bluuebunny/crossref_metadata_2025_split huggingface dataset:
Priority age targets for COVID-19 vaccination in Ethiopia under limited vaccine supply
Authors: Galli Margherita , Zardini Agnese , Gamshie Worku Nigussa , Santini Stefano , Tsegaye Ademe , Trentini Filippo , Marziano Valentina , Guzzetta Giorgio , Manica Mattia , d’Andrea Valeria , Putoto Giovanni , Manenti Fabio , Ajelli Marco , Poletti Piero , Merler Stefano 
Published: April 2023

AbstractThe worldwide inequitable access to vaccination claims for a re-assessment of policies that could minimize the COVID-19 burden in low-income countries. Nine months after the launch of the national vaccination program in March 2021, only 3.4% of the Ethiopian population received two doses of COVID-19 vaccine. We used a SARS-CoV-2 transmission model to estimate the level of immunity accrued before the launch of vaccination in the Southwest Shewa Zone (SWSZ) and to evaluate the impact of alternative age priority vaccination targets in a context of limited vaccine supply. The model was informed with available epidemiological evidence and detailed contact data collected across different geographical settings (urban, rural, or remote). We found that, during the first year of the pandemic, the mean proportion of critical cases occurred in SWSZ attributable to infectors under 30 years of age would range between 24.9 and 48.0%, depending on the geographical setting. During the Delta wave, the contribution of this age group in causing critical cases was estimated to increase on average to 66.7–70.6%. Our findings suggest that, when considering the vaccine product available at the time (ChAdOx1 nCoV-19; 65% efficacy against infection after 2 doses), prioritizing the elderly for vaccination remained the best strategy to minimize the disease burden caused by Delta, irrespectively of the number of available doses. Vaccination of all individuals aged ≥ 50 years would have averted 40 (95%PI: 18–60), 90 (95%PI: 61–111), and 62 (95%PI: 21–108) critical cases per 100,000 residents in urban, rural, and remote areas, respectively. Vaccination of all individuals aged ≥ 30 years would have averted an average of 86–152 critical cases per 100,000 individuals, depending on the setting considered. Despite infections among children and young adults likely caused 70% of critical cases during the Delta wave in SWSZ, most vulnerable ages should remain a key priority target for vaccination against COVID-19.
Improving detention ponds for effective stormwater management and water quality enhancement under future climate change: a simulation study using the PCSWMM model
Authors: Abduljaleel Yasir , Salem Ali , ul Haq Faraz , Awad Ahmed , Amiri Mustapha 
Published: April 2023

AbstractUrban surfaces are often covered by impermeable materials such as concrete and asphalt which intensify urban runoff and pollutant concentration during storm events, and lead to the deterioration of the quality of surrounding water bodies. Detention ponds are used in urban stormwater management, providing two-fold benefits: flood risk reduction and pollution load minimization. This paper investigates the performance of nine proposed detention ponds (across the city of Renton, Washington, USA) under different climate change scenarios. First, a statistical model was developed to estimate the pollutant load for the current and future periods and to understand the effects of increased rainfall on stormwater runoff and pollutant loads. The Personal Computer Storm Water Management Model (PCSWMM) platform is employed to calibrate an urban drainage model for quantifying stormwater runoff and corresponding pollutant loads. The calibrated model was used to investigate the performance of the proposed nine (9) detention ponds under future climate scenarios of 100-year design storms, leading to identifying if they are likely to reduce stormwater discharge and pollutant loads. Results indicated significant increases in stormwater pollutants due to increases in rainfall from 2023 to 2050 compared to the historical period 2000–2014. We found that the performance of the proposed detention ponds in reducing stormwater pollutants varied depending on the size and location of the detention ponds. Simulations for the future indicated that the selected detention ponds are likely to reduce the concentrations (loads) of different water quality constituents such as ammonia (NH3), nitrogen dioxide (NO2), nitrate (NO3), total phosphate (TP), and suspended solids (SS) ranging from 18 to 86%, 35–70%, 36–65%, 26–91%, and 34–81%, respectively. The study concluded that detention ponds can be used as a reliable solution for reducing stormwater flows and pollutant loads under a warmer future climate and an effective adaptation option to combat climate change related challenges in urban stormwater management.
The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic
Authors: Yang Jialin , Skaro Michael , Chen Jiani , Zhan Duna , Lyu Leke , Gay Skylar , Kandeil Ahmed , Ali Mohamed A. , Kayali Ghazi , Stoianova Kateryna , Ji Pensheng , Alabady Magdy , Bahl Justin , Liu Liang , Arnold Jonathan 
Published: April 2023

