bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lifetime over 10000 hours for organic solar cells with Ir/IrOx electron-transporting layer
Authors: Li Yanxun , Huang Bo , Zhang Xuning , Ding Jianwei , Zhang Yingyu , Xiao Linge , Wang Boxin , Cheng Qian , Huang Gaosheng , Zhang Hong , Yang Yingguo , Qi Xiaoying , Zheng Qiang , Zhang Yuan , Qiu Xiaohui , Liang Minghui , Zhou Huiqiong 
Published: March 2023

AbstractThe stability of organic solar cells is a key issue to promote practical applications. Herein, we demonstrate that the device performance of organic solar cells is enhanced by an Ir/IrOx electron-transporting layer, benefiting from its suitable work function and heterogeneous distribution of surface energy in nanoscale. Notably, the champion Ir/IrOx-based devices exhibit superior stabilities under shelf storing (T80 = 56696 h), thermal aging (T70 = 13920 h), and maximum power point tracking (T80 = 1058 h), compared to the ZnO-based devices. It can be attributed to the stable morphology of photoactive layer resulting from the optimized molecular distribution of the donor and acceptor and the absence of photocatalysis in the Ir/IrOx-based devices, which helps to maintain the improved charge extraction and inhibited charge recombination in the aged devices. This work provides a reliable and efficient electron-transporting material toward stable organic solar cells.
China’s electric vehicle and climate ambitions jeopardized by surging critical material prices
Authors: Wang Hetong , Feng Kuishuang , Wang Peng , Yang Yuyao , Sun Laixiang , Yang Fan , Chen Wei-Qiang , Zhang Yiyi , Li Jiashuo 
Published: March 2023

AbstractThe adoption of electric vehicles (EVs) on a large scale is crucial for meeting the desired climate commitments, where affordability plays a vital role. However, the expected surge in prices of lithium, cobalt, nickel, and manganese, four critical materials in EV batteries, could hinder EV uptake. To explore these impacts in the context of China, the world’s largest EV market, we expand and enrich an integrated assessment model. We find that under a high material cost surge scenario, EVs would account for 35% (2030) and 51% (2060) of the total number of vehicles in China, significantly lower than 49% (2030) and 67% (2060) share in the base-line, leading to a 28% increase in cumulative carbon emissions (2020-2060) from road transportation. While material recycling and technical battery innovation are effective long-term countermeasures, securing the supply chains of critical materials through international cooperation is highly recommended, given geopolitical and environmental fragilities.
Micro-electrochemical insights into pit initiation site on aged UNS S32750 super duplex stainless steel
Authors: Amatsuka Shuichiro , Nishimoto Masashi , Muto Izumi , Kawamori Makoto , Takara Yuya , Sugawara Yu 
Published: March 2023

