bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-year variation of near-surface ozone at Zhongshan Station, Antarctica
Authors: Tian Biao , Ding Minghu , Putero Davide , Li Chuanjin , Zhang Dongqi , Tang Jie , Zheng Xiangdong , Bian Lingen , Xiao Cunde 
Published: February 2022

Abstract
With the support of the Chinese National Antarctic Research Expedition, near-surface ozone (O3) was continuously monitored at Zhongshan Station (ZOS) (69°22′12″ S, 76°21′49″ E, 18.5 m above sea level) in East Antarctica from 2008 to 2020. The seasonal and diurnal variability of near-surface O3 at ZOS were investigated. O3 enhancement events (OEEs) were frequently observed in the warm season (OEEs in January accounted for 23.0% of all OEEs). The OEEs at ZOS were related to the photochemical reaction processes under the influences of O3 and solar radiation in the stratosphere and synoptic-scale air mass transport from coastal areas (Princess Elizabeth Land, Wilkes Land, and Queen Mary Land), as evidenced by the recorded wind speed, solar shortwave irradiance, and total column ozone data and the computed potential source contribution function and concentration-weighted trajectory models. The results computed by the tool Stratosphere-to-Troposphere Exchange Flux indicated that stratosphere-to-troposphere transport had no direct impact on OEEs at ZOS. Therefore, synoptic-scale air mass transport is the main cause of OEEs in Antarctica, which is consistent with previous studies. Unlike OEEs at inland Antarctic stations, which are mainly affected by air mass transport from inland plateaus, OEEs at ZOS, a coastal station, are mainly affected by air mass transport from coastal land in East Antarctica.
Mapping public support for climate solutions in France
Authors: Schmid Nicolas , Guinaudeau Benjamin 
Published: February 2022

Abstract
Although successful sustainability transitions depend on public support, we still know little about citizens’ opinions on climate solutions. Existing research often focuses on the problem perception of climate change rather than analyzing attitudes toward specific climate solutions. Studies also largely use closed questions to assess public opinion, posing a problem of ecological validity. Here, we address these gaps by leveraging data from a large-scale public consultation process, the “Grand Débat National”, launched by the French government in response to the Yellow Vest movement in 2019. Combining structural topic modelling, dictionary-based text analysis and qualitative coding, we map the salience and directionality of public opinion on climate solutions. We find that consultation participants perceive climate change as the most salient environmental problem. Transforming the transport and energy sectors is the most supported solution for addressing climate change. For these two sectors, substitution-based climate solutions - as opposed to sufficiency- or efficiency-based measures - are most salient. For instance, participants stress the need to expand public transport infrastructure and switch to renewable energy technologies for power generation. Our findings demonstrate a strong public consensus on most substitution-based climate solutions, except for the role of cars and nuclear energy. While most participants do not link climate solutions to specific policy instruments, we find preferences for authority-based instruments in the context of phasing out polluting technologies, and treasury-based instruments for supporting innovation and phasing in low carbon technologies.
The use of GEDI canopy structure for explaining variation in tree species richness in natural forests
Authors: Marselis Suzanne M , Keil Petr , Chase Jonathan M , Dubayah Ralph 
Published: February 2022

Abstract
Variables describing the abiotic environment (e.g. climate, topography or biogeographic history) have a long tradition of use as predictors of tree species richness patterns. However, these variables may capture variations in richness related to climate, but not those that are related to soil type or forest disturbance. Canopy structure has previously been shown to provide information on the variation of tree species richness, with richness generally increasing with larger canopy heights and denser foliage. The use of canopy structure is increasingly relevant with the availability of such data from the Global Ecosystem Dynamics Investigation (GEDI), a lidar mission onboard the International Space Station. In this analysis we show that GEDI canopy structure explains up to 66% of the variation in tree species richness in natural forests without a history of recent disturbance across the globe. However, this portion overlaps with the variation (up to 80%) explained by environmental and biogeographical variables. Our results show that relationships between tree species richness on one side and climate and canopy structure on the other side are not as straightforward as we initially expected, and should be further investigated across both natural and disturbed forests.
Thermally actuated micro-/nanoscale deformations for optical reconfigurations
Authors: Zhao Yinghao , Ji Chang-Yin , Yang Hengzhang , Wang Yang , Xie Huikai , Li Jiafang 
Published: February 2022