AbstractA consensus species tree is reconstructed from 11 gene trees for human, bat, and pangolin beta coronaviruses from samples taken early in the pandemic (prior to April 1, 2020). Using coalescent theory, the shallow (short branches relative to the hosts) consensus species tree provides evidence of recent gene flow events between bat and pangolin beta coronaviruses predating the zoonotic transfer to humans. The consensus species tree was also used to reconstruct the ancestral sequence of human SARS-CoV-2, which was 2 nucleotides different from the Wuhan sequence. The time to most recent common ancestor was estimated to be Dec 8, 2019 with a bat origin. Some human, bat, and pangolin coronavirus lineages found in China are phylogenetically distinct, a rare example of a class II phylogeography pattern (Avise et al. in Ann Rev Eco Syst 18:489–422, 1987). The consensus species tree is a product of evolutionary factors, providing evidence of repeated zoonotic transfers between bat and pangolin as a reservoir for future zoonotic transfers to humans.
Dietary fatty acids differentially affect secretion of pro-inflammatory cytokines in human THP-1 monocytes
Authors: Hung Hao-Chang , Tsai Sheng-Feng , Chou Hsuan-Wen , Tsai Ming-Jun , Hsu Pei-Ling , Kuo Yu-Min 
Published: April 2023

AbstractMonocytes are a major population of circulating immune cells that play a crucial role in producing pro-inflammatory cytokines in the body. The actions of monocytes are known to be influenced by the combinations and concentrations of certain fatty acids (FAs) in blood and dietary fats. However, systemic comparisons of the effects of FAs on cytokine secretion by monocytes have not be performed. In this study, we compared how six saturated FAs (SFAs), two monounsaturated FAs (MUFAs), and seven polyunsaturated FAs (PUFAs) modulate human THP-1 monocyte secretion of TNF, IL-1β, and IL-6 in the absence or presence of lipopolysaccharide. SFAs generally stimulated resting THP-1 cells to secrete pro-inflammatory cytokines, with stearic acid being the most potent species. In contrast, MUFAs and PUFAs inhibited lipopolysaccharide-induced secretion of pro-inflammatory cytokines. Interestingly, the inhibitory potentials of MUFAs and PUFAs followed U-shaped (TNF and IL-1β) or inverted U-shaped (IL-6) dose–response curves. Among the MUFAs and PUFAs that were analyzed, docosahexaenoic acid (C22:6 n-3) exhibited the largest number of double bonds and was found to be the most potent anti-inflammatory compound. Together, our findings reveal that the chemical compositions and concentrations of dietary FAs are key factors in the intricate regulation of monocyte-mediated inflammation.
Supercritical CO2-assisted solid-phase etching preparation of MXenes for high-efficiency alkaline hydrogen evolution reaction
Authors: Feng Huajian , Tian Qingyong , Huang Junhao , Cui Xinwei , Jiang Jingyun , Tian Yapeng , Ye Li , Xu Qun 
Published: April 2023

A novel solid-phase etching approach to synthesize 2D titanium carbide (MXenes) using FeF3·3H2O with the assistance of supercritical CO2 has been successfully achieved, and moreover, the reaction mechanism behind it is revealed.
Depth‐aware lightweight network for RGB‐D salient object detection
Authors: Ling Liuyi , Wang Yiwen , Wang Chengjun , Xu Shanyong , Huang Yourui 
Published: April 2023

AbstractRGB‐D salient object detection (SOD) is to detect salient objects from one RGB image and its depth data. Although related networks have achieved appreciable performance, they are not ideal for mobile devices since they are cumbersome and time‐consuming. The existing lightweight networks for RGB‐D SOD use depth information as additional input, and integrate depth information with colour image, which achieve impressive performance. However, the quality of depth information is uneven and the acquisition cost is high. To solve this issue, depth‐aware strategy is first combined to propose a lightweight SOD model, Depth‐Aware Lightweight network (DAL), using only RGB maps as input, which is applied to mobile devices. The DAL's framework is composed of multi‐level feature extraction branch, specially designed channel fusion module (CF) to perceive the depth information, and multi‐modal fusion module (MMF) to fuse the information of multi‐modal feature maps. The proposed DAL is evaluated on five datasets and it is compared with 14 models. Experimental results demonstrate that the proposed DAL outperforms the state‐of‐the‐art lightweight networks. The proposed DAL has only 5.6 M parameters and inference speed of 39 ms. Compared with the best‐performing lightweight method, the proposed DAL has fewer parameters, faster inference speed, and higher accuracy.
Improved SwinTrack single target tracking algorithm based on spatio‐temporal feature fusion
Authors: Zhao Min , Yue Qiang , Sun Dihua , Zhong Yuan 
Published: April 2023

