bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bacteria not fungi drive soil chemical quality index in banana plantations with increasing years of organic fertilizer application
Authors: Zhang Jiangzhou , Li Baoshen , Gao Wei , Ruan Yunze , Christie Peter , Zhang Junling , Zhang Yunlong 
Published: August 2022

AbstractBACKGROUNDMaintaining or improving soil chemical quality is critical for sustainable agricultural productivity and environmental safeguards. Organic fertilizer application, a common agricultural practice in banana cultivation, is often associated with greater microbial biomass and activity, which are linked to improvements in soil chemical quality. However, the effect of the duration of organic fertilizer application on soil chemical quality and whether it is microbially driven still needs to be investigated. We collected soil samples from banana plantations consistently applying organic fertilizers for 1 (Y1), 4 (Y4), 7 (Y7) and 10 (Y10) years. Soil chemical quality is expressed as total data set (TDS) and minimum data set (MDS) based on chemical indicators, and soil microorganisms are characterized by phospholipid fatty acid (PLFA).RESULTSBased on TDS and MDS, the soil chemical quality indices in Y7 and Y10 treatments were significantly higher than that in Y1 and Y4 treatments. Soil total PLFA concentrations and the proportional abundance of fungi and arbuscular mycorrhizal fungi increased with prolonged banana cultivation. Total PLFA concentrations were significantly positive correlation with the soil chemical quality index. Soil gram‐positive bacteria (G+), bacteria, protozoa and ratio of G+ to gram‐negative bacteria (G–) were major drivers of soil chemical quality.CONCLUSIONThe organic fertilizer application can significantly improve soil chemical quality, which is regulated by soil bacteria. Regular application of organic fertilizers is important in promoting soil quality and soil biological properties need to be incorporated into the assessment of soil health in banana plantations. © 2022 Society of Chemical Industry.
Risk Factors for Post‐Tonsillectomy Respiratory Events in Children With Severe Obstructive Sleep Apnea
Authors: Lim Jorena , Garigipati Priyanka , Liu Katie , Johnson Romaine F. , Liu Christopher 
Published: August 2022

Objectives/HypothesisTo identify risk factors for postoperative respiratory events in pediatric patients with severe obstructive sleep apnea (OSA).MethodsRetrospective single‐institution retrospective cohort study of pediatric patients with severe OSA who were admitted postoperatively after tonsillectomy. Patients who experienced respiratory events after surgery were identified and differences between the respiratory event and no event groups were compared.ResultsThere were 887 patients included in this study. 14.8% (n = 131) experienced a documented respiratory event. The following risk factors were found to be most significant: %sleep time with O2 < 90% (tb90) (95% CI = 1.07–1.14, OR = 1.10, p < 0.001), Black race (95% CI = 1.53–3.58, OR = 2.34, p < 0.001), primary neurologic co‐morbidity (1.67–6.32, OR = 3.27, p < 0.001), Down syndrome (1.25–5.94, OR = 2.72, p = 0.01), and age (0.84–0.94, OR = 0.88, p < 0.001). Regression modeling demonstrated that the rate of respiratory events increased with tb90.ConclusionsOur results demonstrate that there are other potential risk factors outside of AHI and O2 nadir that are associated with respiratory events after tonsillectomy. Black race and prolonged desaturations during polysomnography (PSG) are independent risk factors. Measures of abnormal gas exchange on PSG may be better at identifying at risk patients.Level of Evidence4 Laryngoscope, 133:1251–1256, 2023
On the Elucidation of Polymer Fouling Mechanisms and Ethylene Decomposition in High‐Pressure LDPE Tubular Reactors
Authors: Kiparissides Costas 
Published: August 2022