Abstract
The unique three-dimensional (3D) deformations caused by nano-kirigami have enabled a new degree of freedom for reconfigurable optics. Here, we demonstrate a facile nano-kirigami method that can create 3D deformed structures, which can flexibly manipulate optical properties using thermally actuated micro-/nanoscale deformations. By connecting four pairs of thermal actuators to the four sides of a gradient metasurface, large-angle beam steering (∼90°) can be achieved by adjusting the temperature of the actuators. The amplitude of circular dichroism can be adjusted by thermally actuating micro-/nanoscale deformations. The 2D-to-3D transformation of the curved arm structure on metallic substrate results in enhanced structural absorption, inducing an almost perfect absorption at specific wavelengths. Curved asymmetric structures can also be created by thermally actuated micro-/nanoscale deformations, which provides a novel method for cross-polarized light conversion. The proposed design with thermally actuated micro-/nanoscale deformations provides a new methodology to explore versatile reconfigurable functionalities.
ABO Blood Groups Are Not Associated With COVID-19 Disease Incidence and Severity When Correcting for Ethnicity Differences in Blood Type
Authors: Pasko Bryce E , Abbott Diana , Bocsi Gregary T , Draper Nicole L 
Published: February 2022

Abstract

Objectives
To determine if blood type is a risk factor for coronavirus disease 2019 (COVID-19) disease incidence and severity after correcting for ethnicity differences between novel infections and known ABO blood type frequency differences.

Methods
We performed a retrospective analysis on all severe acute respiratory system coronavirus 2 (SARS-CoV-2) infections and disease severity across two major testing sites in Colorado. We evaluated all individuals with a SARS-CoV-2 nucleic acid test (NAT) and a known blood type between March 1, 2020, and June 1, 2020. We then created a prediction algorithm based on the corrected blood types by ethnicity using data from the Colorado Department of Health and established blood types by ethnicity. We applied this prediction algorithm to all patients in our sample.

Results
Of 8,676 patients, 485 (5.6%) had a positive SARS-CoV-2 NAT test and 8,191 (94.4%) had a negative test. All patients had ABO blood types that mirrored the expected blood type distribution within the state of Colorado (P = .15, χ 2 statistic = 5.31). No differences in expected blood groups were present between ethnicity-adjusted SARS-CoV-2–negative and SARS-CoV-2–positive patients (χ 2 = 3.416313, P = .332).

Conclusions
Blood type is not associated with COVID-19 disease incidence or severity after correcting for ethnicity differences in expected blood type frequencies.
cSurvival: a web resource for biomarker interactions in cancer outcomes and in cell lines
Authors: Cheng Xuanjin , Liu Yongxing , Wang Jiahe , Chen Yujie , Robertson Andrew Gordon , Zhang Xuekui , Jones Steven J M , Taubert Stefan 
Published: February 2022

