bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations Between Natural Language Processing–Enriched Social Determinants of Health and Suicide Death Among US Veterans
Authors: Mitra Avijit , Pradhan Richeek , Melamed Rachel D. , Chen Kun , Hoaglin David C. , Tucker Katherine L. , Reisman Joel I. , Yang Zhichao , Liu Weisong , Tsai Jack , Yu Hong 
Published: March 2023

ImportanceSocial determinants of health (SDOHs) are known to be associated with increased risk of suicidal behaviors, but few studies use SDOHs from unstructured electronic health record notes.ObjectiveTo investigate associations between veterans’ death by suicide and recent SDOHs, identified using structured and unstructured data.Design, Setting, and ParticipantsThis nested case-control study included veterans who received care under the US Veterans Health Administration from October 1, 2010, to September 30, 2015. A natural language processing (NLP) system was developed to extract SDOHs from unstructured clinical notes. Structured data yielded 6 SDOHs (ie, social or familial problems, employment or financial problems, housing instability, legal problems, violence, and nonspecific psychosocial needs), NLP on unstructured data yielded 8 SDOHs (social isolation, job or financial insecurity, housing instability, legal problems, barriers to care, violence, transition of care, and food insecurity), and combining them yielded 9 SDOHs. Data were analyzed in May 2022.ExposuresOccurrence of SDOHs over a maximum span of 2 years compared with no occurrence of SDOH.Main Outcomes and MeasuresCases of suicide death were matched with 4 controls on birth year, cohort entry date, sex, and duration of follow-up. Suicide was ascertained by National Death Index, and patients were followed up for up to 2 years after cohort entry with a study end date of September 30, 2015. Adjusted odds ratios (aORs) and 95% CIs were estimated using conditional logistic regression.ResultsOf 6 122 785 veterans, 8821 committed suicide during 23 725 382 person-years of follow-up (incidence rate 37.18 per 100 000 person-years). These 8821 veterans were matched with 35 284 control participants. The cohort was mostly male (42 540 [96.45%]) and White (34 930 [79.20%]), with 6227 (14.12%) Black veterans. The mean (SD) age was 58.64 (17.41) years. Across the 5 common SDOHs, NLP-extracted SDOH, on average, retained 49.92% of structured SDOHs and covered 80.03% of all SDOH occurrences. SDOHs, obtained by structured data and/or NLP, were significantly associated with increased risk of suicide. The 3 SDOHs with the largest effect sizes were legal problems (aOR, 2.66; 95% CI, 2.46-2.89), violence (aOR, 2.12; 95% CI, 1.98-2.27), and nonspecific psychosocial needs (aOR, 2.07; 95% CI, 1.92-2.23), when obtained by combining structured data and NLP.Conclusions and RelevanceIn this study, NLP-extracted SDOHs, with and without structured SDOHs, were associated with increased risk of suicide among veterans, suggesting the potential utility of NLP in public health studies.
A systematic map of knowledge exchange across the science‐policy interface for forest science: How can we improve consistency and effectiveness?
Authors: Westwood Alana R. , Hutchen Jenna , Kapoor Tyreen , Klenk Kimberly , Saturno Jacquelyn , Antwi Effah K. , Egunyu Felicitas , Cortini Francesco , Robertson Manjulika , Le Noble Sophie , Wang Jonathan , Falconer Matthew , Nguyen Vivian M. 
Published: March 2023

Abstract

Knowledge produced by scientists is essential to the policy and practice of managing natural resources, including forests. However, there has never been systematic mapping of which techniques in knowledge exchange (KE) have been applied in the forest sciences, by whom, and to what effect. We examined KE techniques documented in the forest sciences globally.

We used standardized search strings in English and French across two academic search engines (BASE and Scopus) and a specialist website (ResearchGate) to locate relevant items. We screened items, extracted data, conducted qualitative and quantitative analysis, and built a network visualization diagram to demonstrate knowledge flow.

Our final map included 122 items published from 1998 to 2020, with most published after 2010. Items mentioned organizations from 66 countries as knowledge producers or users. The interactive network visualization diagram displays linkages between organizations, sectors and countries. We found that most of the KE activity involved the Global North (89%). Governments were the most common knowledge users, and industry was frequently reported as a user but rarely a producer. Academia was both producer and user. Indigenous, local, traditional or community knowledge was included in 24% of items, but these communities were not associated with any coauthor affiliations. Reported funders were universities, governments, non‐profits or foundations. We found 90 unique terms in the items related to KE with less than 25% of terms used in more than one item. Fifteen per cent of item keywords related to KE. The most commonly identified enabling conditions for KE were trust, funding and established relationships, while major barriers were challenges for translation of science and lack of time.

