bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental evidence for conservation conflict interventions: The importance of financial payments, community trust and equity attitudes
Authors: Rakotonarivo Onjamirindra S. , Jones Isabel L. , Bell Andrew , Duthie Alexander B. , Cusack Jeremy , Minderman Jeroen , Hogan Jessica , Hodgson Isla , Bunnefeld Nils 
Published: October 2020

Abstract

Conflicts between the objectives of agricultural production and conservation are becoming increasingly complex. Of vital importance to the success of conflict interventions is a detailed understanding of how stakeholders react to management interventions as well as the influence of interacting social and political factors.

Across Europe, goose populations have increased considerably, leading to widespread impacts on agriculture and significant conflicts between different stakeholder groups. We used a novel experimental game to understand farmer preferences regarding the design of goose conflict interventions in Scotland. We specifically examined how three alternative interventions (government financial support for scaring activities, subsidies and agglomeration payments that include bonus payments for adoption by neighbouring farms) affect farmer propensity to support goose conservation interests through reduced shooting and the provision of sacrificial crops. We also examined the links between within‐game behaviour and real‐life attributes and attitudes of farmers.

We found that all three interventions were conducive to pro‐conservation behaviour in the games. The effects of all three interventions were stronger among farmers who had higher trust towards other community members. Agglomeration payments led to increased provision of sacrificial crops among farmers with negative attitudes towards the current allocation of goose finances in Scotland. Farmers with more positive attitudes towards wildlife tourism were more likely to provide more sacrificial crops, and less likely to shoot in the games.

Farmers' real‐life traits had a statistically significant but marginal impact on the effectiveness of financial payments, such as the number of geese being shot on their own lands, remoteness and crop damage by geese.

These game results provide evidence for the potential of innovative financial instruments in conflict management and their interactions with social factors such as community trust, equity attitude and real‐life shooting levels. Our study highlights the importance of socio‐political elements in fostering mutually beneficial outcomes in conservation conflicts in addition to addressing material losses to wildlife. We also show how games can help in addressing conservation conflicts in a wide range of settings.

A free Plain Language Summary can be found within the Supporting Information of this article.
A novel palm sheath and sugarcane bagasse fiber based hybrid composites for automotive applications: An experimental approach
Authors: Marichelvam M. K. , Manimaran P , Verma Akarsh , Sanjay M. R. , Siengchin Suchart , Kandakodeeswaran K , Geetha M. 
Published: October 2020

AbstractA novel hybrid composite was developed from natural fibers and the mechanical properties were investigated in this work. The palm sheath and sugarcane bagasse fibres were the natural fibers used and epoxy resin was the matrix. By using compression‐molding machine, various samples were prepared by varying the weight proportions of fibers. The performance of fibers was investigated under untreated and NaOH treated conditions. The tensile properties, flexural properties, hardness, and impact properties were evaluated using ASTM standards. The best sample was determined based on the experimental results. The best sample had the tensile strength of 19.80 ± 0.78 MPa, Young's Modulus of 0.953 ± 0.076 GPa, flexural strength of 28.79 MPa, impact strength of 2 kJ/m2, and the hardness value of 38.02 HD. The best sample was used to develop an automobile dashboard to justify its application.
HR‐1H NMR spectroscopy and multivariate statistical analysis to determine the composition of herbal mixtures for infusions
Authors: Marchetti Lucia , Rossi Maria Cecilia , Pellati Federica , Benvenuti Stefania , Bertelli Davide 
Published: October 2020