Abstract
Survival analysis is a technique for identifying prognostic biomarkers and genetic vulnerabilities in cancer studies. Large-scale consortium-based projects have profiled &gt;11 000 adult and &gt;4000 pediatric tumor cases with clinical outcomes and multiomics approaches. This provides a resource for investigating molecular-level cancer etiologies using clinical correlations. Although cancers often arise from multiple genetic vulnerabilities and have deregulated gene sets (GSs), existing survival analysis protocols can report only on individual genes. Additionally, there is no systematic method to connect clinical outcomes with experimental (cell line) data. To address these gaps, we developed cSurvival (https://tau.cmmt.ubc.ca/cSurvival). cSurvival provides a user-adjustable analytical pipeline with a curated, integrated database and offers three main advances: (i) joint analysis with two genomic predictors to identify interacting biomarkers, including new algorithms to identify optimal cutoffs for two continuous predictors; (ii) survival analysis not only at the gene, but also the GS level; and (iii) integration of clinical and experimental cell line studies to generate synergistic biological insights. To demonstrate these advances, we report three case studies. We confirmed findings of autophagy-dependent survival in colorectal cancers and of synergistic negative effects between high expression of SLC7A11 and SLC2A1 on outcomes in several cancers. We further used cSurvival to identify high expression of the Nrf2-antioxidant response element pathway as a main indicator for lung cancer prognosis and for cellular resistance to oxidative stress-inducing drugs. Altogether, these analyses demonstrate cSurvival’s ability to support biomarker prognosis and interaction analysis via gene- and GS-level approaches and to integrate clinical and experimental biomedical studies.
Do deep learning models make a difference in the identification of antimicrobial peptides?
Authors: García-Jacas César R , Pinacho-Castellanos Sergio A , García-González Luis A , Brizuela Carlos A 
Published: February 2022

AbstractIn the last few decades, antimicrobial peptides (AMPs) have been explored as an alternative to classical antibiotics, which in turn motivated the development of machine learning models to predict antimicrobial activities in peptides. The first generation of these predictors was filled with what is now known as shallow learning-based models. These models require the computation and selection of molecular descriptors to characterize each peptide sequence and train the models. The second generation, known as deep learning-based models, which no longer requires the explicit computation and selection of those descriptors, started to be used in the prediction task of AMPs just four years ago. The superior performance claimed by deep models regarding shallow models has created a prevalent inertia to using deep learning to identify AMPs. However, methodological flaws and/or modeling biases in the building of deep models do not support such superiority. Here, we analyze the main pitfalls that led to establish biased conclusions on the leading performance of deep models. Also, we analyze whether deep models truly contribute to achieve better predictions than shallow models by performing fair studies on different state-of-the-art benchmarking datasets. The experiments reveal that deep models do not outperform shallow models in the classification of AMPs, and that both types of models codify similar chemical information since their predictions are highly similar. Thus, according to the currently available datasets, we conclude that the use of deep learning could not be the most suitable approach to develop models to identify AMPs, mainly because shallow models achieve comparable-to-superior performances and are simpler (Ockham’s razor principle). Even so, we suggest the use of deep learning only when its capabilities lead to obtaining significantly better performance gains worth the additional computational cost.
Predicting the function of rice proteins through Multi-instance Multi-label Learning based on multiple features fusion
Authors: Liu Jing , Tang Xinghua , Cui Shuanglong , Guan Xiao 
Published: February 2022

Abstract
There are a large number of unannotated proteins with unknown functions in rice, which are difficult to be verified by biological experiments. Therefore, computational method is one of the mainstream methods for rice proteins function prediction. Two representative rice proteins, indica protein and japonica protein, are selected as the experimental dataset. In this paper, two feature extraction methods (the residue couple model method and the pseudo amino acid composition method) and the Principal Component Analysis method are combined to design protein descriptive features. Moreover, based on the state-of-the-art MIML algorithm EnMIMLNN, a novel MIML learning framework MK-EnMIMLNN is proposed. And the MK-EnMIMLNN algorithm is designed by learning multiple kernel fusion function neural network. The experimental results show that the hybrid feature extraction method is better than the single feature extraction method. More importantly, the MK-EnMIMLNN algorithm is superior to most classic MIML learning algorithms, which proves the effectiveness of the MK-EnMIMLNN algorithm in rice proteins function prediction.
Bridging the Research Gap between Live Collections in Zoos and Preserved Collections in Natural History Museums
Authors: Poo Sinlan , Whitfield Steven M , Shepack Alexander , Watkins-Colwell Gregory J , Nelson Gil , Goodwin Jillian , Bogisich Allison , Brennan Patricia L R , D'Agostino Jennifer , Koo Michelle S , Mendelson Joseph R , Snyder Rebecca , Wilson Sandra , Aronsen Gary P , Bentley Andrew C , Blackburn David C , Borths Matthew R , Campbell Mariel L , Conde Dalia A , Cook Joseph A , Daza Juan D , Dembiec Daniel P , Dunnum Jonathan L , Early Catherine M , Ferguson Adam W , Greene Amanda , Guralnick Robert , Janney Courtney , Johnson Debbie , Knightly Felicia , Poulin Stephane , Rocha Luiz , Soltis Pamela S , Thiers Barbara , Chakrabarty Prosanta 
Published: February 2022

