduction. According to various micro source power characteristics and the cold and hot electricity load demand, this paper establishes a multi-objective model of cold-hot electric installations and an integrated energy system, by considering the influence of DianZhuan gas equipment and economic costs, and enhances the precision of the target function. Compared with the basic multi-target gray wolf algorithm, the improved algorithm effectively reduces economic drain, wind abandoned and pollution discharge amount.
Experimental Transient Performance of Heat Sink with Phase Change Material and Movable Metal Foams Insert
Authors: Feng Biao , Li Dedi , Rong Yangyiming , Gao Jun , Zhou Jie , Luo Guanqun 
Published: September 2023

Abstract
The effects of embedding fixed and movable metal foams in composite PCMs on the transient performance were studied with pulsed heat loads experimentally under various powers and different cell sizes. Similar conclusions could be drawn both from the experimental and numerical results. It was shown that when fixed metal foams were solely adopted, the heat storage system performance could be enhanced by ∼24.6% by increasing the number of metal foams by three times at the heat flux of 56.1 W/cm2 and 15 ppi. When the movable technique was utilized, the heat transfer enhancement reached up to 36.9% under the same amount of metal foams for the same cell sizes and heat flux. The better performances were attributed to combined positive influences due to the adoption of the movable metal foam technique, which extends heat transfer area, improves heat conduction, and eases suppression of natural heat convection by cutting the amount of metal foams. Moreover, as cutting the amount of metal foams could obviously reduce the wastage of energy storage capacity, the movable metal foam technique demonstrated quite a promising future.
Calculating the area of a particular deformation region of an optical surface based on the finite element method
Authors: Su Ruifeng 
Published: September 2023

Abstract
To study the deformation of an optical surface and its effect on optical performance, a method based on the finite element method for calculating the area of a particular deformation region of an optical surface is proposed, and a concept of effective area ratio is further introduced to describe the effect of deformation on optical performance. The principle of the method is presented, and the deformation of a potassium dihydrogen phosphate (KH2PO4, KDP) crystal is studied using this method, while the calculation accuracy is discussed. The results demonstrate that the method and the concept of effective area ratio are available for studying the deformation of an optical surface and its effect on optical performance.
n-type CdTe:In for photovoltaics: in situ doping, type verification and compensation effects
Authors: Hobson Theodore D C , Thomas Luke , Phillips Laurie J , Jones Leanne A H , Smiles Matthew J , Don Christopher H , Thakur Pardeep K , Shiel Huw , Campbell Stephen , Barrioz Vincent , Dhanak Vin , Veal Tim , Major Jonathan D , Durose Ken 
Published: September 2023

Abstract
We explored the in-situ doping of cadmium telluride thin films with indium to produce n-type absorbers as an alternative to the near-universal choice of p-type for photovoltaic devices. The films were grown by close space sublimation from melt-synthesised feedstock. Transfer of the indium during film growth was limited to 0.0014%–0.014%—unless reducing conditions were used which yielded 14%–28% efficient transport. While chunks of bulk feedstock were verified as n-type by the hot probe method, carrier type of thin film material was only able to be verified by using hard x-ray photoelectron spectroscopy to determine the Fermi level position within the band gap. The assignment of n-type conductivity was consistent with the rectification behaviour of a p-InP/CdTe:In junction. However, chloride treatment had the effect of compensating n-CdTe:In to near-intrinsic levels. Without chloride, the highest dopant activation was 20% of the chemical concentration of indium, this being for a film having a carrier concentration of n = 2 × 1015 cm−3. However, the activation was often much lower, and compensation due to over-doping with indium and native defects (stoichiometry) are discussed. Results from preliminary bifacial devices comprising Au/P3HT/ZnTe/CdTe:In/CdS/FTO/glass are presented.
MuDCoD: multi-subject community detection in personalized dynamic gene networks from single-cell RNA sequencing
Authors: Şapcı Ali Osman Berk , Lu Shan , Yan Shuchen , Ay Ferhat , Tastan Oznur , Keleş Sündüz 
Published: September 2023