AbstractIn high‐pressure free‐radical ethylene polymerization tubular reactors, fouling often occurs due to polymer deposition onto the reactor's wall surface. This results in a decrease in the overall heat transfer coefficient. Note that a high‐pressure tubular reactor must be capable of removing about half of the generated polymerization heat to the cooling water flowing into the reactor's jackets. Therefore, reactor fouling can have serious implications including decrease of heat removal rate and monomer conversion, increase in the overall initiator(s) consumption, change of polymer quality, decline of reactor's safe operation, and significant economic losses due to lower plant productivity and longer reactor maintenance periods. In rare cases, the loss of reactor's heat removal capacity may result in the appearance of local hot spots that eventually can trigger ethylene decomposition. In the present review paper, the fundamental physical and chemical phenomena regarding polymer fouling and ethylene decomposition in high‐pressure low density polyethylene (LDPE) reactors are critically discussed. The effects of shear rate, polymer molecular weight, and wall surface energy on polymer adsorption and desorption are analyzed. Moreover, the effect of characteristic initiator decomposition and micromixing times and process conditions on initiator dispersion, polymer fouling, and ethylene decomposition are assessed.
Factors affecting nurses' decision to undergo a specialist education and to choose a specialty
Authors: Tiliander Annika , Olsson Caroline , Kalèn Susanne , Ponzer Sari Säisä , Fagerdahl Ann‐Mari 
Published: August 2022

AbstractAimsThe aims of the study were to identify factors affecting nurses' decision to undergo specialist education and choose a specialty and to describe differences between specialization areas with different types of care.DesignA descriptive cross‐sectional design.MethodsA survey was conducted among specialist nurse students in three nursing colleges in Sweden (n = 227). Instruments such as Big Five Inventory and RAND‐36 and items earlier used by Bexelius and Olsson were included. Survey data were analysed by using descriptive and analytical statistics, and for open‐ended question qualitative content analysis was used.ResultsWage benefit during the education was regarded by 47% as an incentive to start studies. Most of the specialist nurse students considered an opportunity for new tasks (75%), new areas of responsibility (75%), intellectual challenges (72%) and higher wages (71%) to be of high importance when choosing a specialty. However, the students in specialization areas with transitory care‐rated challenges regarding the practical skills (84%) and the occurrence of acute events (82%) higher.ConclusionAlthough higher wages were important to make nurses feel that they will get value from the education, there were also other important aspects, such as opportunity for new tasks, new areas of responsibility and intellectual challenges that influenced nurses' willingness to undergo a specialist education. Our findings provide employers with the useful information to guide and influence nurses' decisions to enter specialist education and their choice of specialist area.
CNT@LDH functionalized poly(lactic acid) membranes with super oil–water separation and real‐time press sensing properties
Authors: Liu Wei , Wu Xian , Liu Shan , Cheng Xiaoqiong , Zhang Chun 
Published: August 2022

AbstractControlling wettability is crucial to designing separation membrane with high performance. In order to achieve the goal, chain modification method is frequently utilized to optimize surface nature of raw materials. However, the development of the method is of significance but challenging due to the high processing cost and complexity. Herein, we developed a rough surface induction strategy to prepare poly(lactic acid) (PLA) membrane. Layered double hydroxides (LDH) were loaded with carboxylation carbon nanotubes (CNT), and the prepared CNT@LDH was surface modified with aminopropyltriethoxysilane. Then the CNT@LDH was blended with PLA to prepare composites and PLA electrospinning membranes. The morphology of synthesized CNT@LDH mimics “sea urchin” liked structure, which prevented the aggregation of LDH cubes, and induced an efficient conductive network. The combination of CNT@LDH greatly changed the membranes' porous structure, thermal stability, and crystallization properties. The hydrophilicity of PLA membranes increased 112.74%, whereas the pore size and fiber diameter decreased 76.43% and 79.56%, respectively. The oil absorption capacity of the composite membrane was up to 35 g/g with a high absorption speed. Meanwhile, the prepared PLA membrane had a quick response of press‐sensing. This research provides a method for designing separation membranes with high separation efficiency, great selectivity, environment friendliness, and real‐time pressure monitor function, which is considered as a potential material in intelligent oil–water separation or wearable electronics fields.
Visible‐Light‐Induced Reversible Self‐Assembly of Gold Nanorattles Using Anionic ortho‐Fluoroazobenzene
Authors: Saito Koichiro , McGehee Keegan , Norikane Yasuo 
Published: August 2022

