bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimising multi-target multileaf collimator tracking using real-time dose for locally advanced prostate cancer patients
Authors: Hewson Emily A , Nguyen Doan Trang , Le Andrew , Booth Jeremy T , Keall Paul J , Mejnertsen Lars 
Published: August 2022

Abstract

Objective. The accuracy of radiotherapy for patients with locally advanced cancer is compromised by independent motion of multiple targets. To date, MLC tracking approaches have used 2D geometric optimisation where the MLC aperture shape is simply translated to correspond to the target’s motion, which results in sub-optimal delivered dose. To address this limitation, a dose-optimised multi-target MLC tracking method was developed and evaluated through simulated locally advanced prostate cancer treatments. Approach. A dose-optimised multi-target tracking algorithm that adapts the MLC aperture to minimise 3D dosimetric error was developed for moving prostate and static lymph node targets. A fast dose calculation algorithm accumulated the planned dose to the prostate and lymph node volumes during treatment in real time, and the MLC apertures were recalculated to minimise the difference between the delivered and planned dose with the included motion. Dose-optimised tracking was evaluated by simulating five locally advanced prostate plans and three prostate motion traces with a relative interfraction displacement. The same simulations were performed using geometric-optimised tracking and no tracking. The dose-optimised, geometric-optimised, and no tracking results were compared with the planned doses using a 2%/2 mm γ criterion. Main results. The mean dosimetric error was lowest for dose-optimised MLC tracking, with γ-failure rates of 12% ± 8.5% for the prostate and 2.2% ± 3.2% for the nodes. The γ-failure rates for geometric-optimised MLC tracking were 23% ± 12% for the prostate and 3.6% ± 2.5% for the nodes. When no tracking was used, the γ-failure rates were 37% ± 28% for the prostate and 24% ± 3.2% for the nodes. Significance. This study developed a dose-optimised multi-target MLC tracking method that minimises the difference between the planned and delivered doses in the presence of intrafraction motion. When applied to locally advanced prostate cancer, dose-optimised tracking showed smaller errors than geometric-optimised tracking and no tracking for both the prostate and nodes.
Residential exposure to petroleum refining and stroke in the southern United States
Authors: Kim Honghyok , Festa Natalia , Burrows Kate , Kim Dae Cheol , Gill Thomas M , Bell Michelle L 
Published: August 2022

Abstract
The southern United States (US) sustains a disproportionate burden of incident stroke and associated mortality, compared to other parts of the US. A large proportion of this risk remains unexplained. Petroleum production and refining (PPR) is concentrated within this region and emits multiple pollutants implicated in stroke pathogenesis. The relationship between residential PPR exposure and stroke has not been studied. We aimed to investigate the census tract-level association between residential PPR exposure and stroke prevalence for adults (⩾18 years) in seven southern US states in 2018. We conducted spatial distance- and generalized propensity score-matched analysis that adjusts for sociodemographic factors, health behavioral factors, and unmeasured spatial confounding. PPR was measured as inverse-distance weighted averages of petroleum production within 2.5 km or 5 km from refineries, which was strongly correlated with measured levels of sulfur dioxide, a byproduct of PPR. The prevalence of self-reported stroke ranged from 0.4% to 12.7% for all the census tracts of the seven states. People with low socioeconomic status and of Hispanic ethnicity resided closer to petroleum refineries. The non-Hispanic Black population was exposed to higher PPR, while the non-Hispanic White population was exposed to lower PPR. Residential PPR exposure was significantly associated with stroke prevalence. One standard deviation increase in PPR within 5 km from refineries was associated with 0.22 (95% confidence interval: 0.09, 0.34) percentage point increase in stroke prevalence. PPR explained 5.6% (2.4, 8.9) of stroke prevalence in the exposed areas. These values differed by states: 1.1% (0.5, 1.7) in Alabama to 11.7% (4.9, 18.6) in Mississippi, and by census tract-level: 0.08% (0.03, 0.13) to 25.3% (10.6, 40.0). PPR is associated with self-reported stroke prevalence, suggesting possible links between pollutants emitted from refineries and stroke. The increased prevalence due to PPR may differ by sociodemographic factors.
MLysPRED: graph-based multi-view clustering and multi-dimensional normal distribution resampling techniques to predict multiple lysine sites
Authors: Zuo Yun , Hong Yue , Zeng Xiangxiang , Zhang Qiang , Liu Xiangrong 
Published: August 2022

