bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of the ocean on tropical cyclone intensity using a high resolution coupled atmosphere–ocean model: A case study of very severe cyclonic storm Ockhi over the North Indian Ocean
Authors: Mohanty Shyama , Nadimpalli Raghu , Joseph Sudheer , Srivastava Akhil , Das Ananda K. , Mohanty Uma C. , Sil Sourav 
Published: May 2022

AbstractA very severe cyclonic storm (VSCS), Ockhi was conceived in the Bay of Bengal and moved over the Arabian Sea undergoing rapid intensification (RI) in the early stages of its life cycle. Ockhi is simulated using the high‐resolution coupled Hybrid Coordinate Ocean Model and the Hurricane Weather Research Forecast model. The study suggests that sea surface temperature warmer than the seasonal climatological mean with the availability of a large tropical cyclone heat potential (TCHP) has acted as a potential cause for RI when the TC moved over that region. We have conducted experiments with (CP) and without (UCP) ocean coupling. The predicted tracks of UCP and CP experiments agree well with the India Meteorological Department's best track data. However, CP showed a significant improvement in intensity prediction with 61 and 19% for mean sea level pressure and maximum sustained surface wind at 10 m respectively in comparison to UCP. The presence of thermal and haline stratification in the subsurface affects surface cooling. The subsurface turbulent heat flux calculated for the high‐TCHP region under the TC suggests that the upward transport of heat, which increases the enthalpy flux, becomes necessary to bring about RI. The primary circulation, secondary circulation, inflow, thermal structure, moisture distribution and mass flux within the TC environment during the 24‐hr RI period are analyzed to investigate the evolution of TC characteristics for both UCP and CP experiments. The analyses suggest that the UCP experiments show higher values of intensity as compared to CP experiments. Further, a more organized evolution of updrafts is present in the CP simulation, maybe due to the formation of a stable boundary layer. The study shows the significant influence of coupling on surface enthalpy controlling boundary layer characteristics and thus ultimately producing a more organized TC.
Single‐cell profiling of transcriptomic changes during in vitro maturation of human oocytes
Authors: Takeuchi Hiroki , Yamamoto Mari , Fukui Megumi , Inoue Akihiro , Maezawa Tadashi , Nishioka Mikiko , Kondo Eiji , Ikeda Tomoaki , Matsumoto Kazuya , Miyamoto Kei 
Published: May 2022

AbstractPurposeIn vitro maturation (IVM) of human oocytes offers an invaluable opportunity for infertility treatment. However, in vitro matured oocytes often show lower developmental abilities than their in vivo counterparts, and molecular mechanisms underlying successful maturation remain unclear. In this study, we investigated gene expression profiles of in vitro matured oocytes at the single‐cell level to gain mechanistic insight into IVM of human oocytes.MethodsHuman oocytes were retrieved by follicular puncture and in vitro matured. In total, 19 oocytes from 11 patients were collected and subjected to single‐cell RNA‐seq analyses.ResultsGlobal gene expression profiles were similar among oocytes at the same maturation stage, while a small number of oocytes showed distinct transcriptomes from those at the corresponding maturation stage. Differential gene expression analysis identified hundreds of transcripts that dynamically altered their expression during IVM, and we revealed molecular pathways and upstream regulators that may govern oocyte maturation. Furthermore, oocytes that were delayed in their maturation showed distinct transcriptomes. Finally, we identified genes whose transcripts were enriched in each stage of oocyte maturation.ConclusionsOur work uncovers transcriptomic changes during human oocyte IVM and the differential gene expression profile of each oocyte.
Iterative learning based consensus control for distributed parameter type multi‐agent differential inclusion systems
Authors: Zhou Min , Wang JinRong , Shen Dong 
Published: May 2022

AbstractThis article considers the learning consensus problem of distributed parameter type multi‐agent differential inclusion systems including parabolic type and hyperbolic type. By imposing a Lipschitz condition on a set‐valued mapping and utilizing distributed ‐type iterative learning consensus control protocols, an iterative learning process is established. Further, sufficient conditions for the convergence of the consensus error between any two agents in the sense of the certain norm are obtained with the help of Steiner‐type selectors. Finally, numerical simulations verify the validity of the proposed method.
Prediction of greenhouse gas emissions from agricultural fields with and without cover crops
Authors: Mehmandoost Kotlar Ali , Singh Jasdeep , Kumar Sandeep 
Published: May 2022