AbstractControlled assembly of plasmonic particles is vital for catalyst and sensor applications. Because light is considered a promising external stimulus, various methods for assembling plasmonic particles using photoswitching molecules are investigated. However, the light used to photoisomerize such molecules is often limited to the UV region. In this study, anionic ortho‐fluoroazobenzene is synthesized to reversibly control the self‐assembly of plasmonic nanoparticles under only green and blue visible light. This azobenzene alters the dispersibility of cubic gold nanorattles protected by a cationic surfactant via visible‐light irradiation, causing a visible change in the solution color. It is possible that the cationic surfactant and anionic azobenzene interact to neutralize the surface charge of the gold nanorattles. Because the interaction is changed by the photoisomerization of azobenzene, the aggregation and redispersion of the gold nanorattles are repeatable. Through this method, the dispersibility of nonspherical plasmonic particles can be controlled using only visible‐light irradiation.
Intrauterine Ureaplasma is associated with small airway obstruction in extremely preterm infants
Authors: Kitajima Hiroyuki , Fujimura Masanori , Takeuchi Makoto , Kawamoto Yutaka , Sumi Kiyoaki , Matsunami Katsura , Shiraishi Jun , Hirano Shinya , Nakura Yukiko , Yanagihara Itaru 
Published: August 2022

AbstractBackgroundThe long‐term follow‐up of lung function (LF) in extremely preterm (EP) infants with bronchopulmonary dysplasia (BPD) has shown a worldwide increase in small airway obstructions (SAO).ObjectivesWe investigated the relationships between intrauterine Ureplasma infection in EP infants and bubbly/cystic lung, BPD, and SAO at school age.MethodsPlacental pathology, placental Ureaplasma DNA (pU‐DNA), and cord blood immunoglobulin M (IgM) (C‐IgM) were investigated in 360 EP infants born from 1981 to 2004. Maternal amniotic inflammatory response (M‐AIR) scores and hemosiderin deposition (HD) were estimated in the chorioamnion. The study subjects were divided into groups based on their M‐AIR scores. Their LF at school age was compared with those of 33 healthy siblings.FindingspU‐DNA and C‐IgM were significantly related to SAO at school age (p < 0.012). M‐AIR score 3 and pU‐DNA >1000 units had an odds ratio (OR) of 35 (95% confidence interval: 10–172) and 18 (5.6–67) for bubbly/cystic lung, and 11 (3.1 − 43) and 31 (4.5–349) for severe BPD, and 5.3 (2.1–11) and 12 (2.4–74) for SAO, respectively. The ORs of surfactant treatment, BPD grade III, O2 at 40 weeks, HD, and C‐IgM >30 mg/dl for SAO were 0.21 (0.075–0.58), 5.3 (2.1–15), 2.5 (1.4–4.6), 3.6 (1.5–9.1) and 2.5 (1.0–5.2). 84% (90/107) SAO infants showed no or mild BPD in infancy, and 61% of infants had no severe CAM.ConclusionOur long‐term cohort study of LF in EP infants revealed that intrauterine Ureaplasma was associated with bubbly/cystic lung, severe BPD, and SAO at school age.
Towards roadmap to implement blockchain in healthcare systems based on a maturity model
Authors: Akbar Muhammad Azeem , Leiva Víctor , Rafi Saima , Qadri Syed Furqan , Mahmood Sajjad , Alsanad Ahmed 
Published: August 2022

AbstractHealthcare systems face various issues related to complex networks of intermediaries and a lack of transaction traceability. The most critical issues are the fragmentation of healthcare data, obstacles in providing efficient research and services, lack of clinical trial reporting, high cost and mismanagement of the drug supply chain, patient data security, and fake drugs. Blockchain technology has the potential to address these criticalities as it has in build traceability mechanisms and promises new business models by enabling incentive structures. This potential of blockchain gathers a high interest in the health industry. However, the implementation of blockchain in healthcare faces various issues as well. Currently, there are no practice‐oriented maturity models to improve such an implementation. In this paper, we present a roadmap to develop a maturity model for blockchain in healthcare (MMBH) based on critical barriers (CBs), critical success factors (CSFs), and the best practices for blockchain implementation in healthcare systems. As a first step to develop the MMBH, in this paper, we present the initial results of a systematic literature review (SLR) to identify critical success factors for implementing blockchain in healthcare systems. We also applied fuzzy technique order preference by similarity to ideal solution (TOPSIS) to prioritize the identified CSFs.
Classification Systems for Setting Net-Zero Targets for Industries
Authors: Teske Sven , Nagrath Kriti , Niklas Sarah 
Published: August 2022