AbstractAn aging treatment of UNS S32750 super duplex stainless steel at 1173 K for 1.0 ks produced σ and secondary austenite (γ2) phases in the α and γ phase boundary regions. Small amount of Mn-Cr oxide and MnS complex inclusions were present in the steel. No pitting was observed during the potentiodynamic polarization of a small area (200 × 200 µm) without inclusions in 1 M MgCl2 at 348 K. Because the electrode area included α, γ, σ, and γ2 phases, these phases and their boundaries alone could not act as initiation sites for pitting. The electrode area size was gradually reduced from 3 × 3 mm to 1 × 1 mm, and pitting corrosion was observed to occur at the Mn-Cr oxide and MnS complex inclusions in a region that appeared to be the γ2 phase near the σ phase.
The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data
Authors: Leonard Hampton L. , Murtadha Ruqaya , Martinez-Carrasco Alejandro , Jama Alina , Müller-Nedebock Amica Corda , Gil-Martinez Ana-Luisa , Illarionova Anastasia , Moore Anni , Bustos Bernabe I. , Jadhav Bharati , Huxford Brook , Storm Catherine , Towns Clodagh , Vitale Dan , Chetty Devina , Yu Eric , Grenn Francis P. , Salazar Gabriela , Rateau Geoffrey , Iwaki Hirotaka , Elsayed Inas , Foote Isabelle Francesca , Jansen van Rensburg Zuné , Kim Jonggeol Jeff , Yuan Jie , Lake Julie , Brolin Kajsa , Senkevich Konstantin , Wu Lesley , Tan Manuela M. X. , Periñán María Teresa , Makarious Mary B. , Ta Michael , Pillay Nikita Simone , Betancor Oswaldo Lorenzo , Reyes-Pérez Paula R. , Alvarez Jerez Pilar , Saini Prabhjyot , al-Ouran Rami , Sivakumar Ramiya , Real Raquel , Reynolds Regina H. , Hu Ruifneg , Abrahams Shameemah , Rao Shilpa C. , Antar Tarek , Leal Thiago Peixoto , Iankova Vassilena , Scotton William J. , Song Yeajin , Singleton Andrew , Nalls Mike A. , Dey Sumit , Bandres-Ciga Sara , Blauwendraat Cornelis , Noyce Alastair J. ,   on behalf of The International Parkinson Disease Genomics Consortium (IPDGC) and The Global Parkinson’s Genetics Program (GP2)
Published: March 2023

AbstractOpen science and collaboration are necessary to facilitate the advancement of Parkinson’s disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD.
Immunogenicity and protective activity of mRNA vaccine candidates against yellow fever virus in animal models
Authors: Medina-Magües Lex G. , Mühe Janine , Jasny Edith , Medina-Magües Emily S. , Roth Nicole , Lopera-Madrid Jaime , Salas-Quinchucua Cristhian , Knuese Cole , Petsch Benjamin , Osorio Jorge E. 
Published: March 2023

AbstractDespite the success of the widely used attenuated yellow fever (YF) vaccine, its global supply remains a substantial barrier to implementing vaccination campaigns in endemic regions and combating emerging epidemics. In A129 mice and rhesus macaques, we evaluated the immunogenicity and protective activity of messenger RNA (mRNA) vaccine candidates encapsulated in lipid nanoparticles, expressing the pre-membrane and envelope proteins or the non-structural protein 1 of YF virus. Vaccine constructs induced humoral and cell-mediated immune responses in mice, resulting in protection against lethal YF virus infection after passive administration of serum or splenocytes from vaccinated mice. Vaccination of macaques induced sustained high humoral and cellular immune responses for at least 5 months after the second dose. Our data demonstrate that these mRNA vaccine candidates can be considered an attractive addition to the licensed YF vaccine supply based on the induction of functional antibodies correlating with protection and T-cell responses; they could alleviate the limited supply of current YF vaccines, mitigating future YF epidemics.
Predicting indirect effects of rotavirus vaccination programs on rotavirus mortality among children in 112 countries
Authors: Kraay A. N. M. , Chaney D. M. , Deshpande A. , Pitzer V. E. , Lopman B. A. 
Published: March 2023

AbstractRotavirus is a leading cause of diarrhea deaths in children, particularly in low-to-middle income countries (LMICs). Licensed rotavirus vaccines provide strong direct protection, but their indirect effect—the protection due to reduced transmission—is not fully understood. We aimed to quantify the population-level effects of rotavirus vaccination and identify factors that drive indirect protection. We used an SIR-like transmission model to estimate the indirect effects of vaccination on rotavirus deaths in 112 LMICs. We performed a regression analysis to identify predictors of indirect effect magnitude (linear regression) and the occurrence of negative indirect effects (logistic regression). Indirect effects contributed to vaccine impacts in all regions, with effect sizes 8-years post-vaccine introduction ranging from 16.9% in the WHO European region to 1.0% in the Western Pacific region. Indirect effect estimates were higher in countries with higher under-5 mortality, higher vaccine coverage, and lower birth rates. Of the 112 countries analyzed, 18 (16%) had at least 1 year with a predicted negative indirect effect. Negative indirect effects were more common in countries with higher birth rate, lower under-5 mortality and lower vaccine coverage. Rotavirus vaccination may have a larger impact than would be expected from direct effects alone, but the impact of these indirect effects is expected to vary by country.
Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding
Authors: Islam Md Kamrul , Amaya-Ramirez Diego , Maigret Bernard , Devignes Marie-Dominique , Aridhi Sabeur , Smaïl-Tabbone Malika 
Published: March 2023