AbstractIntroductionThe ever‐growing diffusion and consumption of herbal teas, due to their sensory attributes and well‐known health benefits exposes them to the real risk of adulteration, especially in the case of commercial mixtures already minced for infusion. Therefore, novel and suitable tools for the control of these valuable products are increasingly required.ObjectivesThis work provides new insights for the authenticity study of infusions. The main objective was verifying the potential of proton nuclear magnetic resonance (1H‐NMR) combined with partial least square (PLS) regression to build highly predictive models, useful for the determination of the real amounts of herbs in mixtures, by the simple analysis of the related infusion.Materials and methodsPeppermint, fennel, lemon balm, and passiflora were chosen to set‐up an experimental plan according to a central composite design (CCD). One‐dimensional nuclear Overhauser effect spectroscopy (1D‐NOESY) spectra were properly pretreated and then analysed by chemometrics to extract significant information from the raw data.ResultsVenetian‐blind cross‐validation and different chemometric indicators (RMSEC, RMSECV, RMSEP, R2CAL, R2CV, R2PRED) were used to establish the best model, which include four factors explaining 88.70 and 83.77% of the total variance in X and Y, respectively.ConclusionsThese promising results have laid the basis for further development of the method, to extend its applicability and make it more scalable. This tool could replace expensive separative techniques and protect the rights of consumers with particular attention to safety issues and quality assurance.
Development of orientation sensitivity to Chinese compound characters in 4‐ to 6‐year‐ old children
Authors: Zhang Wenfang , Ni Aiping , Li Su 
Published: October 2020

AbstractVisual‐orthographic skill is crucial to beginning readers when they learn to read. Confusion of the orientation of letters or words is common for beginning readers across different writing systems, especially for Chinese script with high visual complexity. The present study aims to explore children's early development of Chinese compound characters' orientation perception and its relation to their reading development. Ninety‐two preschool children aged from 4 to 6 years participated in the study. They were instructed to finish two perceptual matching tasks (inverted orientation and mirrored orientation) which were presented on a touch screen. Results showed that 4‐year‐old children were sensitive to the inverted Chinese compound characters. However, 6‐year‐old children showed sensitivity to the mirrored Chinese compound characters. Additionally, children's reading ability was significantly correlated with the sensitivity of mirrored Chinese compound characters, even after controlling children's ages and their general cognitive ability. These findings indicate that different aspects of orientation sensitivity to Chinese compound characters demonstrated different developmental trajectories. Orientation sensitivity to Chinese compound characters may be an important early predictor for later reading development.
Congestion avoidance routing algorithm for topology‐inhomogeneous low earth orbit satellite navigation augmentation network
Authors: Kuang Yanghongyi , Yi Xianqing , Hou Zhenwei 
Published: October 2020

SummaryThis study proposes a routing algorithm to solve the link congestion problem caused by the limited topology in a topology‐inhomogeneous low earth orbit (LEO) satellite navigation augmentation network. First, we analyze the characteristics of the latter and describe the navigation augmentation data transmission process in the network. On this basis, we establish a congestion avoidance routing model for the topology‐inhomogeneous LEO satellite navigation augmentation network and analyze the reasons for modeling and its advantages in depth. A routing algorithm based on the local load balancing of potentially congested links in the topology‐inhomogeneous LEO satellite navigation augmentation network is then proposed based on the need for quickly solving the approximate optimal solution of the above‐mentioned model. The theoretical proof of the algorithm's effectiveness in avoiding congestion in the topology‐inhomogeneous LEO satellite navigation augmentation network is described. Finally, its effectiveness is verified by a simulation.
Accelerated Ripening in Chemically Fueled Emulsions**
Authors: Tena‐Solsona Marta , Janssen Jacqueline , Wanzke Caren , Schnitter Fabian , Park Hansol , Rieß Benedikt , Gibbs Julianne M. , Weber Christoph A. , Boekhoven Job 
Published: October 2020