Abstract
Posttranslational modification of lysine residues, K-PTM, is one of the most popular PTMs. Some lysine residues in proteins can be continuously or cascaded covalently modified, such as acetylation, crotonylation, methylation and succinylation modification. The covalent modification of lysine residues may have some special functions in basic research and drug development. Although many computational methods have been developed to predict lysine PTMs, up to now, the K-PTM prediction methods have been modeled and learned a single class of K-PTM modification. In view of this, this study aims to fill this gap by building a multi-label computational model that can be directly used to predict multiple K-PTMs in proteins.
In this study, a multi-label prediction model, MLysPRED, is proposed to identify multiple lysine sites using features generated from human protein sequences. In MLysPRED, three kinds of multi-label sequence encoding algorithms (MLDBPB, MLPSDAAP, MLPSTAAP) are proposed and combined with three encoding strategies (CHHAA, DR and Kmer) to convert preprocessed lysine sequences into effective numerical features. A multidimensional normal distribution oversampling technique and graph-based multi-view clustering under-sampling algorithm were first proposed and incorporated to reduce the proportion of the original training samples, and multi-label nearest neighbor algorithm is used for classification. It is observed that MLysPRED achieved an Aiming of 92.21%, Coverage of 94.98%, Accuracy of 89.63%, Absolute-True of 81.46% and Absolute-False of 0.0682 on the independent datasets. Additionally, comparison of results with five existing predictors also indicated that MLysPRED is very promising and encouraging to predict multiple K-PTMs in proteins. For the convenience of the experimental scientists, ‘MLysPRED’ has been deployed as a user-friendly web-server at http://47.100.136.41:8181.
Open Source Solutions in Experimental Design: An Introduction to the Symposium
Authors: Tanner Richelle L , Onthank Kirt L 
Published: August 2022

Abstract
The Open Science movement has increased dramatically in popularity with deserved calls to action around transparency, access to resources, and inclusion in our field. However, its practical applications within experimental design have been slow to uptake, with researchers unsure where to even start with the dizzying array of open source hardware and software solutions available. The perceived time investment and unknown cost, especially in implementing open source hardware, has stagnated the implementation of inexpensive experimental solutions, but we sought to increase awareness to lower the barrier to participation in this space. While there are countless technical and financial advantages to integrating open source solutions into every biologist's experimental design, we put an emphasis on the “people” part of the equation in our symposium. This symposium championed innovative experimental designs by early career Society for Integrative and Comparative Biology researchers across all fields of biology, from plants to animals, in the lab or in the field, or even virtually engaging with the public and students. The Open Science movement operates within community norms that champion transparency, continuous development, and collaboration. These values are congruent with the priorities of reducing barriers to participation in science, and we hope our symposium's collection of open source solutions encourages readers to adopt these or other innovative designs into their own experimentation.
Designing, generating, and translating deep-ocean observations for and with international policy makers
Authors: Levin Lisa A , Cimoli Laura , Gjerde Kristina , Harden-Davies Harriet , Heimbach Patrick , LaScala-Gruenewald Diana , Pachiadaki Maria , Pillar Helen R , Smith Leslie M , Stocks Karen , Stopa Justin E , Wright Dawn J 
Published: August 2022

Abstract
Deep-ocean observing is essential for informing policy making in the arenas of climate, biodiversity, fisheries, energy and minerals extraction, pollution, hazards, and genetic resources. The Deep Ocean Observing Strategy (DOOS), a UN Ocean Decade endorsed programme, is meeting with representatives from relevant international bodies and agreements to strengthen their interface with the deep-ocean science community, ensure that deep observing is responsive to societal needs, identify points of entry for science in policy making, and to develop relevant products for broad use. DOOS collaboration with the Environmental Systems Research Institute (Esri) facilitates this co-design. A DOOS policy liaison team is being formed to link the contacts, voices, and messaging of multiple deep-ocean networks and organizations in reaching international policy makers. The UN Ocean Decade will help to gain the ear of target communities, scale communication channels appropriately, minimize duplicative efforts, maximize limited resources, and organize inclusive and equitable public and private partners in deep-ocean science and policy.
Digital health for climate change mitigation and response: a scoping review
Authors: Rahimi-Ardabili Hania , Magrabi Farah , Coiera Enrico 
Published: August 2022

