bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of antifungal activity of plant extracts against plant pathogen associated with sweet orange (Citrus sinensis L.), in Jimma, Western Ethiopia
Authors: Amenu Desalegn , Desalegn Ra’el , Nugusa Ayantu , Tolera Chimdesa , Tafesse Temesgen 
Published: July 2024

Abstract
Background
Sweet oranges are a vital agricultural commodity, but they are susceptible to various pathogenic fungi that can cause significant economic losses. This study aimed to evaluate the antifungal activity of plant extracts against pathogenic fungi attacking sweet oranges in Jimma, Ethiopia.

Materials and methods
Various plant extracts were obtained from locally available plant species and tested against selected pathogenic fungi using standard in vitro antifungal assays. The results revealed varying degrees of antifungal activity among the plant extracts, with some showing promising inhibitory effects against the targeted fungi. Statistical analysis indicated significant differences in antifungal efficacy among the tested extracts.

Results
The study found that Penicilium spp., Aspergillus spp., Rhizopus spp., Mucor spp., and Fusarium spp, were the predominant fungal species. The study found that the extracts of Vernonia amygdalina, Ginger oficealae, and Pterolobium stalatam were effective in inhibiting mycelial growth against these pathogens. This suggests the use of these medicinal plants for the preservation and control of sweet orange fruit in most of the Ethiopian region.

Conlusion
These findings suggest the potential of certain plant extracts as natural alternatives to synthetic fungicides for managing fungal diseases in sweet orange cultivation. Further research is needed to elucidate the mechanisms of action of these plant extracts and optimize their application in agricultural practices. This study contributes to the development of sustainable and eco-friendly strategies for plant disease management in the region.
Iteration-Free quantum approximate optimization algorithm using neural networks
Authors: Amosy Ohad , Danzig Tamuz , Lev Ohad , Porat Ely , Chechik Gal , Makmal Adi 
Published: July 2024

AbstractThe quantum approximate optimization algorithm (QAOA) is a leading iterative variational quantum algorithm for heuristically solving combinatorial optimization problems. A large portion of the computational effort in QAOA is spent by the optimization steps, which require many executions of the quantum circuit. Therefore, there is active research focusing on finding better initial circuit parameters, which would reduce the number of required iterations and hence the overall execution time. While existing methods for parameter initialization have shown great success, they often offer a single set of parameters for all problem instances. We propose a practical method that uses a simple, fully connected neural network that leverages previous executions of QAOA to find better initialization parameters tailored to a new given problem instance. We benchmark state-of-the-art initialization methods for solving the MaxCut problem of Erdős-Rényi graphs using QAOA and show that our method is consistently the fastest to converge while also yielding the best final result. Furthermore, the parameters predicted by the neural network are shown to match very well with the fully optimized parameters, to the extent that no iterative steps are required, thereby effectively realizing an iteration-free QAOA scheme.
Healthcare workers’ perspectives on a prescription phone program to meet the health equity needs of patients in the emergency department: a qualitative study
Authors: Hodwitz Kathryn , Ginocchio Galo F. , Fedorovsky Tali , Girdler Hannah , Bossin Brielle , Juando-Prats Clara , Dell Evelyn , Somers Andrea , Hulme Jennifer 
Published: July 2024

AbstractObjectivesPeople experiencing homelessness and marginalization face considerable barriers to accessing healthcare services. Increased reliance on technology within healthcare has exacerbated these inequities. We evaluated a hospital-based prescription phone program aimed to reduce digital health inequities and improve access to services among marginalized patients in Emergency Departments. We examined the perceived outcomes of the program and the contextual barriers and facilitators affecting outcomes.MethodsWe conducted a constructivist qualitative program evaluation at two urban, academic hospitals in Toronto, Ontario. We interviewed 12 healthcare workers about their perspectives on program implementation and outcomes and analyzed the interview data using reflexive thematic analysis.ResultsOur analyses generated five interrelated program outcomes: building trust with patients, facilitating independence in healthcare, bridging sectors of care, enabling equitable care for marginalized populations, and mitigating moral distress among healthcare workers. Participants expressed that phone provision is critical for adequately serving patients who face barriers to accessing health and social services, and for supporting healthcare workers who often lack resources to adequately serve these patients. We identified key contextual enablers and challenges that may influence program outcomes and future implementation efforts.ConclusionsOur findings suggest that providing phones to marginalized patient populations may address digital and social health inequities; however, building trusting relationships with patients, understanding the unique needs of these populations, and operating within a biopsychosocial model of health are key to program success.
Carbon emission efficiency and regional synergistic peaking strategies in Beijing-Tianjin-Hebei region
Authors: Gao Zixing , Xia Erman , Lin Sirui , Xu Jiaxin , Tao Chenlu , Yu Chang 
Published: July 2024