AbstractThe significant contribution of greenhouse gas (GHG) emissions to global climate change and stratospheric ozone depletion has been calling the attention to assess the effect of agricultural management on them. Although machine learning (ML) methods have been widely used for the quantification of various inherent and dynamic soil properties, the accuracy of these techniques in the prediction of agricultural soil GHG emissions remains unclear. Therefore, this study aims at evaluating the performance of six different ML methods including simple linear regression, Cubist, support vector machines (SVM) with three different kernel functions, and random forest (RF) for the prediction of CO2 and N2O fluxes from plots managed with and without cover cropping. The input parameters include typical meteorological data as well as soil temperature and soil water content. Results show that the daily flux of CO2 is positively correlated with soil temperature and solar radiation and negatively with soil water content, whereas daily N2O flux is positively correlated with soil water content. For plots without cover cropping, Cubist and SVM with polynomial kernel function outperformed in the prediction of the testing dataset with RMSE of 14.18 kg ha–1 d–1 and 11.52 g ha–1 d–1 for daily CO2 and N2O emissions, respectively. Where cover cropping was considered, SVM with radial basis function and Cubist were the best models in the prediction of daily CO2 and N2O fluxes with respective RMSE values of 15.71 kg ha–1 d–1 and 14.12 g ha–1 d–1. Considering the ranking of the models for all scenarios and both GHGs, SVM with nonlinear kernel functions and Cubist method surpassed other ML techniques.
Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation
Authors: Fairley Michael , Rao Isabelle J. , Brandeau Margaret L. , Qian Gary L. , Gonsalves Gregg S. 
Published: May 2022

AbstractOutbreaks of an endemic infectious disease can occur when the disease is introduced into a highly susceptible subpopulation or when the disease enters a network of connected individuals. For example, significant HIV outbreaks among people who inject drugs have occurred in at least half a dozen US states in recent years. This motivates the current study: how can limited testing resources be allocated across geographic regions to rapidly detect outbreaks of an endemic infectious disease? We develop an adaptive sampling algorithm that uses profile likelihood to estimate the distribution of the number of positive tests that would occur for each location in a future time period if that location were sampled. Sampling is performed in the location with the highest estimated probability of triggering an outbreak alarm in the next time period. The alarm function is determined by a semiparametric likelihood ratio test. We compare the profile likelihood sampling (PLS) method numerically to uniform random sampling (URS) and Thompson sampling (TS). TS was worse than URS when the outbreak occurred in a location with lower initial prevalence than other locations. PLS had lower time to outbreak detection than TS in some but not all scenarios, but was always better than URS even when the outbreak occurred in a location with a lower initial prevalence than other locations. PLS provides an effective and reliable method for rapidly detecting endemic disease outbreaks that is robust to this uncertainty.
Spontaneous Formation of Lead‐Free Cs3Cu2I5 Quantum Dots in Metal–Organic‐Frameworks with Deep‐Blue Emission
Authors: Zhang Yuqing , He Yong , Tang Zhenyu , Yu Wenjin , Zhang Zehao , Chen Zhijian , Xiao Lixin , Shi Jun‐jie , Wang Shufeng , Qu Bo 
Published: May 2022

AbstractAll‐inorganic lead‐free Cs3Cu2I5 perovskite‐derivant quantum dots (QDs) have attracted tremendous attention due to their nontoxicity and unique optoelectronic properties. However, the traditional hot‐injection method requires high temperatures and multiple ligands to confine the growth of QDs. Herein, a strategy is reported to spontaneously synthesize ultrasmall Cs3Cu2I5 QDs within metal–organic‐frameworks (MOFs) MOF‐74 at room temperature (RT) with an average diameter of 4.33 nm. The obtained Cs3Cu2I5 QDs exhibit an evident deep‐blue emission with Commission Internationale de L'Eclairage coordinates of (0.17, 0.07), owing to the strong quantum confinement effect. Due to the protection of MOF‐74, the Cs3Cu2I5 QDs demonstrate superior stability, and the photoluminescence quantum yield retains 89% of the initial value after the storage of 1440 h under the environment with relative humidity exceeding 70%. Besides, triplet–triplet annihilation upconversion emission is observed within the composite of Cs3Cu2I5@MOF‐74, which brings out apparent temperature‐dependent photoluminescence. This study reveals a facile method for fabricating ultrasmall lead‐free perovskite‐derivant QDs at RT without multiple ligands. Besides, the temperature‐dependent photoluminescence of Cs3Cu2I5@MOF‐74 may open up a new way to develop the applications of temperature sensors or other related optoelectronic devices.
In‐Plane Mott–Schottky Effects Enabling Efficient Hydrogen Evolution from Mo5N6‐MoS2 Heterojunction Nanosheets in Universal‐pH Electrolytes
Authors: Pi Chaoran , Li Xingxing , Zhang Xuming , Song Hao , Zheng Yang , Gao Biao , Kızılaslan Abdulkadir , Chu Paul K. , Huo Kaifu 
Published: May 2022