AbstractThe search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns “ensemble embeddings” of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.
Development of a nomogram for predicting 90-day mortality in patients with sepsis-associated liver injury
Authors: Cui Liangwen , Bao Junjie , Yu Chao , Zhang Cheng , Huang Rui , Liu Lian , Shao Min 
Published: March 2023

AbstractThe high mortality rate in sepsis patients is related to sepsis-associated liver injury (SALI). We sought to develop an accurate forecasting nomogram to estimate individual 90-day mortality in SALI patients. Data from 34,329 patients were extracted from the public Medical Information Mart for Intensive Care (MIMIC-IV) database. SALI was defined by total bilirubin (TBIL) > 2 mg/dL and the occurrence of an international normalized ratio (INR) > 1.5 in the presence of sepsis. Logistic regression analysis was performed to establish a prediction model called the nomogram based on the training set (n = 727), which was subsequently subjected to internal validation. Multivariate logistic regression analysis showed that SALI was an independent risk factor for mortality in patients with sepsis. The Kaplan‒Meier curves for 90-day survival were different between the SALI and non-SALI groups after propensity score matching (PSM) (log rank: P < 0.001 versus P = 0.038), regardless of PSM balance. The nomogram demonstrated better discrimination than the sequential organ failure assessment (SOFA) score, logistic organ dysfunction system (LODS) score, simplified acute physiology II (SAPS II) score, and Albumin–Bilirubin (ALBI) score in the training and validation sets, with areas under the receiver operating characteristic curve (AUROC) of 0.778 (95% CI 0.730–0.799, P < 0.001) and 0.804 (95% CI 0.713–0.820, P < 0.001), respectively. The calibration plot showed that the nomogram was sufficiently successful to predict the probability of 90-day mortality in both groups. The DCA of the nomogram demonstrated a higher net benefit regarding clinical usefulness than SOFA, LODS, SAPSII, and ALBI scores in the two groups. The nomogram performs exceptionally well in predicting the 90-day mortality rate in SALI patients, which can be used to assess the prognosis of patients with SALI and may assist in guiding clinical practice to enhance patient outcomes.
Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts
Authors: Stoewer Paul , Schilling Achim , Maier Andreas , Krauss Patrick 
Published: March 2023

AbstractHow do we make sense of the input from our sensory organs, and put the perceived information into context of our past experiences? The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and navigation in cognitive maps of arbitrary mental spaces via place and grid cells can serve as a representation of memories and experiences and their relations to each other. The multi-scale successor representation is proposed to be the mathematical principle underlying place and grid cell computations. Here, we present a neural network, which learns a cognitive map of a semantic space based on 32 different animal species encoded as feature vectors. The neural network successfully learns the similarities between different animal species, and constructs a cognitive map of ‘animal space’ based on the principle of successor representations with an accuracy of around 30% which is near to the theoretical maximum regarding the fact that all animal species have more than one possible successor, i.e. nearest neighbor in feature space. Furthermore, a hierarchical structure, i.e. different scales of cognitive maps, can be modeled based on multi-scale successor representations. We find that, in fine-grained cognitive maps, the animal vectors are evenly distributed in feature space. In contrast, in coarse-grained maps, animal vectors are highly clustered according to their biological class, i.e. amphibians, mammals and insects. This could be a putative mechanism enabling the emergence of new, abstract semantic concepts. Finally, even completely new or incomplete input can be represented by interpolation of the representations from the cognitive map with remarkable high accuracy of up to 95%. We conclude that the successor representation can serve as a weighted pointer to past memories and experiences, and may therefore be a crucial building block to include prior knowledge, and to derive context knowledge from novel input. Thus, our model provides a new tool to complement contemporary deep learning approaches on the road towards artificial general intelligence.
Hard optimization problems have soft edges
Authors: Marino Raffaele , Kirkpatrick Scott 
Published: March 2023