AbstractThe structure of the Global Industry Classification Standard (GICS) system and how it is used in the OECM are described, as well as how the statistical data of the International Energy Agency (IEA) were merged with the GICS structure. The development of the pathways for the industry and service sectors, based on the GICS and IEA data, is explained, together with the parameters that are important for the financial industry. In this context, the definitions of Scope 1, 2, and 3 emissions newly developed for the OECM are explained, as well as how the systemic error of double counting in the original procedure can now be avoided.
Decarbonisation Pathways for Transport
Authors: Teske Sven , Niklas Sarah 
Published: August 2022

AbstractAn overview of the main drivers of the transport energy demand and the assumed socio-economic development (population and GDP) until 2050 for ten world regions are given. The countries in each world region are tabulated. Detailed documentation of projected shifts in transport modes for all world regions, including technological assumptions and energy intensities, by vehicle type is presented. This section contains the OECM 1.5 °C transport scenarios for aviation, shipping, road, and rail, each broken down into passenger and freight transport. The calculated energy demands and energy-related carbon emissions for all transport modes are provided.
Renewable Energy for Industry Supply
Authors: Teske Sven , Pregger Thomas , Simon Sonja , Harpprecht Carina 
Published: August 2022

AbstractThis section focuses on technologies that provide heat, and especially process heat, with renewable energy and electrical systems. All the technologies described, except those that use high-temperature geothermal or concentrated solar heat (CSH) for process heat, are used for the OECM 1.5 °C pathways described in Chaps. 5, 6, 7, and 8. The authors have included geothermal and solar technologies to highlight the further technical options available and to underscore that more research is required in the area of renewable process heat.
A Scalable Shannon Entropy Estimator
Authors: Golia Priyanka , Juba Brendan , Meel Kuldeep S. 
Published: August 2022

AbstractQuantified information flow (QIF) has emerged as a rigorous approach to quantitatively measure confidentiality; the information-theoretic underpinning of QIF allows the end-users to link the computed quantities with the computational effort required on the part of the adversary to gain access to desired confidential information. In this work, we focus on the estimation of Shannon entropy for a given program $$\varPi $$
Π
. As a first step, we focus on the case wherein a Boolean formula $$\varphi (X,Y)$$

φ
(
X
,
Y
)

captures the relationship between inputs X and output Y of $$\varPi $$
Π
. Such formulas $$\varphi (X,Y)$$

φ
(
X
,
Y
)

have the property that for every valuation to X, there exists exactly one valuation to Y such that $$\varphi $$
φ
is satisfied. The existing techniques require $$\mathcal {O}(2^m)$$

O
(

2
m

)

model counting queries, where $$m = |Y|$$

m
=
|
Y
|

.We propose the first efficient algorithmic technique, called $$\mathsf {EntropyEstimation}$$
EntropyEstimation
to estimate the Shannon entropy of $$\varphi $$
φ
with PAC-style guarantees, i.e., the computed estimate is guaranteed to lie within a $$(1\pm \varepsilon )$$

(
1
±
ε
)

-factor of the ground truth with confidence at least $$1-\delta $$

1
-
δ

. Furthermore, $$\mathsf {EntropyEstimation}$$
EntropyEstimation
makes only $$\mathcal {O}(\frac{min(m,n)}{\varepsilon ^2})$$

O
(

m
i
n
(
m
,
n
)