AbstractIn the context of China's resolute advancement of dual carbon goals (carbon peaking and carbon neutrality), urban agglomerations emerge as pivotal areas for carbon emission mitigation due to their dense economic activities and rapid urbanization. Previous studies overlook regional disparities in carbon emission prediction, disregarding the variations and policy directives across different provinces or cities. Therefore, this study addresses the research gap by investigating synergistic strategies to foster regional carbon peaking within the Beijing-Tianjin-Hebei region. Employing a novel approach tailored to regional segmentation policies, we provide more accurate predictions reflecting real-world conditions and distinct policy landscapes. Meanwhile, we integrate carbon emission efficiency into our analysis, emphasizing the dual goals of emission reduction and quality economic growth. Our empirical investigation in the Beijing-Tianjin-Hebei region, utilizing the Super-SBM and extended STIRPAT models, reveals upward trends in carbon emission efficiency, with varying trajectories across cities. Scenario simulations informed by the "14th Five-Year Plan" demonstrate that under the green development scenario, carbon peaking accelerates, alongside enhanced efficiency, supporting long-term emission reduction. Moreover, we design seven regional synergy carbon peak strategies for scenario simulations to facilitate the rational layout of dual carbon policies for collaborative development. We find that synergistic strategies have proven more effective in reducing regional carbon emission and increasing efficiency than strategies focusing solely on economic development or energy conservation. This innovative finding emphasizes the necessity of comprehensive green development in the Beijing-Tianjin-Hebei region and provides strong evidence for policymakers. Our research contributes to targeted strategies for improving carbon emission efficiency and reducing emissions, emphasizing the importance of synergistic approaches for regional carbon reduction.
Kaizen: A Street Smart Low Latency-Aware Resource Choreography Scheme for Decentralized Autonomous Organization (DAO) and Non-DAO Based Application Execution Over Blockchain and MEC Empowered 6 G Network
Authors: Chowdhury Mahfuzulhoq 
Published: July 2024

AbstractDecentralized autonomous organization (DAO)-based applications can revolutionize traditional centralized decision-making procedures and services by enabling scalable, decentralized, autonomous, and democratized decision-making processes. Unlike traditional applications, DAO-based decentralized applications use Ethereum blockchain-based smart contract programs to execute policies or make automated decisions. To that end, 6 G technologies can improve the latency and reliability of many existing blockchain-based DAOs. Previous research did not investigate the execution of DAO and non-DAO-based applications, as well as an adaptive resource choreography scheme, while accounting for various 6 G technologies, blockchain, and mobile-edge cloud (MEC). To prevail over the previous shortcomings, this article supplies a street smart multi-platform coordination, application scheduling, and low-latency-aware resource choreography scheme for both DAO and non-DAO-based application execution over blockchain and MEC-enabled 6 G networks by taking heterogenous DAO and non-DAO application count, application requirements, physical worker, virtual worker, and communication resource status into account. The results verified that the proposed kaizen scheme delivers at least 11.26% app work completion delay gain, 7.2% user energy overhead gain, 6.55% user economic charge gain, and 21% service provider profit than the compared schemes.
Opportunities and implementation pathway for China’s forestry development under the “Dual Carbon” strategy
Authors: Liu Houzhou , Wang Hui , Nong Huazhan , He Yutong , Chen Yinglong , Wang Hailong , Yu Min 
Published: July 2024