AbstractMotivationWith the wide availability of single-cell RNA-seq (scRNA-seq) technology, population-scale scRNA-seq datasets across multiple individuals and time points are emerging. While the initial investigations of these datasets tend to focus on standard analysis of clustering and differential expression, leveraging the power of scRNA-seq data at the personalized dynamic gene co-expression network level has the potential to unlock subject and/or time-specific network-level variation, which is critical for understanding phenotypic differences. Community detection from co-expression networks of multiple time points or conditions has been well-studied; however, none of the existing settings included networks from multiple subjects and multiple time points simultaneously. To address this, we develop Multi-subject Dynamic Community Detection (MuDCoD) for multi-subject community detection in personalized dynamic gene networks from scRNA-seq. MuDCoD builds on the spectral clustering framework and promotes information sharing among the networks of the subjects as well as networks at different time points. It clusters genes in the personalized dynamic gene networks and reveals gene communities that are variable or shared not only across time but also among subjects.ResultsEvaluation and benchmarking of MuDCoD against existing approaches reveal that MuDCoD effectively leverages apparent shared signals among networks of the subjects at individual time points, and performs robustly when there is no or little information sharing among the networks. Applications to population-scale scRNA-seq datasets of human-induced pluripotent stem cells during dopaminergic neuron differentiation and CD4+ T cell activation indicate that MuDCoD enables robust inference for identifying time-varying personalized gene modules. Our results illustrate how personalized dynamic community detection can aid in the exploration of subject-specific biological processes that vary across time.Availability and implementationMuDCoD is publicly available at https://github.com/bo1929/MuDCoD as a Python package. Implementation includes simulation and real-data experiments together with extensive documentation.
Frequent allopolyploidy with distant progenitors in the moss genera Physcomitrium and Entosthodon (Funariaceae) identified via subgenome phasing of targeted nuclear genes
Authors: Patel Nikisha , Medina Rafael , Williams Lindsay D , Lemieux Olivia , Goffinet Bernard , Johnson Matthew G 
Published: September 2023

Abstract
Allopolyploids represent a new frontier in species discovery among embryophytes. Within mosses, allopolyploid discovery is challenged by low morphological complexity. The rapid expansion of sequencing approaches in addition to computational developments to identifying genome merger and whole-genome duplication using variation among nuclear loci representing homeologs has allowed for increased allopolyploid discovery among mosses. Here, we test a novel approach to phasing homeologs within loci and phasing loci across subgenomes, or subgenome assignment, called Homologizer, in the family Funariaceae. We confirm the intergeneric hybrid nature of Entosthodon hungaricus, and the allopolyploid origin of Physcomitrium eurystomum and one population of Physcomitrium collenchymatum. We also reveal that hybridization gave rise to Physcomitrium immersum, as well as to yet unrecognized lineages sharing the phenotype of Physcomitrium pyriforme and Physcomitrium sphaericum. Our findings demonstrate the utility of our approach when working with polyploid genomes, and its value in identifying progenitor species using target capture data.
Constraint on the event rate of general relativistic instability supernovae from the early JWST deep field data
Authors: Moriya Takashi J , Harikane Yuichi , Inoue Akio K 
Published: September 2023