AbstractSingle target tracking based on computer vision helps to collect, analyse and exploit target information. The SwinTrack algorithm has received widespread attention as one of the twin network algorithms with the best trade‐off between tracking accuracy and speed, but it also suffers from the insufficient fusion of deep and shallow features leading to loss of shallow information and insufficient use of temporal information leading to inconsistency between target and template. Semantic information and detailed information are combined and multiple convolutional forms are introduced to propose a multi‐level feature fusion strategy to effectively fuse features in space. Besides, based on the idea of feedback, a dynamic template branching approach is also designed to fuse temporal features and enhance the representation of target features. The effectiveness of this method was verified on the OTB100 and GOT10K datasets.
Model for the cooperative obstacle‐avoidance of the automated vehicle swarm in a connected vehicles environment
Authors: Zhai Donghai , Yang Da , Chen Jing , Luo Ziqi , Yu Mengsi , Zhou Zihan 
Published: April 2023

AbstractThe obstacle‐avoidance problem of automated vehicles is a hot topic in the community of autonomous driving. The majority of the existing studies focused on the obstacle‐avoidance of a single automated vehicle. The connected vehicles technology provides the possibility of controlling a vehicle swarm to avoid the obstacle cooperatively. Through cooperation, the vehicle swarm not only can avoid an obstacle safely but also can minimize traffic delays. Therefore, this paper proposes a cooperative obstacle‐avoidance model for the automated vehicle swarm driving on the freeway based on the A2C reinforcement learning. The proposed model considers the efficiencies of both the individual and swarm in the learning, and a cooperative lane‐changing execution model is proposed to ensure that the optimal decision made by the A2C algorithm can be performed by the vehicles. Furthermore, simulations are conducted to verify the proposed model. The results indicate that the proposed model can significantly improve the overall traffic efficiency compared with the existing models. In a congested state, when the proposed model is applied to control vehicles, an optimal control range can be found (i.e. 700 m here), and within this optimal range, the traffic efficiency increases with the increment of the number of the vehicles controlled by the proposed model.
Optimal planning of a micro‐grid containing tidal barrage equipped to the hydro‐pumps
Authors: Negahdari Mohammad Reza , Ghaedi Amir , Nafar Mehdi , Simab Mohsen 
Published: April 2023

AbstractDue to the advantages of micro‐grids including power losses and voltage drops reduction, reliability improvement and reduction in transmission network cost, numerous clean micro‐grids including renewable resources such as wind, tidal and solar are developed in different countries of world. The investment cost of the renewable energy‐based generation units especially tidal barrages is high, and to generate the cost‐effective electricity from the renewable resources, the optimization process should be performed. In this paper, optimal planning of a micro‐grid containing energy storage device and new mixture of renewable resources including tidal barrage and photovoltaic system is performed. For this purpose, optimal characteristics of barrage type tidal plant including number of turbines, sluices and hydro‐pumps, turbine tip and hub diameters and sluice width are determined to maximum energy of tidal plant is generated. Then, number of photovoltaic systems and batteries are obtained to supply the required load in minimum cost. To optimize the objective functions, different heuristic approaches including particle swarm, genetic and imperial competitive algorithms (ICAs) are applied, in the paper. To study the effectiveness of the proposed approach, optimal planning of a micro‐grid is performed. It is deduced from the numerical results that the particle swarm method has performed best in determining the optimal solution.
Detection of open cluster rotation fields fromGaiaEDR3 proper motions
Authors: Guilherme-Garcia P. , Krone-Martins A. , Moitinho A. 
Published: April 2023