To improve searchability of information related to KE and encourage a culture of considering KE in scientific research and forest management work, we recommend a common lexicon of ‘knowledge exchange’/‘échange de connaisances’. We recommend that more effort be given to forest science‐related KE connections between the Global North and South as well as a deliberate collection of evidence for the effectiveness of KE techniques. Researchers and practitioners can use our KE typology to identify their goals and design appropriate evaluation measures.
Geometric and dosimetric evaluation of deep learning based auto‐segmentation for clinical target volume on breast cancer
Authors: Zhong Yang , Guo Ying , Fang Yingtao , Wu Zhiqiang , Wang Jiazhou , Hu Weigang 
Published: March 2023

AbstractBackgroundRecently, target auto‐segmentation techniques based on deep learning (DL) have shown promising results. However, inaccurate target delineation will directly affect the treatment planning dose distribution and the effect of subsequent radiotherapy work. Evaluation based on geometric metrics alone may not be sufficient for target delineation accuracy assessment. The purpose of this paper is to validate the performance of automatic segmentation with dosimetric metrics and try to construct new evaluation geometric metrics to comprehensively understand the dose‐response relationship from the perspective of clinical application.Materials and MethodsA DL‐based target segmentation model was developed by using 186 manual delineation modified radical mastectomy breast cancer cases. The resulting DL model were used to generate alternative target contours in a new set of 48 patients. The Auto‐plan was reoptimized to ensure the same optimized parameters as the reference Manual‐plan. To assess the dosimetric impact of target auto‐segmentation, not only common geometric metrics but also new spatial parameters with distance and relative volume () to target were used. Correlations were performed using Spearman's correlation between segmentation evaluation metrics and dosimetric changes.ResultsOnly strong (|R2| > 0.6, p < 0.01) or moderate (|R2| > 0.4, p < 0.01) Pearson correlation was established between the traditional geometric metric and three dosimetric evaluation indices to target (conformity index, homogeneity index, and mean dose). For organs at risk (OARs), inferior or no significant relationship was found between geometric parameters and dosimetric differences. Furthermore, we found that OARs dose distribution was affected by boundary error of target segmentation instead of distance and to target.ConclusionsCurrent geometric metrics could reflect a certain degree of dose effect of target variation. To find target contour variations that do lead to OARs dosimetry changes, clinically oriented metrics that more accurately reflect how segmentation quality affects dosimetry should be constructed.
A roadmap for implementation of kV‐CBCT online adaptive radiation therapy and initial first year experiences
Authors: Stanley Dennis N. , Harms Joseph , Pogue Joel A. , Belliveau Jean‐Guy , Marcrom Samuel R. , McDonald Andrew M. , Dobelbower Michael C. , Boggs Drexell H. , Soike Michael H. , Fiveash John A. , Popple Richard A. , Cardenas Carlos E. 
Published: March 2023

AbstractPurposeOnline Adaptive Radiation Therapy (oART) follows a different treatment paradigm than conventional radiotherapy, and because of this, the resources, implementation, and workflows needed are unique. The purpose of this report is to outline our institution's experience establishing, organizing, and implementing an oART program using the Ethos therapy system.MethodsWe include resources used, operational models utilized, program creation timelines, and our institutional experiences with the implementation and operation of an oART program. Additionally, we provide a detailed summary of our first year's clinical experience where we delivered over 1000 daily adaptive fractions. For all treatments, the different stages of online adaption, primary patient set‐up, initial kV‐CBCT acquisition, contouring review and edit of influencer structures, target review and edits, plan evaluation and selection, Mobius3D 2nd check and adaptive QA, 2nd kV‐CBCT for positional verification, treatment delivery, and patient leaving the room, were analyzed.ResultsWe retrospectively analyzed data from 97 patients treated from August 2021–August 2022. One thousand six hundred seventy seven individual fractions were treated and analyzed, 632(38%) were non‐adaptive and 1045(62%) were adaptive. Seventy four of the 97 patients (76%) were treated with standard fractionation and 23 (24%) received stereotactic treatments. For the adaptive treatments, the generated adaptive plan was selected in 92% of treatments. On average(±std), adaptive sessions took 34.52 ± 11.42 min from start to finish. The entire adaptive process (from start of contour generation to verification CBCT), performed by the physicist (and physician on select days), was 19.84 ± 8.21 min.ConclusionWe present our institution's experience commissioning an oART program using the Ethos therapy system. It took us 12 months from project inception to the treatment of our first patient and 12 months to treat 1000 adaptive fractions. Retrospective analysis of delivered fractions showed that the average overall treatment time was approximately 35 min and the average time for the adaptive component of treatment was approximately 20 min.
Entanglement in Smart Hydrogels: Fast Response Time, Anti‐Freezing and Anti‐Drying
Authors: Feng Yuqin , Wang Shancheng , Li Yaqin , Ma Wenxia , Zhang Gang , Yang Ming , Li Haibo , Yang Yongsheng , Long Yi 
Published: March 2023