ABSTRACT
General relativistic instability supernovae (GRSNe) at 10 ≲ z ≲ 15 are predicted to be observed as red faint point sources, and they can be detected only in the reddest filters in James Webb Space Telescope (JWST)/NIRCam (F444W and F356W). They should be observed as persistent point sources with little flux variations for a couple of decades because of time dilation. We search for static point sources detected only in the F444W filter or only in the F444W and F356W filters in the early JWST deep field data. No real point source of such kind is identified. Therefore, the GRSN rate at 10 ≲ z ≲ 15 is constrained to be less than ∼8 × 10−7 Mpc−3 yr−1 for the first time.
Follow-up analyses to the O3 LIGO–Virgo–KAGRA lensing searches
Authors: Janquart J , Wright M , Goyal S , Chan J C L , Ganguly A , Garrón Á , Keitel D , Li A K Y , Liu A , Lo R K L , Mishra A , More A , Phurailatpam H , Prasia P , Ajith P , Biscoveanu S , Cremonese P , Cudell J R , Ezquiaga J M , Garcia-Bellido J , Hannuksela O A , Haris K , Harry I , Hendry M , Husa S , Kapadia S , Li T G F , Magaña Hernandez I , Mukherjee S , Seo E , Van Den Broeck C , Veitch J 
Published: September 2023

ABSTRACT
Along their path from source to observer, gravitational waves may be gravitationally lensed by massive objects leading to distortion in the signals. Searches for these distortions amongst the observed signals from the current detector network have already been carried out, though there have as yet been no confident detections. However, predictions of the observation rate of lensing suggest detection in the future is a realistic possibility. Therefore, preparations need to be made to thoroughly investigate the candidate lensed signals. In this work, we present some follow-up analyses that could be applied to assess the significance of such events and ascertain what information may be extracted about the lens-source system by applying these analyses to a number of O3 candidate events, even if these signals did not yield a high significance for any of the lensing hypotheses. These analyses cover the strong lensing, millilensing, and microlensing regimes. Applying these additional analyses does not lead to any additional evidence for lensing in the candidates that have been examined. However, it does provide important insight into potential avenues to deal with high-significance candidates in future observations.
The Syphilis Epidemic Among Heterosexuals Is Accelerating: Evidence From King County, Washington
Authors: Berzkalns Anna , Ramchandani Meena S , Cannon Chase A , Kerani Roxanne P , Dombrowski Julie C , Golden Matthew R 
Published: September 2023

Abstract

Background
We characterized the rapid increase in syphilis among cisgender women in King County, Washington, and compared it with trends among cisgender men who have sex with men.

Method
We used surveillance data from King County, 2007 to 2022, to describe incidence trends stratified by syphilis stage, gender, and gender of sex partners; trends in pregnant cases and congenital syphilis; and trends in rapid plasma reagin titer at diagnosis among late/unknown duration cases. We used joinpoint regression to analyze trends.

Results
Among cisgender women, all-stage syphilis incidence remained stable from 2007 to 2010 but then increased by 16.3% per year (95% CI, 12.0%–20.7%) from 2010 to 2020 and 90.1% per year (95% CI, 26.4%–185.9%) from 2020 to 2022. Early syphilis rates rose gradually from 2007 to 2017 (18% per year; 95% CI, 7.4%–29.6%) and then rapidly from 2017 to 2022 (62.5% per year; 95% CI, 24.1%–112.9%). In contrast, the increase in late/unknown duration syphilis incidence was delayed. Among cisgender men who have sex with women, all-stage syphilis remained stable from 2007 to 2014 and increased 25.0% per year (95% CI, 14.0%–37.0%) from 2014 to 2022. Syphilis incidence increased steadily among men who have sex with men, with all-stage incidence increasing 7.0% per year (95% CI, 4.8%–9.2%) from 2007 to 2022. Median rapid plasma reagin titer among late/unknown duration cases increased significantly over the analysis period.

Conclusions
An explosive epidemic of syphilis is ongoing in King County. The delayed increase in asymptomatic late/unknown duration cases relative to early symptomatic cases suggests that there is a large and growing reservoir of recently acquired undiagnosed syphilis in women. New clinical and public health activities are urgently needed to control the growing epidemic.
ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity
Authors: Boscardin Christy K. , Gin Brian , Golde Polo Black , Hauer Karen E. 
Published: September 2023