AbstractFinding a Maximum Clique is a classic property test from graph theory; find any one of the largest complete subgraphs in an Erdös-Rényi G(N, p) random graph. We use Maximum Clique to explore the structure of the problem as a function of N, the graph size, and K, the clique size sought. It displays a complex phase boundary, a staircase of steps at each of which $$2 \log _2N$$

2

log
2

N

and $$K_{\text {max}}$$

K
max

, the maximum size of a clique that can be found, increases by 1. Each of its boundaries has a finite width, and these widths allow local algorithms to find cliques beyond the limits defined by the study of infinite systems. We explore the performance of a number of extensions of traditional fast local algorithms, and find that much of the “hard” space remains accessible at finite N. The “hidden clique” problem embeds a clique somewhat larger than those which occur naturally in a G(N, p) random graph. Since such a clique is unique, we find that local searches which stop early, once evidence for the hidden clique is found, may outperform the best message passing or spectral algorithms.
Organic carbon accumulation and aggregate formation in soils under organic and inorganic fertilizer management practices in a rice–wheat cropping system
Authors: Zhao Zhanhui , Mao Yanli , Gao Songfeng , Lu Chunyang , Pan Chuanjiao , Li Xiaoyu 
Published: March 2023

AbstractSoil organic carbon (C) and aggregates are the important components of soil fertility and the foundation of sustainable agriculture. The storage and protection of SOC in aggregates is widely regarded as the material basis of soil organic C accumulation. However, current understanding of soil aggregate and its associated organic C is insufficient to elucidate the regulation mechanism of soil organic C. A nine-year field experiment including chemical fertilizer (FR) and organic manure (OM) treatments was set up in the eastern plain of Funiu Mountain, central China. Using chemical analysis, physical sieving as well as nuclear magnetic resonance (NMR) methods, we mainly probed into the response of soil organic C concentration and composition, and C functional groups, water-stable aggregates to different treatments. Furthermore, scanning electronic microscopy (SEM) and partial least square structural equation modelling (PLS-SEM) was conducted to characterise the different size aggregates and to analyse the mechanism of soil organic C accumulation and stabilisation at aggregate scales. After nine years of farming, OM treatment substantially increased soil organic C content (by 3.77 g kg−1) and significantly enhanced the formation of macro-aggregates (> 250 μm), while FR had no significant influence on soil organic C. At the aggregate scale, the amounts of soil organic C, C physical fractions (particulate and mineral-associated organic C), total nitrogen and microbial biomass carbon associated in macro-aggregates (> 250 μm) were obviously higher than that in micro-aggregates and silt + clay fraction, and OM treatment greatly increased the accumulation of soil organic C and its components in macro-aggregates. Moreover, microbial biomass carbon (MBC) amounts in aggregates were remarkably increased (27–116%) by the application of OM. And MBC had a positively effect on the physical fractions of SOC but not on the C chemical structure within aggregates. The present study indicated that soil organic C accumulation mainly rely on macro-aggregates (> 250 μm). Intra–particulate organic carbon (POC) and mineral-associated organic carbon (MOC) within macro-aggregates played an important role in soil organic C accumulation. Meanwhile, soil microbes were a driving force for the accumulation of soil organic C physical fractions (POC and MOC). We concluded that OM treatment accelerated the synergistic process between organic C sequestration and soil aggregation, and showed great potential to increase soil organic C accumulation.
Comparison of various machine learning algorithms used for compressive strength prediction of steel fiber-reinforced concrete
Authors: Pakzad Seyed Soroush , Roshan Naeim , Ghalehnovi Mansour 
Published: March 2023