AbstractThe common techniques to improve hydrogel's mechanical properties include increasing crosslinking density and forming crosslinked double‐network hydrogel, which may cause some hydrogels to lose their smart functionalities. Inspired by entanglement‐induced strengthening, a simple approach to introducing hydroxypropyl cellulose (HPC) fibers entangled with different smart hydrogel matrix systems are reported. Different from the conventional methods which hinder the movement of the polymer network, through entanglement with HPC fibers, the composite hydrogel shows both improved Young's modulus and toughness and more importantly improved smart functionalities including response speed, anti‐drying, and anti‐freezing capabilities and cycle stability. This strategy provides a new design rule to fabricate durable and strengthened smart hydrogels which can be used in smart windows, sensors, and soft robots.
Highly Flexible Carbon Film Implanted with Single‐Atomic Zn−N2 Moiety for Long‐Life Sodium‐Sulfur Batteries
Authors: Yao Ge , Li Zhiqiang , Zhang Yuhang , Xiao Yue , Wei Lingzhi , Niu Helin , Chen Qianwang , Yang Yang , Zheng Fangcai 
Published: March 2023

AbstractRoom‐temperature sodium‐sulfur (RT Na–S) batteries are regarded as one of promising next‐generation energy storage systems owing to the high theoretical energy density (1274 Wh kg−1) and rich abundance of the raw materials. However, the sluggish redox kinetics and low electrical conductivity of sulfur (S) cathode significantly imped their practical application. Herein, a flexible carbon film implanted with single‐atomic Zn−N2 moiety (Zn‐N2/CF) is constructed as the efficient S host material to effectively improve the redox kinetics and electrical conductivity. The theoretical and experimental results show that, compared to Zn−N4 center, unsaturated Zn−N2 center with asymmetric electron distribution has significant advantages in anchoring and activating sodium polysulfides to accelerate the conversion from S8 to Na2S and reducing the reaction energy barrier of Na2S decomposition. Consequently, Zn‐N2/CF/S can retain a reversible capacity of 838.5 mAh g−1 at 0.1 A g−1 after 100 cycles, which is higher than that of Zn‐N4/CF/S (688.0 mAh g−1). Moreover, Zn‐N2/CF/S also maintains a long‐term cycling performance with a negligible capacity decay rate of 0.006% per cycle over 4000 cycles at 10 A g−1. This work provides an effective strategy to obtain the flexible carbon film implanted with unsaturated single‐atomic structure, thereby ultimately resulting in high‐performance RT Na–S batteries.
A Polymer Defect Passivator for Efficient Hole‐Conductor‐Free Printable Mesoscopic Perovskite Solar Cells
Authors: Xiang Junwei , Han Chuanzhou , Qi Jianhang , Cheng Yanjie , Chen Kai , Ma Yongming , Xie Jiayu , Hu Yue , Mei Anyi , Zhou Yinhua , Han Hongwei 
Published: March 2023