Abstract
ChatGPT has ushered in a new era of artificial intelligence (AI) that already has significant consequences for many industries, including health care and education. Generative AI tools, such as ChatGPT, refer to AI that is designed to create or generate new content, such as text, images, or music, from their trained parameters. With free access online and an easy-to-use conversational interface, ChatGPT quickly accumulated more than 100 million users within the first few months of its launch. Recent headlines in the popular press have ignited concerns relevant to medical education over the possible implications of cheating and plagiarism in assessments as well as excitement over new opportunities for learning, assessment, and research. In this Scholarly Perspective, the authors offer insights and recommendations about generative AI for medical educators based on literature review, including the AI literacy framework. The authors provide a definition of generative AI, introduce an AI literacy framework and competencies, and offer considerations for potential impacts and opportunities to optimize integration of generative AI for admissions, learning, assessment, and medical education research to help medical educators navigate and start planning for this new environment. As generative AI tools continue to expand, educators need to increase their AI literacy through education and vigilance around new advances in the technology and serve as stewards of AI literacy to foster social responsibility and ethical awareness around the use of AI.
Beware False Growth Mindset: Building Growth Mindset in Medical Education Is Essential but Complicated
Authors: Memari Milad , Gavinski Katherine , Norman Marie K. 
Published: September 2023

Abstract
Mindset theory aims to explain how learners’ beliefs about intelligence and learning affect how they perceive effort, react to failure, and respond to feedback in challenging learning contexts. Mindset theory distinguishes between growth mindset (the belief that human capacities can be developed over time) and fixed mindset (the belief that human capacities are inherent and unchangeable). Efforts to develop growth mindset in learners have shown a wide range of benefits, including positive effects on students’ resilience, commitment to lifelong learning, and persistence in a field of study, with notable impacts on learners who are struggling, learners from minoritized groups, and women in scientific fields. In recent years, mindset theory interventions have caught the interest of medical educators hoping to engage learners as partners in their own learning and progression to competence. Educators hoping to apply this theory to educational programs and learner-teacher interactions in ways that promote growth mindsets would benefit from awareness of the concept of false growth mindset, a term coined by Carol Dweck to refer to common pitfalls in the theory's application. In this article, the authors highlight important findings from mindset interventions in medical education, identify common pitfalls of false growth mindset in the context of medical learners, and offer suggestions for how educators and institutions can better instigate changes to promote growth mindsets within medical education.
SHARPening Residency Selection: Implementing a Systematic Holistic Application Review Process
Authors: Igarabuza Laura , Gusoff Geoffrey M. , Maharaj-Best Ayiti-Carmel , Baylson Margaret J. , Betancourt Renée M. , Nicklin David E. , Wang Jenny Y. 
Published: September 2023

Abstract

Problem
Traditional metrics used in residency application review processes are systematically biased against applicants from minoritized communities that are underrepresented in medicine (URiM). These biases harm not just URiM applicants but also residency programs and patients. Although several residency programs have implemented holistic reviews to mitigate these biases, few tested tools exist that can be adapted and implemented in a wide variety of settings within academic medicine.

Approach
This article describes advances made in the third year of a longitudinal, ongoing quality improvement project that used the A3 framework to improve recruitment of URiM residents to a family medicine residency program. The authors devised a systematic holistic application review process (SHARP) to determine which applicants to invite to interview with the program. SHARP's development began in August 2019, and after significant discussion with program leadership and iterations of rubric refinement, the program adopted SHARP in September 2020 to review applications for the 2021 application cycle.

Outcomes
Compared with the 2016 to 2020 period before SHARP implementation, data from the 2021 and 2022 residency application cycles after SHARP implementation showed a significant increase in the proportion of interviewed candidates who identify as URiM (from 23% to 38%, P < .001) and matched candidates who identify as URiM (from 27% to 62%, P = .004). There was also a notable increase in the number and diversity of reviewers who evaluated applicants to the program.

Next Steps
SHARP is a promising tool to mitigate the effects of racism and other biases against URiM applicants to residency programs. Residency programs across specialties may benefit from adopting SHARP and adapting it based on their own goals and priorities.