AbstractCost‐effective electrocatalysts for the hydrogen evolution reaction (HER) spanning a wide pH range are highly desirable but still challenging for hydrogen production via electrochemical water splitting. Herein, Mo5N6‐MoS2 heterojunction nanosheets prepared on hollow carbon nanoribbons (Mo5N6‐MoS2/HCNRs) are designed as Mott–Schottky electrocatalysts for efficient pH‐universal HER. The in‐plane Mo5N6‐MoS2 Mott–Schottky heterointerface induces electron redistribution and a built‐in electric field, which effectively activates the inert MoS2 basal planes to intrinsically increase the electrocatalytic activity, improve electronic conductivity, and boost water dissociation activity. Moreover, the vertical Mo5N6‐MoS2 nanosheets provide more activated sites for the electrochemical reaction and facilitate mass/electrolyte transport, while the tightly coupled HCNRs substrate and metallic Mo5N6 provide fast electron transfer paths. Consequently, the Mo5N6‐MoS2/HCNRs electrocatalyst delivers excellent pH‐universal HER performances exemplified by ultralow overpotentials of 57, 59, and 53 mV at a current density of 10 mA cm−2 in acidic, neutral, and alkaline electrolytes with Tafel slopes of 38.4, 43.5, and 37.9 mV dec−1, respectively, which are superior to those of the reported MoS2‐based catalysts and outperform Pt in overall water splitting. This work proposes a new strategy to construct an in‐plane heterointerface on the nanoscale and provides fresh insights into the HER electrocatalytic mechanism of MoS2‐based heterostructures.
Sort race
Authors: Zhang Hantao , Meng Baoluo , Liang Yiwen 
Published: May 2022

AbstractSorting is one of the oldest computing problems and is still very important in the age of big data. Numerous algorithms and implementation techniques have been proposed. In this study, we focus on comparison based, internal sorting algorithms. We created 12 types of data of various sizes for experiments and tested extensively various implementations in a single setting. Using some effective techniques, we found that quicksort is adaptive to nearly sorted inputs and is still the best overall sorting algorithm. We also identified techniques that are effective in timsort, which is one of the most popular and efficient sorting methods based on natural mergesort. In addition, we created a version of our own mergesort, which performs better than timsort on nearly sorted instances. Our implementations of quicksort and mergesort are different from other implementations reported in all textbooks or research articles, and are faster than any version of the C library qsort functions not only for randomly generated data, but also for various types of nearly sorted data. This work can aid the user to choose the best sorting algorithm for the hard sorting job at hand, and provides a platform for anyone to test their own sorting algorithm against the best in the field.
DNA Nanotechnology‐Based Supramolecular Assemblies for Targeted Biomedical Applications
Authors: Singh Ankur , Bhatia Dhiraj 
Published: May 2022

AbstractDNA is a polyanionic, hydrophilic, and natural biopolymer that offers properties such as biodegradability, biocompatibility, non‐toxicity, and non‐immunogenicity. These properties of DNA as an ideal biopolymer offer modern‐day researchers’ reasons to exploit these to form high‐order supramolecular assemblies. These structures could range from simple to complex and provide various applications. Among them, supramolecular assemblies like DNA hydrogels (DNA‐HG) and DNA dendrimers (DNA‐DS) show massive growth potential in the areas of biomedical applications such as cell biology, medical stream, molecular biology, pharmacology, and healthcare product manufacturing. The application of both of these assemblies has seen enormous growth in recent years. In this focused review on DNA‐based supramolecular assemblies like hydrogels and dendrimers, we present the principles of synthesis and characterization, key developments with examples and applications, and conclude with a brief perspective on challenges and future outlook for such devices and their subsequent applications.
Synthesis, characterization, anticancer, and antioxidant activities of chitosan Schiff bases bearing quinolinone or pyranoquinolinone and their silver nanoparticles derivatives
Authors: Mostafa Mai A. , Ismail Mostafa M. , Morsy Jehan M. , Hassanin Hany M. , Abdelrazek Marwa M. 
Published: May 2022