AbstractDue to the low cost and excellent potential for mass production, printable mesoscopic perovskite solar cells (p‐MPSCs) have drawn a lot of attention among other device structures. However, the low open‐circuit voltage (VOC) of such devices restricts their power conversion efficiency (PCE). This limitation is brought by the high defect density at perovskite grain boundaries in the mesoporous scaffold, which results in severe nonradiative recombination and is detrimental to the VOC. To improve the perovskite crystallization process, passivate the perovskite defects, and enhance the PCE, additive engineering is an effective way. Herein, a polymeric Lewis base polysuccinimide (PSI) is added to the perovskite precursor solution as an additive. It improves the perovskite crystallinity and its carbonyl groups strongly coordinate with Pb2+, which can effectively passivate defects. Additionally, compared with its monomer, succinimide (SI), PSI serves as a better defect passivator because the long‐chained macromolecule can be firmly anchored on those defect sites and form a stronger interaction with perovskite grains. As a result, the champion device has a PCE of 18.84%, and the VOC rises from 973 to 1030 mV. This study offers a new strategy for fabricating efficient p‐MPSCs.
Monolithic Zirconium‐Based Metal–Organic Frameworks for Energy‐Efficient Water Adsorption Applications
Authors: Çamur Ceren , Babu Robin , Suárez del Pino José A. , Rampal Nakul , Pérez‐Carvajal Javier , Hügenell Philipp , Ernst Sebastian‐Johannes , Silvestre‐Albero Joaquin , Imaz Inhar , Madden David G. , Maspoch Daniel , Fairen‐Jimenez David 
Published: March 2023

AbstractSpace cooling and heating, ventilation, and air conditioning (HVAC) accounts for roughly 10% of global electricity use and are responsible for ca. 1.13 gigatonnes of CO2 emissions annually. Adsorbent‐based HVAC technologies have long been touted as an energy‐efficient alternative to traditional refrigeration systems. However, thus far, no suitable adsorbents have been developed which overcome the drawbacks associated with traditional sorbent materials such as silica gels and zeolites. Metal–organic frameworks (MOFs) offer order‐of‐magnitude improvements in water adsorption and regeneration energy requirements. However, the deployment of MOFs in HVAC applications has been hampered by issues related to MOF powder processing. Herein, three high‐density, shaped, monolithic MOFs (UiO‐66, UiO‐66‐NH2, and Zr‐fumarate) with exceptional volumetric gas/vapor uptake are developed—solving previous issues in MOF‐HVAC deployment. The monolithic structures across the mesoporous range are visualized using small‐angle X‐ray scattering and lattice‐gas models, giving accurate predictions of adsorption characteristics of the monolithic materials. It is also demonstrated that a fragile MOF such as Zr‐fumarate can be synthesized in monolithic form with a bulk density of 0.76 gcm−3 without losing any adsorption performance, having a coefficient of performance (COP) of 0.71 with a low regeneration temperature (≤ 100 °C).
Localized Bound Multiexcitons in Engineered Quasi‐2D Perovskites Grains at Room Temperature for Efficient Lasers
Authors: Li Guohui , Lin Kai , Zhao Kefan , Huang Yang , Ji Ting , Shi Linlin , Hao Yuying , Xiong Qihua , Zheng Kaibo , Pullerits Tonu , Cui Yanxia 
Published: March 2023

AbstractReducing the excitation threshold to minimize the Joule heating is critical for the realization of perovskite laser diodes. Although bound excitons are promising for low threshold laser, how to generate them at room temperature for laser applications is still unclear in quasi‐2D perovskite‐based devices. In this work, via engineering quasi‐2D perovskite PEA2(CH3NH3)n‐1PbnBr3n+1 microscopic grains by the anti‐solvent method, room‐temperature multiexciton radiative recombination is successfully demonstrated at a remarkably low pump density of 0.97 µJ cm−2, which is only one‐fourth of that required in 2D CdSe nanosheets. In addition, the well‐defined translational momentum in quasi‐2D perovskite grains can restrict the Auger recombination which is detrimental to radiative emission. Furthermore, the quasi‐2D perovskite grains are favorable for increasing binding energies of excitons and biexcitons and so as the related radiative recombination. Consequently, the prepared <n = 8> phase quasi‐2D perovskite film renders a threshold of room‐temperature stimulated emission as low as 13.7 µJ cm−2, reduced by 58.6% relative to the amorphous counterpart with larger grains. The findings in this work are expected to facilitate the development of solution‐processable perovskite multiexcitonic laser diodes.
Defect‐Induced, Ferroelectric‐Like Switching and Adjustable Dielectric Tunability in Antiferroelectrics
Authors: Pan Hao , Tian Zishen , Acharya Megha , Huang Xiaoxi , Kavle Pravin , Zhang Hongrui , Wu Liyan , Chen Dongfang , Carroll John , Scales Robert , Meyers Cedric J. G. , Coleman Kathleen , Hanrahan Brendan , Spanier Jonathan E. , Martin Lane W. 
Published: March 2023

