bluuebunny/crossref_metadata_2025_split huggingface dataset:
The fate of the Caspian Sea under projected climate change and water extraction during the 21st century
Authors: Koriche Sifan A , Singarayer Joy S , Cloke Hannah L 
Published: August 2021

Abstract
The Caspian Sea (CS) delivers considerable ecosystem services to millions of people. It experienced water level variations of 3 m during the 20th century alone. Robust scenarios of future CS level are vital to inform environmental risk management and water-use planning. In this study we investigated the water budget variation in the CS drainage basin and its potential impact on CS level during the 21st century using projected climate from selected climate change scenarios of shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs), and explored the impact of human extractions. We show that the size of the CS prescribed in climate models determines the modelled water budgets for both historical and future projections. Most future projections show drying over the 21st century. The moisture deficits are more pronounced for extreme radiative forcing scenarios (RCP8.5/SSP585) and for models where a larger CS is prescribed. By 2100, up to 8 (10) m decrease in CS level is found using RCP4.5 (RCP8.5) models, and up to 20 (30) m for SSP245 (SSP585) scenario models. Water extraction rates are as important as climate in controlling future CS level, with potentially up to 7 m further decline, leading to desiccation of the shallow northern CS. This will have wide-ranging implications for the livelihoods of the surrounding communities; increasing vulnerability to freshwater scarcity, transforming ecosystems, as well as impacting the climate system. Caution should be exercised when using individual models to inform policy as projected CS level is so variable between models. We identify that many climate models either ignore, or do not properly prescribe, CS area. No future climate projections include any changes in CS surface area, even when the catchment is projected to be considerably drier. Coupling between atmosphere and lakes within climate models would be a significant advance to capture crucial two-way feedbacks.
Analytical measurements of contact resistivity in two-dimensional WSe2 field-effect transistors
Authors: Moon Inyong , Choi Min Sup , Lee Sungwon , Nipane Ankur , Hone James , Yoo Won Jong 
Published: August 2021

Abstract
It becomes clear that, in two-dimensional (2D) materials-based devices, sheet resistances underneath electrodes change due to a metallic contact, leading to substantial errors in determining a transfer length. Thus, the extraction of transfer length and corresponding contact resistivity must be revisited to assess the performance of 2D devices. In this study, we present the three different approaches of determining the contact resistivity in 2D WSe2 field effect transistors for the first time by theoretical analysis using the resistive network model as well as electrical measurements using the contact-end resistance and transfer length methods, based on the followings: (a) contact resistance multiplied by transfer length (

R

cf

W
⋅

L

Tk

), (b) integrated contact resistance (

∫
0
L

R

(
x
)

⋅
W
d
x

), and (c) contact resistance raised to a constant power

R

cf

W

α

). These different extraction methods give rise to almost identical transfer length and contact resistivity, validating our model and its accuracy from the results obtained by using various contact metals and plasma doping conditions. This work serves as a foundation for future research on the determination of physical parameters responsible for the carrier transport at the metallic contact interface in 2D semiconductor devices.
A closed-form expression of effective permittivity with spherically symmetric function for honeycomb structure
Authors: Li Shilei , Wan Guobin , Fu Bin , Liu Yunzhe , Wang Nan 
Published: August 2021

Abstract
A novel closed-form expression for predicting the equivalent electromagnetic parameters of the honeycomb structure is proposed. It is obtained by approximating the correlation terms in the derivation of the strong fluctuation theory with the integral of the spherically symmetric function. Through several simulation examples, the calculation results of the formula are compared with the results of several traditional extraction methods and compared with the existing experimental data. Comparison of the extraction results of the formula with the simulation results and the experimental data shows good agreement, which proves the feasibility of the extraction expression, and this method does not require simulation as a prerequisite and can shorten the time for optimizing the design of the honeycomb absorbing structure.
Simultaneous measurement of refractive index and temperature of seawater based on surface plasmon resonance in a dual D-type photonic crystal fiber
Authors: Zhang Yingyue , Chen Hailiang , Wang Mingyue , Liu Yundong , Fan Xiaoya , Chen Qiang , Wu Biao 
Published: August 2021

Abstract
A dual D-type photonic crystal fiber (PCF) was proposed in this work to measure the refractive index and temperature of seawater. Two golden layers were designed to be coated on the two polished planes in the dual D-type PCF. Two confinement loss peaks in the transmission spectrum appeared due to the surface plasmon resonances which were inspired on the two golden layers. In order to achieve two-parameter sensing, one of the two polished planes was further coated with a polydimethylsiloxane (PDMS) layer which was temperature-sensitive. Seawater was assumed to be coated on the outer surface of the PCF. Numerical results by using the finite element method showed that the measurement sensitivity of the refractive index of seawater reached 1371 and 1228 nm/RIU, while the measurement sensitivity of temperature reached −0.3 and −1.06 nm/ °C, respectively. Finally, we obtained the transfer matrix expression which could be used to measure the refractive index and temperature of seawater simultaneously. The designed dual D-type PCF, which is simple in structure, highly sensitive and two-parameter measuring, could be a promising candidate for the monitoring of seawater.
Using design of experiments in the evaluation of the microstructural characterization parameters with the LePera reagent in a multiphase steel
Authors: de Faria Neto Antonio dos Reis , Fukugauchi Cristina Sayuri , dos Santos Pereira Marcelo 
Published: August 2021