AbstractObjectiveClimate change poses a major threat to the operation of global health systems, triggering large scale health events, and disrupting normal system operation. Digital health may have a role in the management of such challenges and in greenhouse gas emission reduction. This scoping review explores recent work on digital health responses and mitigation approaches to climate change.Materials and MethodsWe searched Medline up to February 11, 2022, using terms for digital health and climate change. Included articles were categorized into 3 application domains (mitigation, infectious disease, or environmental health risk management), and 6 technical tasks (data sensing, monitoring, electronic data capture, modeling, decision support, and communication). The review was PRISMA-ScR compliant.ResultsThe 142 included publications reported a wide variety of research designs. Publication numbers have grown substantially in recent years, but few come from low- and middle-income countries. Digital health has the potential to reduce health system greenhouse gas emissions, for example by shifting to virtual services. It can assist in managing changing patterns of infectious diseases as well as environmental health events by timely detection, reducing exposure to risk factors, and facilitating the delivery of care to under-resourced areas.DiscussionWhile digital health has real potential to help in managing climate change, research remains preliminary with little real-world evaluation.ConclusionSignificant acceleration in the quality and quantity of digital health climate change research is urgently needed, given the enormity of the global challenge.
Impact of digital dermatitis on locomotion and gait traits of beef cattle
Authors: Thomas Anice D , Orsel Karin , Pajor Ed A 
Published: August 2022

AbstractDigital dermatitis (DD) is an infectious skin disease and a major cause of lameness that significantly impacts cattle productivity and welfare. However, DD does not always result in lameness and lameness scoring systems are not specific to hoof pathologies. Digital dermatitis detection protocols could be improved by including gait traits most related to DD. The aims of this study were to 1) determine the association between DD M-stage (“M” for Mortellaro), locomotion, and gait traits: arched back (AB), asymmetric gait (AG), head bobbing (HB), tracking up (TU), and reluctance to bear weight (WB), and 2) determine which traits are most associated with DD. Cattle (n = 480) from three feedlots were enrolled. Locomotion score (LS) and gait traits were assessed as cattle walked four strides along a dirt alleyway. Next, cattle were restrained in a chute, each hind foot lifted, and DD M-stage (absent, active, or chronic) determined. The association between presence of DD, LS, and gait traits were scored independently (n = 291). For both LS and gait the lowest score represents normal and the highest score severely altered. Digital dermatitis presence was associated with higher LS (P &lt; 0.001). Odds ratios (ORs) for cattle with DD being lame or moderately to severely lame were 8.0 (P &lt; 0.001) and 10.1 (P &lt; 0.001) times more than cattle without lesions. Cattle with active lesions had the greatest odds of being lame (OR = 9.4; P &lt; 0.001). Digital dermatitis presence was associated with all gait traits (P &lt; 0.001), where AG (OR = 5.5; P &lt; 0.001) and WB (OR = 5.8; P &lt; 0.001) had the greatest OR for classifying cattle with DD as having altered gait. The OR for cattle with active lesions having altered gait was greatest for WB which was 6.0 (P &lt; 0.001) times greater than cattle without lesions. The OR for cattle with chronic lesions having altered gait was greatest for AG being 6.5 (P &lt; 0.001) times more than cattle without lesions. All gait traits had low sensitivity (Se) for detecting cattle with DD and varied from 6.7% to 55.8%. Locomotion score (Se 55.8%) and AG (Se 44.2%) were most predictive with positive predictive values of 76.6% and 74.3%, respectively. Specificity for all traits ranged from 94.1% for LS to 98.4% for WB with negative predictive values of 72.1% and 68.9%, respectively. In conclusion, LS, WB, and AG had the strongest association with cattle that had DD. Locomotion scoring that includes a focus on WB and AG is the best tool to detect DD in beef cattle.
Characterization of Field-Derived Drosophila suzukii (Diptera: Drosophilidae) Resistance to Pyrethroids in California Berry Production
Authors: Ganjisaffar Fatemeh , Demkovich Mark R , Chiu Joanna C , Zalom Frank G 
Published: August 2022