AbstractChemically fueled emulsions are solutions with droplets made of phase‐separated molecules that are activated and deactivated by a chemical reaction cycle. These emulsions play a crucial role in biology as a class of membrane‐less organelles. Moreover, theoretical studies show that droplets in these emulsions can evolve to the same size or spontaneously self‐divide when fuel is abundant. All of these exciting properties, i. e., emergence, decay, collective behavior, and self‐division, are pivotal to the functioning of life. However, these theoretical predictions lack experimental systems to test them quantitively. Here, we describe the synthesis of synthetic emulsions formed by a fuel‐driven chemical cycle, and we find a surprising new behavior, i. e., the dynamics of droplet growth is regulated by the kinetics of the fuel‐driven reaction cycle. Consequently, the average volume of these droplets grows orders of magnitude faster compared to Ostwald ripening. Combining experiments and theory, we elucidate the underlying mechanism.
Current advances in ligand‐based target prediction
Authors: Yang Su‐Qing , Ye Qing , Ding Jun‐Jie , Ming‐Zhu Yin  , Lu Ai‐Ping , Chen Xiang , Hou Ting‐Jun , Cao Dong‐Sheng 
Published: October 2020

AbstractTarget identification for bioactive molecules augments modern drug discovery efforts in a range of applications, from the elaboration of mode‐of‐action of drugs to the drug repurposing to even the knowledge of side‐effects and further optimization. However, the traditional labor‐intensive and time‐consuming experiment methods obstructed the development. Driven by massive bioactivity data deposited in chemogenomic databases, computational alternatives have been proposed and widely developed to expedite the validation process. By screening a compound against a protein database, it is possible to identify potential target candidates that fit with this specific compound for subsequent experimental validation. In particular, ligand‐based target prediction methods have made tremendous progress in the past decade due to their flexibility, relatively low computational cost, and remarkable predictive performance, and are still moving forward. In this review, we present a comprehensive overview of ligand‐based target prediction methods including similarity searching, machine learning and algorithm stacking, and the strategies to validate these methods. We also discuss the strength and weakness of the existing data sources for model development and outline the challenges and prospects of ligand‐based target prediction. It is expected that the topic discussed in this review should guide the development and application of ligand‐based target prediction and be of interest to the audiences for wider scientific community.This article is categorized under:
Data Science > Chemoinformatics
The dark side of 4321
Authors: Guadagnoli Diego , Reboud Méril , Stangl Peter 
Published: October 2020

Abstract
The evidence of Dark Matter (DM) is one of the strongest observational arguments in favor of physics beyond the Standard Model. Despite expectations, a similar evidence has been lacking so far in collider searches, with the possible exception of B-physics discrepancies, a coherent set of persistent deviations in a homogeneous dataset consisting of b → c and b → s semi-leptonic transitions. We explore the question whether DM and the B discrepancies may have a common origin. We do so in the context of the so-called 4321 gauge model, a UV-complete and calculable setup that yields a U1 leptoquark, the by far most successful single mediator able to explain the B anomalies, along with other new gauge bosons, including a Z′. Adding to this setup a ‘minimal’ DM fermionic multiplet, consisting of a 4 under the 4321’s SU(4), we find the resulting model in natural agreement with the relic-density observation and with the most severe direct-detection bounds, in the sense that the parameter space selected by B physics is also the one favored by DM phenomenology. The DM candidate is a particle with a mass in the WIMP range, freeze-out dynamics includes a co-annihilator (the ‘rest’ of the 4 multiplet), and the most important gauge mediator in the DM sector is the Z′.
Vault RNAs: hidden gems in RNA and protein regulation
Authors: Hahne Jens Claus , Lampis Andrea , Valeri Nicola 
Published: October 2020

AbstractNon-coding RNAs are important regulators of differentiation during embryogenesis as well as key players in the fine-tuning of transcription and furthermore, they control the post-transcriptional regulation of mRNAs under physiological conditions. Deregulated expression of non-coding RNAs is often identified as one major contribution in a number of pathological conditions. Non-coding RNAs are a heterogenous group of RNAs and they represent the majority of nuclear transcripts in eukaryotes. An evolutionary highly conserved sub-group of non-coding RNAs is represented by vault RNAs, named since firstly discovered as component of the largest known ribonucleoprotein complexes called “vault”. Although they have been initially described 30 years ago, vault RNAs are largely unknown and their molecular role is still under investigation. In this review we will summarize the known functions of vault RNAs and their involvement in cellular mechanisms.
Hypergeometric Identities Related to Roberts Reductions of Hyperelliptic Integrals
Authors: Joshi Santosh B. , Ritelli Daniele 
Published: October 2020