Context.Most stars from in groups which with time disperse, building the field population of their host galaxy. In the Milky Way, open clusters have been continuously forming in the disk up to the present time, providing it with stars spanning a broad range of ages and masses. Observations of the details of cluster dissolution are, however, scarce. One of the main difficulties is obtaining a detailed characterisation of the internal cluster kinematics, which requires very high-quality proper motions. For open clusters, which are typically loose groups with tens to hundreds of members, there is the additional difficulty of inferring kinematic structures from sparse and irregular distributions of stars.Aims.Here, we aim to analyse internal stellar kinematics of open clusters, and identify rotation, expansion, or contraction patterns.Methods.We useGaiaEarly Data Release 3 (EDR3) astrometry and integrated nested Laplace approximations to perform vector-field inference and create spatio-kinematic maps of 1237 open clusters. The sample is composed of clusters for which individual stellar memberships were already known, thus minimising contamination from field stars in the velocity maps. Projection effects were corrected using EDR3 data complemented with radial velocities fromGaiaData Release 2 and other surveys.Results.We report the detection of rotation patterns in eight open clusters. Nine additional clusters display possible rotation signs. We also observe 14 expanding clusters, with 15 other objects showing possible expansion patterns. Contraction is evident in two clusters, with one additional cluster presenting a more uncertain detection. In total, 53 clusters are found to display kinematic structures. Within these, elongated spatial distributions suggesting tidal tails are found in five clusters. These results indicate that the approach developed here can recover kinematic patterns from noisy vector fields, as those from astrometric measurements of open clusters or other stellar or galactic populations, thus offering a powerful probe for exploring the internal kinematics and dynamics of these types of objects.
CCND1-Induced Autophagy Contributes to Lymph Node Metastasis in
Endometrial Cancer
Authors: Su Yi , Zhou Haonan , Ma Zhao , Liu Jing , Li Chen 
Published: April 2023

AbstractEndometrial cancer with lymph node metastasis shows poor prognosis, while the
biomarker to predict the metastasis is lacking. The relative mRNA or protein
expression of cyclin D1 (CCND1) and autophagy-related molecules were detected in
real-time PCR and Western blot. Correlation analysis was applied to identify any
significant patterns, and receiver operating characteristics (ROC) was performed
to assess the prediction value. CCND1 vector was transfected in Ishikawa (ISK)
cells, and the relative expression of autophagy-related molecules was detected
with Western blot. CCND1 was overexpressed in endometrial cancer and correlated
with lymph node metastasis. ROC analysis found that CCND1 had a predictive value
to discriminate tumors from normal tissues (cut off=1.455; sensitivity,
71%; specificity, 84%; area under curve (AUC) 0.82;
p<0.001) and had a predictive value to indicate metastasis (cut
off=1.871; sensitivity, 54.17%; specificity, 75%; AUC
0.674; p=0.003). Increased BECLIN1 (r=0.39, p<0.001) and
ATG5 (r=0.41, p<0.001) expression were positively correlated to
CCND1. On the other hand, the relative protein expression of CCND1, BECLIN1,
ATG5, ATG7, and LC3 I/II were also increased in tumor tissues. CCND1
overexpressed ISK cells showed upregulated BECLIN1, ATG5, ATG7, and LC3
I/II expression. CCND1 promoted autophagy may contribute to lymph node
metastasis in endometrial cancer.
Combined Training Improves Executive Functions Without Changing
Brain-Derived Neurotrophic Factor Levels of Middle-Aged and Older Adults with
Type 2 Diabetes
Authors: Silveira-Rodrigues João Gabriel , Gardênia de Holanda Marinho Nogueira Nathálya , Faria Larissa Oliveira , Pereira Daniele Sirineu , Soares Danusa Dias 
Published: April 2023

Abstract
Background Type 2 diabetes mellitus (T2DM) provokes executive function and
long-term memory decrements, and aerobic plus resistance training (combined
training) may alleviate this T2DM-related cognitive impairment. Brain-derived
neurotrophic factor (BDNF) levels have been found to be related to cognitive
performance.
Aim To analyze the effects of 8-week combined training on executive
functions and circulating BDNF levels of subjects with T2DM and verify the
association between BDNF levels and combined training-induced changes in
executive functions and long-term memory.
Methods Thirty-five (63±8 years old) subjects of both sexes were
allocated to combined training (n=17, thrice weekly for 8
weeks) or the control group (n=18). Executive functions
(evaluated through Trail making test, Stroop color task, and Digit Span),
long-term memory (evaluated through the Taylor Complex Figure Test simplified),
and plasma samples were compared pre- and post-intervention.
Results Combined training improved executive function z-score compared to
control (d=1.31). Otherwise, BDNF levels were not statistically
altered (combined training group: 179±88 pg/mL
vs. 148±108 pg/mL; control group:
163±71 pg/mL vs.
141±84 pg/mL, p>0.05). However,
pre-training BDNF levels explained 50.4% of the longitudinal
improvements in composite executive function z-score (r=0.71,
p<0.01), 33.6% of inhibitory control
(r=0.58; p=0.02), and 31.4% of
cognitive flexibility (r=0.56, p=0.04) in the
combined training group.
Conclusion Combined training improved executive functions independently of
alterations in resting BDNF levels after 8 weeks. Furthermore, pre-training BDNF
levels explained one-half of the variance in combined training-induced
improvements in executive functions.
Synthesis of Dibenzo[f,h]quinolines by Stepwise C–H Arylation of 2-Phenylpyridine and Reductive Cyclodehydrogenation
Authors: Zhong Yu-Wu , He Yan-Qin , Li Zhong-Qiu 
Published: April 2023