Abstract
Zoos and natural history museums are both collections-based institutions with important missions in biodiversity research and education. Animals in zoos are a repository and living record of the world's biodiversity, whereas natural history museums are a permanent historical record of snapshots of biodiversity in time. Surprisingly, despite significant overlap in institutional missions, formal partnerships between these institution types are infrequent. Life history information, pedigrees, and medical records maintained at zoos should be seen as complementary to historical records of morphology, genetics, and distribution kept at museums. Through examining both institution types, we synthesize the benefits and challenges of cross-institutional exchanges and propose actions to increase the dialog between zoos and museums. With a growing recognition of the importance of collections to the advancement of scientific research and discovery, a transformational impact could be made with long-term investments in connecting the institutions that are caretakers of living and preserved animals.
Social Workers as Leaders Rather than as Agents of Change
Authors: Allassad Alhuzail Nuzha 
Published: February 2022

AbstractArab citizens of Israel constitute 21 per cent of the country’s population. In April and May 2021 violent conflict erupted between Arab and Jewish Israeli citizens, more severe than ever before. It was manifested on both sides in physical brutality, destruction of property and torching of homes and places of worship. The political leadership on both sides was divided over how to respond. Some tried to restore calm; others tried to use the conflict for political gain and to divide the population. Against this background, a qualitative study, using semi-structured interviews, was conducted among forty Jewish and Arab social workers with the aim of understanding how they viewed their role in the conflict and how they were dealing with it. A thematic analysis revealed three main themes: ‘What’s needed is a social worker who is a leader’; ‘The writing was on the wall’ and ‘The situation could be changed, but…’. The social workers saw importance in their profession’s values of social justice and acceptance of the other but expressed difficulty in acting in a sphere that is defined as political. Recommendations are made for equipping social workers with the necessary tools for acting effectively in times of conflict.
A connectome-based neuromarker of nonverbal number acuity and arithmetic skills
Authors: Zhang Dai , Zhou Liqin , Yang Anmin , Li Shanshan , Chang Chunqi , Liu Jia , Zhou Ke 
Published: February 2022

Abstract
The approximate number system (ANS) is vital for survival and reproduction in animals and is crucial for constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, a neuromarker to characterize an individual’s ANS acuity is lacking, especially one based on whole-brain functional connectivity (FC). Here, based on the resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from a large sample, we identified a distributed brain network (i.e. a numerosity network) using a connectome-based predictive modeling (CPM) analysis. The summed FC strength within the numerosity network reliably predicted individual differences in ANS acuity regarding behavior, as measured using a nonsymbolic number-comparison task. Furthermore, in an independent dataset of the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network also specifically predicted individual differences in arithmetic skills, but not domain-general cognitive abilities. Therefore, our findings revealed that the identified numerosity network could serve as an applicable neuroimaging-based biomarker of nonverbal number acuity and arithmetic skills.
Investment in farming under uncertainty and decoupled support: a real options approach
Authors: Di Corato Luca , Zormpas Dimitrios 
Published: February 2022

AbstractWe develop a real options model to assess the impact of decoupled payments on agricultural investments. The context that we are addressing is the one set by the Common Agricultural Policy where farmers are eligible for decoupled payments as long as their land is properly maintained. We show that decoupled payments are non-neutral with respect to choices concerning timing and capacity. We find that they (i) induce earlier investment with lower productive capacity; (ii) increase the value of the investment option associated with land and (iii) reduce the volatility of farm income. A numerical exercise complements our theoretical analysis.
Rebel without a Cause: The Effects of Social Origins and Disposable Income on Rule Violations
Authors: Armandola Niccolò Giorgio , Ehlert Alexander , Rauhut Heiko 
Published: February 2022