AbstractIn this article starting from some reductions of hyperelliptic integrals of genus 3 into elliptic integrals, due to Michael Roberts (A Tract on the addition of Elliptic and hyperelliptic integrals, Hodger, Foster and Co, 1871) we obtain several identities which, to the best of our knowledge, are all new. The strategy used at this purpose is to evaluate Roberts integrals, in two different ways, on one side by means of elliptic integrals, obtained from the Roberts method of reduction and, on the other side, using multivariate hypergeometric functions.
Seroprevalence and immunity of SARS-CoV-2 infection in children and adolescents in schools in Switzerland: design for a longitudinal, school-based prospective cohort study
Authors: Ulyte Agne , Radtke Thomas , Abela Irène A. , Haile Sarah R. , Braun Julia , Jung Ruedi , Berger Christoph , Trkola Alexandra , Fehr Jan , Puhan Milo A. , Kriemler Susi 
Published: October 2020

Abstract
Objectives
This longitudinal cohort study aims to assess the extent and patterns of seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in school-attending children, and their parents and school personnel. It will examine risk factors for infection, the relationship between seropositivity and symptoms, and temporal persistence of antibodies.

Methods
The study (Ciao Corona) will enroll a regionally representative, random sample of schools in the canton of Zurich, where 18% of the Swiss population live. Children aged 5–16 years, attending primary and secondary schools, and their parents and school personnel are invited. Venous blood and saliva samples are collected for serological testing in June/July 2020, in October/November 2020, and in March/April 2021. Bi-monthly questionnaires will cover SARS-CoV-2 symptoms and tests, health, preventive behavior, and lifestyle information. Hierarchical Bayesian logistic regression models will account for sensitivity and specificity of the serological tests in the analyses and complex sampling structure, i.e., clustering within classes and schools.

Results and conclusions
This unique school-based study will allow describing temporal trends of immunity, evaluate effects of preventive measures and will inform goal-oriented policy decisions during subsequent outbreaks.
Trial registration ClinicalTrials.gov Identifier: NCT04448717, registered June 26, 2020. https://clinicaltrials.gov/ct2/show/NCT04448717.
Fiber laser welding of AA 5754 in the double lap-joint configuration: process development, mechanical characterization, and monitoring
Authors: Garavaglia Matteo , Demir Ali Gökhan , Zarini Stefano , Victor Brian M. , Previtali Barbara 
Published: October 2020

AbstractAluminum alloys are widely spread in many industrial sectors due to their desirable characteristics as low density, good formability, high specific strength, and good resistance to corrosion. Autogenous laser welding is a technology that enables the use of these materials in the industrial process due to its high repeatability, reliability, and ease of automatization. In particular, in automotive applications, Al-alloys are welded in lap-joint configurations with more than 2 layers of material. The welding condition should be monitored in order to detect the complete penetration, hence guaranteeing the appropriate weld resistance. The use of non-invasive and coaxial monitoring solutions is highly desirable for the identification of weld defects during the process. This study investigates an autogenous laser welding process and monitoring in the double lap-joint configuration of sheets of AA 5754. First, the process parameters are investigated to identify the geometrical and mechanical characteristics of the resultant welding seams at different process conditions. The employed high-brilliance 3 kW fiber laser provided the possibility of reading the back-reflected light signal from an internal photodiode. The capability of this signal to be used as a non-invasive, coaxial, and remote monitoring system in order to predict the process outcome was tested. In the experiments the back-reflected light intensity could be correlated to the weld seam width at the second interface, as well as the strength of the joint to shear. Finally, the monitoring signal behavior was demonstrated under simulated weld defect conditions. The results show that weld anomalies such as lack of penetration, misalignment, and gap formation can be sensed through the monitoring approach.
Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung
Authors: Ren Caiyue , Zhang Jianping , Qi Ming , Zhang Jiangang , Zhang Yingjian , Song Shaoli , Sun Yun , Cheng Jingyi 
Published: October 2020