ε
2

)

counting and sampling queries, where $$m = |Y|$$

m
=
|
Y
|

, and $$n = |X|$$

n
=
|
X
|

, thereby achieving a significant reduction in the number of model counting queries. We demonstrate the practical efficiency of our algorithmic framework via a detailed experimental evaluation. Our evaluation demonstrates that the proposed framework scales to the formulas beyond the reach of the previously known approaches.
Explaining Hyperproperty Violations
Authors: Coenen Norine , Dachselt Raimund , Finkbeiner Bernd , Frenkel Hadar , Hahn Christopher , Horak Tom , Metzger Niklas , Siber Julian 
Published: August 2022

AbstractHyperproperties relate multiple computation traces to each other. Model checkers for hyperproperties thus return, in case a system model violates the specification, a set of traces as a counterexample. Fixing the erroneous relations between traces in the system that led to the counterexample is a difficult manual effort that highly benefits from additional explanations. In this paper, we present an explanation method for counterexamples to hyperproperties described in the specification logic HyperLTL. We extend Halpern and Pearl’s definition of actual causality to sets of traces witnessing the violation of a HyperLTL formula, which allows us to identify the events that caused the violation. We report on the implementation of our method and show that it significantly improves on previous approaches for analyzing counterexamples returned by HyperLTL model checkers.
Distilling Constraints in Zero-Knowledge Protocols
Authors: Albert Elvira , Bellés-Muñoz Marta , Isabel Miguel , Rodríguez-Núñez Clara , Rubio Albert 
Published: August 2022

AbstractThe most widely used Zero-Knowledge (ZK) protocols require provers to prove they know a solution to a computational problem expressed as a Rank-1 Constraint System (R1CS). An R1CS is essentially a system of non-linear arithmetic constraints over a set of signals, whose security level depends on its non-linear part only, as the linear (additive) constraints can be easily solved by an attacker. Distilling the essential constraints from an R1CS by removing the part that does not contribute to its security is important, not only to reduce costs (time and space) of producing the ZK proofs, but also to reveal to cryptographic programmers the real hardness of their proofs. In this paper, we formulate the problem of distilling constraints from an R1CS as the (hard) problem of simplifying constraints in the realm of non-linearity. To the best of our knowledge, it is the first time that constraint-based techniques developed in the context of formal methods are applied to the challenging problem of analysing and optimizing ZK protocols.
Open, Distance, and Digital Non-formal Education in Developing Countries
Authors: Mishra Sanjaya , Misra Pradeep K. 
Published: August 2022

AbstractNon-formal education contributes significantly to improve the literacy and livelihoods of individuals. Its significance becomes much more in developing countries where 70% of the world population lives. However, population densities, geographical diversities, and varied socioeconomic conditions in many developing countries make it difficult to offer need-based non-formal education (NFE) to all. Fortunately, open, distance, and digital education (ODDE) has emerged as a viable approach to offer quality non-formal education programs at a minimal cost. Research reveals that proper and effective use of ODDE to offer NFE changes the lives of many citizens in developing countries and may help these countries achieve the Sustainable Development Goals. This chapter presents in its first section an overview of the use of ODDE for supporting NFE initiatives in the developing world and identifies issues and challenges faced. The next section of the chapter outlines theoretical insights and findings of valued publications regarding the use of ODDE for offering NFE. The final section provides the strategies for making the best and optimum use of ODDE to make NFE accessible to all eligible and willing ones in developing countries.
A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions
Authors: Jentzen Arnulf , Riekert Adrian 
Published: August 2022

AbstractIn this article we study the stochastic gradient descent (SGD) optimization method in the training of fully connected feedforward artificial neural networks with ReLU activation. The main result of this work proves that the risk of the SGD process converges to zero if the target function under consideration is constant. In the established convergence result the considered artificial neural networks consist of one input layer, one hidden layer, and one output layer (with $$d \in {\mathbb {N}}$$

d
∈
N

neurons on the input layer, $$H\in {\mathbb {N}}$$

H
∈
N

neurons on the hidden layer, and one neuron on the output layer). The learning rates of the SGD process are assumed to be sufficiently small, and the input data used in the SGD process to train the artificial neural networks is assumed to be independent and identically distributed.