Abstract
The spotted-wing drosophila, Drosophila suzukii (Matsumura), is a global economic pest of berry crops and stone fruit. Since management of this pest primarily relies on calendar insecticide applications, and field-derived resistance to spinosad has already been documented in California caneberry production, there is significant concern for development of resistance to other insecticides. In this study, susceptibility of D. suzukii populations collected from caneberry and strawberry fields to two pyrethroids, zeta-cypermethrin, and bifenthrin, was assessed in 2019 and 2020. Resistance to both pyrethroids were observed in flies from all sampling sites. For flies collected from caneberries in 2019, the LC50 values ranged from 4.5 to 5.2 mg liter−1 with RR50s ranging from 7.5- to 8.7-fold. Our 2020 assays showed that susceptibility of flies to the discriminating dose of zeta-cypermethrin decreased significantly as the season progressed. For flies collected from strawberries in 2020, the LC50s ranged from 19.0 to 36.1 mg liter−1 and from 30.3 to 90.7 mg liter−1 for zeta-cypermethrin and bifenthrin, respectively. The RR50 values varied from 19.0- to 36.1-fold for zeta-cypermethrin and from 15.9- to 47.7-fold for bifenthrin. This study is the first report of field-derived pyrethroid resistance in D. suzukii from two major California berry production areas. Adoption of informed insecticide resistance management practices would be essential to prolong the efficacy of products available to control D. suzukii. Future molecular work is needed to unravel the underlying genetic mechanisms conferring the observed pyrethroid resistance and to develop robust diagnostics that can inform integrated pest management of this pest.
The formation of early-type galaxies through monolithic collapse of gas clouds in Milgromian gravity
Authors: Eappen Robin , Kroupa Pavel , Wittenburg Nils , Haslbauer Moritz , Famaey Benoit 
Published: August 2022

ABSTRACT
Studies of stellar populations in early-type galaxies (ETGs) show that the more massive galaxies form earlier and have a shorter star formation history. In this study, we investigate the initial conditions of ETG formation. The study begins with the collapse of non-rotating post-Big-Bang gas clouds in Milgromian (MOND) gravitation. These produce ETGs with star-forming time-scales (SFT) comparable to those observed in the real Universe. Comparing these collapse models with observations, we set constraints on the initial size and density of the post-Big-Bang gas clouds in order to form ETGs. The effective-radius–mass relation of the model galaxies falls short of the observed relation. Possible mechanisms for later radius expansion are discussed. Using hydrodynamic MOND simulations, this work thus for the first time shows that the SFTs observed for ETGs may be a natural occurrence in the MOND paradigm. We show that different feedback algorithms change the evolution of the galaxies only to a very minor degree in MOND. The first stars have, however, formed more rapidly in the real Universe than possible just from the here studied gravitational collapse mechanism. Dark-matter-based cosmological structure formation simulations disagree with the observed SFTs at more than 5σ confidence.
A multiwavelength study of nearby star-forming spiral galaxies and the clustering of star formation in M63
Authors: Smith Madison V , van Zee L , Dale D A , Staudaher S , Wrock T 
Published: August 2022

ABSTRACT
This multiwavelength study of the star formation and star formation history (SFH) trends in the nearby universe looks at nine nearby late-type spirals. Spectral energy distributions fitted with measurements from the far-ultraviolet (FUV) to the mid-infrared are used to estimate parameters in a double-exponential SFH. Azimuthally averaged radial trends in the SFHs are shown and discussed for each galaxy. In addition to the radial analysis, catalogues of UV-selected sources are identified for each galaxy. An analysis of the clustering of the UV sources in M63 (NGC 5055) is done using a two-point correlation function. There is evidence for hierarchical star formation and clustering out to scales of several kpc. We then discuss the level of clustering in M63’s sources with differing FUV − NUV colours, and how spiral arms may play a role in the organization of star formation even in the low surface brightness regions of a galaxy.
Characterization of hot populations of Melotte 66 open cluster using Swift/UVOT
Authors: Rao Khushboo K , Vaidya Kaushar , Agarwal Manan , Panthi Anju , Jadhav Vikrant , Subramaniam Annapurni 
Published: August 2022