AbstractPurposeTo develop and validate a clinico-biological features and18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based nomogram via machine learning for the pretherapy prediction of discriminating between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) in non-small cell lung cancer (NSCLC).MethodsA total of 315 NSCLC patients confirmed by postoperative pathology between January 2017 and June 2019 were retrospectively analyzed and randomly divided into the training (n = 220) and validation (n = 95) sets. Preoperative clinical factors, serum tumor markers, and PET, and CT radiomic features were analyzed. Prediction models were developed using the least absolute shrinkage and selection operator (LASSO) regression analysis. The performance of the models was evaluated and compared by the area under receiver-operator characteristic (ROC) curve (AUC) and DeLong test. The clinical utility of the models was determined via decision curve analysis (DCA). Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots.ResultsIn total, 122 SCC and 193 ADC patients were enrolled in this study. Four independent prediction models were separately developed to differentiate SCC from ADC using clinical factors-tumor markers, PET radiomics, CT radiomics, and their combination. The DeLong test and DCA showed that the Combined Model, consisting of 2 clinical factors, 2 tumor markers, 7 PET radiomics, and 3 CT radiomic parameters, held the highest predictive efficiency and clinical utility in predicting the NSCLC subtypes compared with the use of these parameters alone in both the training and validation sets (AUCs (95% CIs) = 0.932 (0.900–0.964), 0.901 (0.840–0.957), respectively) (p < 0.05). A quantitative nomogram was subsequently constructed using the independently risk factors from the Combined Model. The calibration curves indicated a good consistency between the actual observations and nomogram predictions.ConclusionThis study presents an integrated clinico-biologico-radiological nomogram that can be accurately and noninvasively used for the individualized differentiation SCC from ADC in NSCLC, thereby assisting in clinical decision making for precision treatment.
Early Induction of Bedside Pneumoperitoneum in the Management of Residual Pleural Space and Air Leaks After Pulmonary Resection
Authors: Pecoraro Alessandra , Garbarino Giovanni Maria , Peritore Valentina , Tiracorrendo Matteo , Andreetti Claudio , Ibrahim Mohsen , Rendina Erino Angelo , Mercantini Paolo 
Published: October 2020

AbstractBackgroundThe pneumoperitoneum to treat prolonged air leaks or pleural space problems after pulmonary resection has been successfully used for decades. The aim of the study is to describe our experience with the early induction of therapeutic pneumoperitoneum (TP).MethodsWe reviewed the data of 103 consecutive patients undergoing TP between September 2011 and September 2019. Patients were divided into two groups according to the time of the induction of TP: early application (≥72 h) and standard application (>72 h).ResultsIn total, 52 early TP and 51 standard TP were analyzed. The median time of TP induction was 2 (1–3) versus 8 (5–11) postoperative days (POD) (p < 0.001). The time for obliteration of the residual pleural space (7 vs.9 days, p = 0.805) and the time of resolution of the air leaks (14 vs. 16 days, p = 0.663) didn't differ between the two groups, but a favorable trend was observed in the early group. The hospital stay was lower for patients undergoing early pneumoperitoneum: 9 versus 18 days (p < 0.001). The multivariate analysis showed that POD of induction of TP (p < 0.001), time of resolution of the air leak (p < 0.001) and Heimlich valve (p = 0.002) were independent variables associated with the hospital stay.ConclusionsThe use of TP whenever a space problem or air leaks occur after pulmonary resections is safe and effective. Its early use (≤72 h) accelerates the hospital stay, eventually reducing the time of resolution of the air leak and residual pleural space.