AbstractAre upper-class individuals more inclined to violate rules? Using behavioural data, recent studies have challenged the traditional assumption of upper social class members being less rule violating, while other studies find no or opposite effects. We bring together behavioural decision-making games with traditional survey measures in a unique setup to re-evaluate the proposed relation between social class and rule violations, distinguishing between the economic and the psychological components of social class. Drawing from a cohort of 750 Swiss adults, we investigate how the conditions they were born in (social origins) and the current financial resources (disposable income) affect self-reported and behaviourally measured rule violations in the lab. Interestingly, our findings show that disposable income impacts the behaviour of individuals conditional upon their social origins. For people with upper social origins an increase in disposable income leads to more rule violations than for people with lower social origins. Additional analyses show that a similar pattern emerges when analysing the different perceptions of morality that the two groups have. We conclude that with increasing disposable income, people with upper social origins become more morally flexible, as they are more tolerant of rule violations and violate the rules more often than individuals with lower social origins.
The WHO Prison Health Framework: a framework for assessment of prison health system performance
Authors: Alves da Costa Filipa , Verschuuren Marieke , Andersen Yanina , Stürup-Toft Sunita , Lopez-Acuña Daniel , Ferreira-Borges Carina 
Published: February 2022

Abstract

Background
The Health in Prisons European Database (HIPED) aims to periodically collect data on prison health systems, services and health outcomes to inform equivalence of care for people living in prison. Recognized as the United Nations hub for health data in prisons, HIPED lacked an established framework to define its domains and indicators to measure progress. Therefore, the objectives of developing this framework were to inform surveillance systems at prison, local, regional, national and international level and to use it to guide improvement of prison health systems and cross-country comparison.

Methods
The framework was conceptualized through identification of policy priorities and existing frameworks, notably the WHO Health System Framework. A consultation with a range of WHO stakeholders was conducted evaluating the components of existing frameworks and their relevance to the prison health context, as well as identifying areas needing further emphasis. The final stage identified the structure of the framework.

Results
The framework consists of three main building blocks. The first captures the system-level aspects of prison health care (or inputs) whilst the second captures delivery aspects of prison health care (or outputs). These building blocks are in turn modified by two influencing factors. Ultimately, all these elements impact on the third building block, health outcomes. In addition, two cross-cutting principles associated with all these building blocks and influencing factors are included.

Conclusions
A new framework for assessing prison health system performance is now available, crucial to support informed decision-making for policy design and implementation for prisons and other places of detention.
Enhanced CoQ10 production by genome modification of Rhodobacter sphaeroides via Tn7 transposition
Authors: Zhu Yongqiang , Pan Mengyao , Wang Chenfei , Ye Lidan , Xia Chunmiao , Yu Hongwei 
Published: February 2022

ABSTRACT
As a native CoQ10 producer, Rhodobacter sphaeroides has been extensively engineered to enhance CoQ10 production. However, the genetic manipulations using plasmids suffer from risk of plasmid loss during propagation process, biomass impairment due to cellular burden and bio-safety concerns. In this paper, genomic manipulations via Tn7 transposition was conducted to boost the CoQ10 biosynthesis in R. sphaeroides. The titer production and content of CoQ10 were improved by 18.44% and 18.87%, respectively compared to the wild type, when an additional copy of dxs and dxr were integrated into the genome. Further overexpression of idi and ispD by genomic integration created strain RSPCDDII with CoQ10 production and content of 81.23 mg/L and 5.93 mg/g, which were 54.28 and 55.97% higher than those of the wild type. The gene segments were successfully inserted into the attTn7 site of the R. sphaeroides genome. Meanwhile, the biomass was not affected. Compared to overexpression of genes on plasmids, this strategy could enhance protein expression to a proper level without affecting cell growth, and in a more stable manner.