AbstractAntiferroelectrics, which undergo a field‐induced phase transition to ferroelectric order that manifests as double‐hysteresis polarization switching, exhibit great potential for dielectric, electromechanical, and electrothermal applications. Compared to their ferroelectric cousins, however, considerably fewer efforts have been made to understand and control antiferroelectrics. Here, it is demonstrated that the polarization switching behavior of an antiferroelectric can be strongly influenced and effectively regulated by point defects. In films of the canonical antiferroelectric PbZrO3, decreasing oxygen pressure during deposition (and thus increasing adatom kinetic energy) causes unexpected “ferroelectric‐like” polarization switching although the films remain in the expected antiferroelectric orthorhombic phase. This “ferroelectric‐like” switching is correlated with the creation of bombardment‐induced point‐defect complexes which pin the antiferroelectric–ferroelectric phase boundaries, and thus effectively delay the phase transition under changing field. The effective pinning energy is extracted via temperature‐dependent switching‐kinetics studies. In turn, by controlling the concentration of defect complexes, the dielectric tunability of the PbZrO3 can be adjusted, including being able to convert between “positive” and “negative” tunability near zero field. This work reveals the important role and strong capability of defects to engineer antiferroelectrics for new performance and functionalities.
Move Aside Pentacene: Diazapentacene‐Doped para‐Terphenyl, a Zero‐Field Room‐Temperature Maser with Strong Coupling for Cavity Quantum Electrodynamics
Authors: Ng Wern , Xu Xiaotian , Attwood Max , Wu Hao , Meng Zhu , Chen Xi , Oxborrow Mark 
Published: March 2023

AbstractMasers can deliver ultralow‐noise amplification of microwave signals in medical imaging and deep‐space communication, with recent research being rekindled through the discovery of gain media operating at room‐temperature, eschewing bulky cryogenics that hindered their use. This work shows the discovery of 6,13‐diazapentacene doped in para‐terphenyl (DAP:PTP) as a maser gain medium that can operate at room‐temperature, without an external magnetic field. With a maser output power of −10 dBm, it is on par with pentacene‐doped para‐terphenyl in masing power, while possessing compelling advantages such as faster amplification startup times, being pumped by longer wavelength light at 620 nm and greater chemical stability from nitrogen groups. Furthermore, the maser bursts from DAP:PTP allow one to reach the strong coupling regime for cavity quantum electrodynamics, with a high cooperativity of 182. The optical and microwave spin dynamics of DAP:PTP are studied in order to evaluate its capabilities as a maser gain medium, where it features fast intersystem crossing and an advantageously higher triplet quantum yield. The results pave the way for the future discovery of similar maser materials and help designate them as promising candidates for quantum sensors, optoelectronic devices and the study of cavity quantum electrodynamic effects at room‐temperature.
Digitally Printable Magnetic Liquid Metal Composite for Recyclable Soft‐Matter Electronics
Authors: Hajalilou Abdollah , Parvini Elahe , Pereira João Pedro Marques , Lopes Pedro Alhais , Silva André F. , De Almeida Anibal , Tavakoli Mahmoud 
Published: March 2023

AbstractThe increasing interest in epidermal patches for wearable monitoring makes it urgent to move toward “greener” and recyclable materials in printed electronics. However, combining scalable fabrication, stretchable function, and recyclable material architecture is challenging to achieve. Herein, this article introduces a printable biphasic liquid metal (LM)‐based composite that combines excellent electrical conductivity, high stretchability, low‐electromechanical gauge factor, printability, sinter‐free functionality, and compatibility with heat‐sensitive substrates, thanks to the sinter‐free formulation. The novel eutectic gallium indium LM‐nickel‐styrene‐isoprene (SIS) thermoplastic elastomer composite takes advantage of a “greener” solvent composed of a mixture of methyl acetate, cyclohexane, and 4‐chlorobenzotrifluoride compared to the toluene used in block copolymers (BCPs). Furthermore, it replaces the costly micron‐sized silver flake filler particles with nickel, a lower‐cost alternative that enables facile recyclability by using a magnetic force. The use of BCPs with non‐permanent physical cross‐links enables the possibility of recycling. A green route is shown for recycling the composite, using only bio‐friendly acids and daily used products such as sugar and Epsom salt. The application of these composites is shown through the digital printing of stretchable circuits and magnetic switches.