AbstractIn this work, new chitosan-based Schiff bases were synthesized by the reaction of chitosan with quinolinone and pyranoquinolinone giving CSQ, and CSP, respectively. The novel Chitosan Schiff bases were grafted on silver nanoparticles providing CSQ/Ag, CSP/Ag structures. Characterization of isolated compounds was carried out by FT-IR, TGA, XRD, SEM, and TEM. The target compounds CSQ, CSP, CSQ/Ag, and CSP/Ag were evaluated as antitumor agents against three cancer cell lines, liver (HepG-2), colon (HCT-116), and breast (MCF-7). Compound CSQ/Ag disclosed potent cytotoxic effect with IC50 values in the range of 41.9–55.1 μg/ml in comparison with 5-fluorouracil against different cancer cell lines. Besides, the antioxidant activity of chitosan and its quinolinone and pyranoquinolinone analogues was assessed as radical scavengers versus 1,1-diphenyl-2-picrylhydrazyl radicals (DPPH%). The compound CSQ/Ag emerged as the most active member in scavenging the DPPH radicals. The obtained findings proved that the new Schiff bases/silver nanoparticles of chitosan showed higher antiproliferative and antioxidant activities than the blank CS and would be highly applicable in biomedical fields.
Graphical abstract
Daily supplementation of a multiple micronutrient powder improves folate but not thiamine, riboflavin, or vitamin B12 status among young Laotian children: a randomized controlled trial
Authors: Hinnouho Guy-Marino , Hampel Daniela , Shahab-Ferdows Setareh , Barffour Maxwell A. , McAnena Liadhan , Arnold Charles D. , Ryan Wessells K. , Kounnavong Sengchanh , Allen Lindsay H. , McNulty Helene , Hess Sonja Y. 
Published: May 2022

Abstract
Purpose
To assess the effects of intervention with a daily multiple micronutrient powder (MNP) on thiamine, riboflavin, folate, and B12 status among young Laotian children.

Methods
Children (n = 1704) aged 6–23 mo, participating in a double-blind placebo-controlled randomized trial were individually randomized to receive daily either MNP (containing 0.5 mg of thiamine, 0.5 mg riboflavin, 150 μg folic acid, and 0.9 μg vitamin B12 along with 11 other micronutrients) or placebo and followed for ~ 36 weeks. In a randomly selected sub-sample of 260 children, erythrocyte thiamine diphosphate (eThDP), plasma folate and B12 concentrations, and erythrocyte glutathione reductase activation coefficient (EGRac; riboflavin biomarker) were assessed at baseline and endline.

Results
There was no treatment effect on endline eThDP concentrations (110.6 ± 8.9 nmol/L in MNP vs. 109.4 ± 8.9 nmol/L in placebo group; p = 0.924), EGRac (1.46 ± 0.3 vs. 1.49 ± 0.3; p = 0.184) and B12 concentrations (523.3 ± 24.6 pmol/L vs. 515.9 ± 24.8 pmol/L; p = 0.678). Likewise, the prevalence of thiamine, riboflavin, and B12 deficiencies did not differ significantly between the two groups. However, endline folate concentration was significantly higher in the MNP compared to the placebo group (28.2 ± 0.8 nmol/L vs 19.9 ± 0.8 nmol/L, respectively; p < 0.001), and correspondingly, the prevalence of folate deficiency was significantly lower in the MNP group (1.6% vs 17.4%; p = 0.015).

Conclusions
Compared to a placebo, daily MNP for 9 months increased only folate but not thiamine, riboflavin, or B12 status in young Laotian children.

Trial registration
The trial was registered at www.clinicaltrials.gov (NCT02428647) on April 29 2015.
Clinical benefit and cost-effectiveness analysis of liquid biopsy application in patients with advanced non-small cell lung cancer (NSCLC): a modelling approach
Authors: Englmeier Fabienne , Bleckmann Annalen , Brückl Wolfgang , Griesinger Frank , Fleitz Annette , Nagels Klaus 
Published: May 2022

Abstract
Purpose
Targeted therapies are effective therapeutic approaches in advanced stages of NSCLC and require precise molecular profiling to identify oncogenic drivers. Differential diagnosis on a molecular level contributes to clinical decision making. Liquid biopsy (LB) use has demonstrated its potential to serve as an alternative to tissue biopsy (TB) particularly in cases where tissue sampling is not feasible or insufficient. We aimed at evaluating the cost-effectiveness of ctDNA-based LB use (molecular multigene testing) according to German care guidelines for metastatic NSCLC.