AbstractThe “Dual Carbon” initiative is a two-stage carbon reduction goal proposed by China, with significant implications for global climate change mitigation. This article examines the impact of the “Dual Carbon” strategy on China's forestry development and explores how to leverage this strategy to facilitate the transformation and advancement of the forestry sector. Current review indicated that forestry has the advantage of achieving higher emission reduction targets at a low cost. Starting with an overview of the “Dual Carbon” strategy, this paper analyzes the carbon sequestration potential of plants and soil, and the challenges and opportunities faced by forestry development under this framework. Furthermore, we outline implementation pathways for forestry development, aiming to provide insights for the progress of China's forestry sector. Overall, it should be noted that the priority is to vigorously develop timber resources, and we also need to vigorously develop and protect forestry talent with the support of China's policies. By trapping into the carbon storage capabilities and leveraging carbon trading mechanisms of forests, a favorable ecological environment can be created, thus achieving the goal of carbon neutrality.
Medical negligence and disclosure of alternative treatments
Authors: Tan Ming Ren 
Published: July 2024

Recent years have witnessed significant developments in medical negligence jurisprudence. In 2015, the Supreme Court in Montgomery v Lanarkshire Health Board famously departed from the House of Lords decision in Sidaway v Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital by ruling that the professional practice test set out in Bolam v Friern Hospital Management Committee no longer applied to the doctor's duty to give advice to the patient. In particular, the Supreme Court in Montgomery held as follows:
The doctor is … under a duty to take reasonable care to ensure that the patient is aware of any material risks involved in any recommended treatment, and of any reasonable alternative or variant treatments. The test of materiality is whether, in the circumstances of the particular case, a reasonable person in the patient's position would be likely to attach significance to the risk, or the doctor is or should reasonably be aware that the particular patient would be likely to attach significance to it.
Determinants of p53 DNA binding, gene regulation, and cell fate decisions
Authors: Fischer Martin , Sammons Morgan A. 
Published: July 2024

AbstractThe extent to which transcription factors read and respond to specific information content within short DNA sequences remains an important question that the tumor suppressor p53 is helping us answer. We discuss recent insights into how local information content at p53 binding sites might control modes of p53 target gene activation and cell fate decisions. Significant prior work has yielded data supporting two potential models of how p53 determines cell fate through its target genes: a selective target gene binding and activation model and a p53 level threshold model. Both of these models largely revolve around an analogy of whether p53 is acting in a “smart” or “dumb” manner. Here, we synthesize recent and past studies on p53 decoding of DNA sequence, chromatin context, and cellular signaling cascades to elicit variable cell fates critical in human development, homeostasis, and disease.
Effect of cross-platform gene-expression, computational methods on breast cancer subtyping in PALOMA-2 and PALLET studies
Authors: Cheang Maggie Chon U , Rimawi Mothaffar , Johnston Stephen , Jacobs Samuel A. , Bliss Judith , Pogue-Geile Katherine , Kilburn Lucy , Zhu Zhou , Schuster Eugene F. , Xiao Hui , Swaim Lisa , Deng Shibing , Lu Dongrui R. , Gauthier Eric , Tursi Jennifer , Slamon Dennis J. , Rugo Hope S. , Finn Richard S. , Liu Yuan 
Published: July 2024

AbstractIntrinsic breast cancer molecular subtyping (IBCMS) provides significant prognostic information for patients with breast cancer and helps determine treatment. This study compared IBCMS methods on various gene-expression platforms in PALOMA-2 and PALLET trials. PALOMA-2 tumor samples were profiled using EdgeSeq and nanostring and subtyped with AIMS, PAM50, and research-use-only (ruo)Prosigna. PALLET tumor biopsies were profiled using mRNA sequencing and subtyped with AIMS and PAM50. In PALOMA-2 (n = 222), a 54% agreement was observed between results from AIMS and gold-standard ruoProsigna, with AIMS assigning 67% basal-like to HER2-enriched. In PALLET (n = 224), a 69% agreement was observed between results from PAM50 and AIMS. Different IBCMS methods may lead to different results and could misguide treatment selection; hence, a standardized clinical PAM50 assay and computational approach should be used.Trial number: NCT01740427
Automated design of hybrid halide perovskite monolayers for band gap engineering
Authors: Hu Jie , Wang Jianwei , Chen Haiyuan , Niu Xiaobin 
Published: July 2024