AbstractAdding hooked industrial steel fibers (ISF) to concrete boosts its tensile and flexural strength. However, the understanding of ISF’s influence on the compressive strength (CS) behavior of concrete is still questioned by the scientific society. The presented paper aims to use machine learning (ML) and deep learning (DL) algorithms to predict the CS of steel fiber reinforced concrete (SFRC) incorporating hooked ISF based on the data collected from the open literature. Accordingly, 176 sets of data are collected from different journals and conference papers. Based upon the initial sensitivity analysis, the most influential parameters like water-to-cement (W/C) ratio and content of fine aggregates (FA) tend to decrease the CS of SFRC. Meanwhile, the CS of SFRC could be enhanced by increasing the amount of superplasticizer (SP), fly ash, and cement (C). The least contributing factors include the maximum size of aggregates (Dmax) and the length-to-diameter ratio of hooked ISFs (L/DISF). Several statistical parameters are also used as metrics to evaluate the performance of implemented models, such as coefficient of determination (R2), mean absolute error (MAE), and mean of squared error (MSE). Among different ML algorithms, convolutional neural network (CNN) with R2 = 0.928, RMSE = 5.043, and MAE = 3.833 shows higher accuracy. On the other hand, K-nearest neighbor (KNN) algorithm with R2 = 0.881, RMSE = 6.477, and MAE = 4.648 results in the weakest performance.
Tofacitinib fails to prevent T cell transfer colitis in mice but ameliorates disease activity
Authors: Subramanyam Sudheendra Hebbar , Hriczko Judit Turyne , Pappas Angeliki , Schippers Angela , Wagner Nobert , Ohl Kim , Tenbrock Klaus 
Published: March 2023

AbstractTofactinib is a JAK inhibitor approved for ulcerative colitis in humans. Despite of its’ proven effectiveness in humans, mechanistic data are scarce on the effectiveness of Tofactinib in experimental colitis in mice. We induced experimental colitis by transfer of CD4+CD25− isolated T cells into RAG2−/− (T and B cell deficient) mice and treated these mice with tofacitinib for 5–6 weeks either with a dosage of 10 or 40 mg/kg body weight immediately after CD4+ transfer or started treatment after first symptoms of disease for several weeks. While treatment with tofacitinib immediately after transfer resulted in an enhanced expansion of CD4+ T cells and did not prevent occurrence of colitis, treatment after start of symptoms of colitis ameliorated disease activity on a clinical basis and in histological analyses. Tofacitinib is effective in the treatment of murine experimental T cell transfer colitis, however does not prevent occurrence of disease.
Direct competition and potential displacement involving managed Trogoderma stored product pests
Authors: Domingue Michael J. , Wu Yunke , Vieira Kendra A. , McGraw Alana R. , Furtado Mandy , Athanassiou Christos G. , Morrison William R. , Myers Scott W. 
Published: March 2023

AbstractThe establishment of an exotic pest may require displacing local species with a similar niche. The potential ofTrogoderma granariumto displaceTrogoderma inclusumwas explored in a stored product setting. We performed direct competition experiments varying commodity and temperature over different durations. At nine weeksT. inclusumoutproducedT. granariumon all commodities at any temperature. However the proportion ofT. granariumversusT. inclusumwas greater at 32 °C compared to 25 °C. The nine-week production ofT. granariumwas best on wheat, while rice was optimal forT. inclusum. After 25 weeks, when adults were used at the start of competition,T. inclusummaintained an advantage in the direct competition. If larvae were used to initiate the competition for 25 weeks, the two species coexisted well at 25 °C, butT. granariumnearly excludedT. inclusumat 32 °C. ThusT. inclusumperforms better in competition over shorter intervals when resources are plentiful, butT. granariumcan be more successful over longer time periods, particularly when late instar larvae are involved. The finding suggests a real threat of introductions ofT. granariumlarvae to establish populations within grain storage infrastructure whereT. inclusumis common.