ABSTRACT
Ultraviolet (UV) wavelength observations have made a significant contribution to our understanding of hot stellar populations of star clusters. Multiwavelength spectral energy distributions (SEDs) of stars, including ultraviolet observations, have proven to be an excellent tool for discovering unresolved hot companions in exotic stars such as blue straggler stars (BSS), thereby providing helpful clues to constrain their formation mechanisms. Melotte 66 is a 3.4 Gyr old open cluster located at a distance of 4810 pc. We identify the cluster members by applying the ML-MOC algorithm on Gaia EDR3 data. Based on our membership identification, we find 1162 members, including 14 BSS candidates, 2 yellow straggler candidates (YSS), and one subdwarf B candidate (sdB). We generated SEDs for 11 BSS candidates and the sdB candidate using Swift/UVOT data combined with other archival data in the optical and IR wavelengths. We discover a hot companion of one BSS candidate, BSS3, with temperature of 38 000$_{-6000}^{+7000}$ K, luminosity of 2.99$_{-1.86}^{+5.47}$ L⊙, and radius of 0.04$_{-0.005}^{+0.008}$ R⊙. This hot companion is a likely low-mass WD with an estimated mass of 0.24–0.44 M⊙. We report one BSS candidate, BSS6, as an Algol-type eclipsing binary with a period of 0.8006 d, based on the Gaia DR3 variability classification. We suggest that BSS3 is formed via either the Case A or Case B mass-transfer channel, whereas BSS6 is formed via the Case A mass transfer.
The Mantis Network II: examining the 3D high-resolution observable properties of the UHJs WASP-121b and WASP-189b through GCM modelling
Authors: Lee Elspeth K H , Prinoth Bibiana , Kitzmann Daniel , Tsai Shang-Min , Hoeijmakers Jens , Borsato Nicholas W , Heng Kevin 
Published: August 2022

ABSTRACT
The atmospheres of ultra hot Jupiters (UHJs) are prime targets for the detection of molecules and atoms at both low and high spectral resolution. We study the atmospheres of the UHJs WASP-121b and WASP-189b by performing 3D general circulation models (GCMs) of these planets using high temperature correlated-k opacity schemes with ultra-violet (UV) absorbing species included. The GCM results are then post-processed at low and high spectral resolutions and compared to available data. The high resolution results are cross-correlated with molecular and atomic templates to produce mock molecular detections. Our GCM models produce similar temperature-pressure (T-p) structure trends to previous 1D radiative-convective equilibrium models of UHJs. Furthermore, the inclusion of UV opacities greatly shapes the thermal and dynamical properties of the high-altitude, low-pressure regions of the UHJ atmospheres, with sharp T-p inversions due to the absorption of UV light. This suggests that optical wavelength, high-resolution observations probe a dynamically distinct upper atmospheric region, rather than the deeper jet forming layers.
Modelling observable signatures of jet-ISM interaction: thermal emission and gas kinematics
Authors: Meenakshi Moun , Mukherjee Dipanjan , Wagner Alexander Y , Nesvadba Nicole P H , Bicknell Geoffrey V , Morganti Raffaella , Janssen Reinier M J , Sutherland Ralph S , Mandal Ankush 
Published: August 2022

ABSTRACT
Relativistic jets are believed to have a substantial impact on the gas dynamics and evolution of the interstellar medium (ISM) of their host galaxies. In this paper, we aim to draw a link between the simulations and the observable signatures of jet-ISM interactions by analyzing the emission morphology and gas kinematics resulting from jet-induced shocks in simulated disc and spherical systems. We find that the jet-induced laterally expanding forward shock of the energy bubble sweeping through the ISM causes large-scale outflows, creating shocked emission and high-velocity dispersion in the entire nuclear regions (∼2 kpcs) of their hosts. The jetted systems exhibit larger velocity widths (&gt;800 km s−1), broader Position-Velocity maps and distorted symmetry in the disc’s projected velocities than systems without a jet. We also investigate the above quantities at different inclination angles of the observer with respect to the galaxy. Jets inclined to the gas disc of its host are found to be confined for longer times, and consequently couple more strongly with the disc gas. This results in prominent shocked emission and high-velocity widths, not only along the jet’s path, but also in the regions perpendicular to them. Strong interaction of the jet with a gas disc can also distort its morphology. However, after the jets escape their initial confinement, the jet-disc coupling is weakened, thereby lowering the shocked emission and velocity widths.