AbstractThe recent experimental confirmation of perovskite monolayers has sparked ongoing efforts in their prediction and synthesis, showcasing their flexible tunable band gap and potential in advanced functional devices. Although large-scale computational designs have been successfully performed for inorganic perovskite monolayers, the complexity introduced by organic cations hinders the same approaches applied to the hybrid halide perovskite monolayers. To address this challenge, we have proposed a high-throughput first-principles computational workflow that automates the design of hybrid halide perovskite monolayers. We strategically reduce the complexity of the configurations by analyzing the orientation of cations and the structural symmetry. Over 400 hybrid halide perovskite monolayers have been designed, and their structures and fundamental properties are stored in the database. Correlation analyses show a strong correlation between band gaps and metal-halogen-metal bond angles or metal-halogen bond lengths, consistent with prior studies for bulk and layered perovskites. The underlying physics that the band gap is modulated by the antibonding in the metal-halogen bond makes band gap engineering of hybrid halide perovskite monolayers feasible. Accordingly, initial research on lateral heterojunctions and solar cells has been conducted to explore the potential practical applications of the designed hybrid halide perovskite monolayers. Our study lays the foundation for further exploration of hybrid halide perovskite monolayers and highlights promising opportunities for their potential applications in electronic and optical devices.
Property-guided generation of complex polymer topologies using variational autoencoders
Authors: Jiang Shengli , Dieng Adji Bousso , Webb Michael A. 
Published: July 2024

AbstractThe complexity and diversity of polymer topologies, or chain architectures, present substantial challenges in predicting and engineering polymer properties. Although machine learning is increasingly used in polymer science, applications to address architecturally complex polymers are nascent. Here, we use a generative machine learning model based on variational autoencoders and data generated from molecular dynamics simulations to design polymer topologies that exhibit target properties. Following the construction of a dataset featuring 1342 polymers with linear, cyclic, branch, comb, star, or dendritic structures, we employ a multi-task learning framework that effectively reconstructs and classifies polymer topologies while predicting their dilute-solution radii of gyration. This framework enables the generation of polymer topologies with target size, which is subsequently validated through molecular simulation. These capabilities are then exploited to contrast rheological properties of topologically distinct polymers with otherwise similar dilute-solution behavior. This research opens avenues for engineering polymers with more intricate and tailored properties with machine learning.
Deploying an asthma dashboard to support quality improvement across a nationally representative sentinel network of 7.6 million people in England
Authors: Mukherjee Mome , Okusi Cecilia , Jamie Gavin , Byford Rachel , Ferreira Filipa , Fletcher Monica , de Lusignan Simon , Sheikh Aziz 
Published: July 2024

AbstractEvery year, there are ~100,000 hospital admissions for asthma in the UK, many of which are potentially preventable. Evidence suggests that carefully conceptualised and implemented audit and feedback (A&F) cycles have the potential to improve clinical outcomes for those with chronic conditions. We wanted to investigate the technical feasibility of developing a near-real time asthma dashboard to support A&F interventions for asthma management in primary care. We extracted cross-sectional data on asthma from 756 participating GP practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) database in England comprising 7.6 million registered people. Summary indicators for a GP practice were compared to all participating RCGP RSC practices using practice-level data, for the week 6–12th-Mar-2023. A weekly, automated asthma dashboard with features that can support electronic-A&F cycles that compared key asthma indicators for a GP practice to RCGP RSC could be created (https://tinyurl.com/3ydtrt85): 12-weeks-incidence 0.4% vs 0.4%, annual prevalence 6.1% vs 6.7%, inhaled relievers to preventer 1.2 vs 1.1, self-management plan given 83.4% vs 60.8%, annual reviews 36.8% vs 57.3%, prednisolone prescriptions 2.0% vs 3.2%, influenza vaccination 56.6% vs 55.5%, pneumococcal vaccination ever (aged ≥65 years) 90.2% vs 84.1% and current smokers 14.9% vs 14.8%. Across the RCGP RSC, the rate of hospitalisations was 0.024%; comparative data had to be suppressed for the study practice because of small numbers. We have successfully created an automated near real-time asthma dashboard that can be used to support A&F initiatives to improve asthma care and outcomes in primary care.
Extant and extinct bilby genomes combined with Indigenous knowledge improve conservation of a unique Australian marsupial
Authors: Hogg Carolyn J. , Edwards Richard J. , Farquharson Katherine A. , Silver Luke W. , Brandies Parice , Peel Emma , Escalona Merly , Jaya Frederick R. , Thavornkanlapachai Rujiporn , Batley Kimberley , Bradford Tessa M. , Chang J. King , Chen Zhiliang , Deshpande Nandan , Dziminski Martin , Ewart Kyle M. , Griffith Oliver W. , Marin Gual Laia , Moon Katherine L. , Travouillon Kenny J. , Waters Paul , Whittington Camilla M. , Wilkins Marc R. , Helgen Kristofer M. , Lo Nathan , Ho Simon Y. W. , Ruiz Herrera Aurora , Paltridge Rachel , Marshall Graves Jennifer A. , Renfree Marilyn , Shapiro Beth , Ottewell Kym ,   Kiwirrkurra Rangers, Gibson Conway , Maxwell Raymond , Spencer Zecharia , Napangati Yalti , Butler Mary , West Janine , West John , James Mantua , Napangati Nolia , Gibson Loretta , West Payu , Gibson Angus , West Scott , West Kim , Japaltjari Walimpirri , Blackwood Ed , Rachel Paltridge  , Belov Katherine 
Published: July 2024