Methods
A Markov model was developed to compare the costs and clinical benefits associated with the use of LB as an add-on to TB according to the guidelines for NSCLC patients. Usual care TB served as comparator. A microsimulation model was used to simulate a cohort of non-squamous NSCLC patients stage IV. The parameters used for modelling were obtained from the literature and from the prospective German CRISP registry (“Clinical Research platform Into molecular testing, treatment, and outcome of non-Small cell lung carcinoma Patients”). For each pathway, average direct medical costs, and QALYs gained per patient were used for calculating incremental cost-effectiveness ratios (ICER).

Results
The use of LB as an add-on was costlier (€144,981 vs. €144,587) but more effective measured in QALYs (1.20 vs. 1.19) for the care pathway of NSCLC patients (ICER €53,909/QALY). Cost-effectiveness was shown for EGFR-mutated patients (ICER €-13,247/QALY).

Conclusion
Including LB as an add-on into the care pathway of advanced NSCLC has positive clinical effects in terms of QALYs accompanied by a moderate cost-effectiveness.
The effect of plant–plant interactions as a key biotic process mediating the spatial variation of phenotypes in a Pinus sylvestris forest
Authors: Carvalho Bárbara , de la Cruz Marcelino , Escudero Adrián , Bastias Cristina C. , Valladares Fernando , Benavides Raquel 
Published: May 2022

Abstract
Key message
In this work, we highlighted the importance of the phenotypic structure of forest in regulating inter-tree competition with scattered individuals showing larger growth than close neighbours, with lower growth rates.

Abstract
Plant interactions are among the fundamental processes shaping the structure and functioning of ecosystems as they modulate competitive dynamics. However, the connection between the response of individual growth to neighbours and to environmental conditions and the mechanisms determining interactions in monospecific stands remain poorly understood. Here, we followed a phenotypic-based approach to disentangle the effect of plant size, neighbourhood interactions and microhabitat effects on Pinus sylvestris growth and traits, as well as their spatial variation of growth. We mapped all adult trees (1002 pines) in a 2 ha stand and measured their height, DBH and crown projection. For each individual, we assessed its growth and a competition index in relation to the closest neighbours. Soil chemical and physical properties and ground cover were also measured in a grid within the stand. We analysed the effects of tree size, neighbour competition and microhabitat variation on tree growth with a linear model. We also used spatial mark-correlation functions to explore the spatial dependence of tree age, secondary growth and phenotypic traits. Our results showed that trees with close neighbours displayed lower growth rates, whilst individuals with larger growths appeared scattered throughout the stand. Moreover, we found that growth depended on competition, tree height and crown area while tree growth poorly correlated with age or microhabitat conditions. Our findings highlight the importance of forest structure, in regulating inter-tree competition and growth in a Mediterranean pure stand and they provide insight into the causes and consequences of intraspecific variation in this system.
Is HbA1c a valid surrogate for mortality in type 2 diabetes? Evidence from a meta-analysis of randomized trials
Authors: Baechle Christina , Scherler Wiebke , Lang Alexander , Filla Tim , Kuss Oliver 
Published: May 2022

Abstract
Aims
Hemoglobin A1c (HbA1c) has been repeatedly questioned as a valid surrogate marker, especially for patient-relevant outcomes. The aim of this study was to validate the HbA1c value as a surrogate for all-cause mortality in people with type 2 diabetes.

Methods
The effect estimates for HbA1c lowering after treatment as well as reductions in all-cause mortality of randomized trials were extracted from a systematic review and updated. For the measurement of actual surrogacy, weighted linear regression models with a random intercept for the study effect were used with the all-cause mortality estimate (risk difference and log relative risk) as the outcome and the estimate for HbA1c difference as the covariate. Surrogacy was assessed according to the criteria of Daniels and Hughes.

Results
A total of 346 HbA1c-mortality-pairs from 205 single randomized trials were included in the analysis. Regarding the risk difference of all-cause mortality, there was no evidence for surrogacy of the HbA1c value. For the log relative risk, a small positive association between HbA1c and the all-cause mortality estimate (slope 0.129 [95% confidence interval −0.043; 0.302]) was observed. However, there was no sign of valid surrogacy.

Conclusions
Based on the results of more than 200 randomized trials, HbA1c is not a valid surrogate marker for all-cause mortality in people with type 2 diabetes.