AbstractA synthetic approach to dibenzo[f,h]quinolines and their derivatives via stepwise ruthenium-catalyzed C–H arylation and potassium-mediated reductive cyclodehydrogenation from 2-phenylpyridine and aryl bromides, is presented. One dibenzo[f,h]quinoline derivative is used as a bidentate ligand to prepare a cyclometalated ruthenium complex. Two dibenzo[f,h]quinoline compounds and the ruthenium complex were characterized by single-crystal X-ray structural analysis.
Palladium/Azaphos-Catalyzed Asymmetric Suzuki–Miyaura Coupling
Authors: Yang Zhiping , Wang Jun , Jiang Yanxin , Cheng Kwai Wun , Zhang Haoyang 
Published: April 2023

AbstractA palladium-catalyzed asymmetric Suzuki–Miyaura coupling is described with a unique monophosphine ligand, Azaphos. This method provides a new ligand framework that could be used in asymmetric Suzuki–Miyaura coupling reactions to prepare the axially chiral compounds.
Phosphine-Mediated [3+2] Cyclization for the Synthesis of Coumarin-Based CF3-Containing Furanones
Authors: Gan Wenhao , Fu Junfeng , Wang Yongjiang , Han Xiaoyu , Zhou Zhixiang , Cao Sheng , Zhang Zhipeng 
Published: April 2023

AbstractA tertiary phosphine-mediated [3+2] cyclization reaction of ynones with fluorinated coumarin derivatives has been developed to give a series of coumarin-based CF3-containing furanones in moderate to good yields under mild reaction conditions. Preliminary investigation into their antitumor activities is also presented.
Community Engagement in Research and Design of a Transgender Health Information Resource
Authors: Morse Brad , Allen Marvyn , Schilling Lisa M. , Soares Andrey , DeSanto Kristen , Holliman Brooke Dorsey , Lee Rita S. , Kwan Bethany M. 
Published: April 2023

Abstract
Background Access to credible and relevant health care information is an unmet need for the transgender and gender-diverse (TGD) community. This paper describes the community engagement methods and resulting community priorities as part of a codesign process for the development of a Transgender Health Information Resource (TGHIR) application.
Methods A lesbian, gay, bisexual, transgender, and queer advocacy organization and an academic health sciences team partnered to establish a community advisory board (CAB) of TGD individuals, parents of TGD individuals, and clinicians with expertise in transgender health to inform the project. The analytic-deliberative model and group facilitation strategies based on Liberating Structures guided procedures. Affinity grouping was used to synthesize insights from CAB meeting notes regarding roles and perspectives on the design of the TGHIR application. We used the Patient Engagement in Research Scale (PEIRS) to evaluate CAB members' experience with the project.
Results The CAB emphasized the importance of designing the application with and for the TGD community, including prioritizing intersectionality and diversity. CAB engagement processes benefited from setting clear expectations, staying focused on goals, synchronous and asynchronous work, and appreciating CAB member expertise. TGHIR application scope and priorities included a single source to access relevant, credible health information, the ability to use the app discreetly, and preserving privacy (i.e., safe use). An out-of-scope CAB need was the ability to identify both culturally and clinically competent TGD health care providers. PEIRS results showed CAB members experienced moderate to high levels of meaningful engagement (M[standard deviation] = 84.7[12] out of 100).
Conclusion A CAB model was useful for informing TGHIR application priority features. In-person and virtual methods were useful for engagement. The CAB continues to be engaged in application development, dissemination, and evaluation. The TGHIR application may complement, but will not replace, the need for both culturally and clinically competent health care for TGD people.