AbstractNinu (greater bilby, Macrotis lagotis) are desert-dwelling, culturally and ecologically important marsupials. In collaboration with Indigenous rangers and conservation managers, we generated the Ninu chromosome-level genome assembly (3.66 Gbp) and genome sequences for the extinct Yallara (lesser bilby, Macrotis leucura). We developed and tested a scat single-nucleotide polymorphism panel to inform current and future conservation actions, undertake ecological assessments and improve our understanding of Ninu genetic diversity in managed and wild populations. We also assessed the beneficial impact of translocations in the metapopulation (N = 363 Ninu). Resequenced genomes (temperate Ninu, 6; semi-arid Ninu, 6; and Yallara, 4) revealed two major population crashes during global cooling events for both species and differences in Ninu genes involved in anatomical and metabolic pathways. Despite their 45-year captive history, Ninu have fewer long runs of homozygosity than other larger mammals, which may be attributable to their boom–bust life history. Here we investigated the unique Ninu biology using 12 tissue transcriptomes revealing expression of all 115 conserved eutherian chorioallantoic placentation genes in the uterus, an XY1Y2 sex chromosome system and olfactory receptor gene expansions. Together, we demonstrate the holistic value of genomics in improving key conservation actions, understanding unique biological traits and developing tools for Indigenous rangers to monitor remote wild populations.
Direct observation of atmospheric turbulence with a video-rate wide-field wavefront sensor
Authors: Guo Yuduo , Hao Yuhan , Wan Sen , Zhang Hao , Zhu Laiyu , Zhang Yi , Wu Jiamin , Dai Qionghai , Fang Lu 
Published: July 2024

AbstractTurbulence is a complex and chaotic state of fluid motion. Atmospheric turbulence within the Earth’s atmosphere poses fundamental challenges for applications such as remote sensing, free-space optical communications and astronomical observation due to its rapid evolution across temporal and spatial scales. Conventional methods for studying atmospheric turbulence face hurdles in capturing the wide-field distribution of turbulence due to its transparency and anisoplanatism. Here we develop a light-field-based plug-and-play wide-field wavefront sensor (WWS), facilitating the direct observation of atmospheric turbulence over 1,100 arcsec at 30 Hz. The experimental measurements agreed with the von Kármán turbulence model, further verified using a differential image motion monitor. Attached to an 80 cm telescope, our WWS enables clear turbulence profiling of three layers below an altitude of 750 m and high-resolution aberration-corrected imaging without additional deformable mirrors. The WWS also enables prediction of the evolution of turbulence dynamics within 33 ms using a convolutional recurrent neural network with wide-field measurements, leading to more accurate pre-compensation of turbulence-induced errors during free-space optical communication. Wide-field sensing of dynamic turbulence wavefronts provides new opportunities for studying the evolution of turbulence in the broad field of atmospheric optics.