Abstract
The performance of multiphase steels is closely related to their microconstituents. Thus, the characterization and effective control of the microstructure of these materials are crucial, and chemical attack processes are essential for this to occur. In this context, this study sought to employ the Taguchi method to evaluate the chemical etching process with the LePera reagent in order to investigate the influence of different process variables, in addition to the interactions between them, on the quality of the image obtained. The variables analyzed were: concentration of picral (CP) and sodium metabisulfite (CSM) solution, pre-attack (PA), drying mode (DM) and attack time (AT). in addition to the relative humidity and temperature of the environment. Therefore, a quality index (QI) was suggested for the images obtained, which, together with the analysis of variance, indicates the best route for microstructural characterization of TRIP800 steel (CP-4.0%; CSM-0.5% ; PA-No; DM-Natural; AT-25s; . Temperature (°C): 15I---25 and Relative humidity (%): 55I---90). In addition to indicating the variables that most influence the process. The influence of noise factors (temperature and relative humidity) was also proven.
Changes in General and Virus-Specific Anxiety During the Spread of COVID-19 in Israel: A 7-Wave Longitudinal Study
Authors: Shahar Golan , Aharonson-Daniel Limor , Greenberg David , Shalev Hadar , Malone Patrick S , Tendler Avichai , Grotto Itamar , Davidovitch Nadav 
Published: August 2021

Abstract
We compared 3 hypothetical trajectories of change in both general and coronavirus disease 2019 (COVID-19)-specific anxiety during the first wave of the spread in the state of Israel: panic (very high anxiety, either from the outset or rapidly increasing), complacency (stable and low anxiety), and threat-sensitive (a moderate, linear increase compatible with the increase in threat). A representative sample of 1,018 Jewish-Israeli adults was recruited online. A baseline assessment commenced 2 days prior to the identification of the first case, followed by 6 weekly assessments. Latent mixture modeling analyses revealed the presence of 3 trajectories: 1) “threat-sensitivity” (29% and 66%, for general and virus-specific anxiety, respectively), 2) panic (12% and 25%), and 3) complacency (29% and 9%). For general anxiety only, a fourth class representing a stable mid-level anxiety was identified (“balanced”: 30%). For general anxiety, women and the initially anxious—both generally and specifically from the spread of the virus—were more likely to belong to the panic class. Men and older participants were more likely to belong to the complacency class. Findings indicate a marked heterogeneity in anxiety responses to the first wave of the spread of COVID-19, including a large group evincing a “balanced” response.
Potential therapeutic targets of Klebsiella pneumoniae: a multi-omics review perspective
Authors: Ali Sabeeha , Alam Manzar , Hasan Gulam Mustafa , Hassan Md Imtaiyaz 
Published: August 2021

Abstract
The multidrug resistance developed in many organisms due to the prolonged use of antibiotics has been an increasing global health crisis. Klebsiella pneumoniae is a causal organism for various infections, including respiratory, urinary tract and biliary diseases. Initially, immunocompromised individuals are primarily affected by K. pneumoniae. Due to the emergence of hypervirulent strains recently, both healthy and immunocompetent individuals are equally susceptible to K. pneumoniae infections. The infections caused by multidrug-resistant and hypervirulent K. pneumoniae strains are complicated to treat, illustrating an urgent need to develop novel and more practical approaches to combat the pathogen. We focused on the previously performed high-throughput analyses by other groups to discover several novel enzymes that may be considered attractive drug targets of K. pneumoniae. These targets qualify most of the selection criteria for drug targeting, including an absence of its homolog’s gene in the host. The capsule, lipopolysaccharide, fimbriae, siderophores and essential virulence factors facilitate the pathogen entry, infection and survival inside the host. This review discusses K. pneumoniae pathophysiology, including its virulence determinants and further the potential drug targets that might facilitate the discovery of novel drugs and effective treatment regimens shortly.
Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture
Authors: Wang Zhengfeng , Lei Xiujuan 
Published: August 2021

Abstract
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is considered to be an important pathway for circRNA function, such as acting as an oncogenic RBP sponge to inhibit cancer. In this study, we design a deep learning framework, CRPBsites, to predict the binding sites of RBPs on circRNAs. In this model, the sequences of variable-length binding sites are transformed into embedding vectors by word2vec model. Bidirectional LSTM is used to encode the embedding vectors of binding sites, and then they are fed into another LSTM decoder for decoding and classification tasks. To train and test the model, we construct four datasets that contain sequences of variable-length binding sites on circRNAs, and each set corresponds to an RBP, which is overexpressed in bladder cancer tissues. Experimental results on four datasets and comparison with other existing models show that CRPBsites has superior performance. Afterwards, we found that there were highly similar binding motifs in the four binding site datasets. Finally, we applied well-trained CRPBsites to identify the binding sites of IGF2BP1 on circCDYL, and the results proved the effectiveness of this method. In conclusion, CRPBsites is an effective prediction model for circRNA-RBP interaction site identification. We hope that CRPBsites can provide valuable guidance for experimental studies on the influence of circRNA on post-transcriptional regulation.
OpenPhi: an interface to access Philips iSyntax whole slide images for computational pathology
Authors: Mulliqi Nita , Kartasalo Kimmo , Olsson Henrik , Ji Xiaoyi , Egevad Lars , Eklund Martin , Ruusuvuori Pekka 
Published: August 2021

Abstract

Summary
Digital pathology enables applying computational methods, such as deep learning, in pathology for improved diagnostics and prognostics, but lack of interoperability between whole slide image formats of different scanner vendors is a challenge for algorithm developers. We present OpenPhi—Open PatHology Interface, an Application Programming Interface for seamless access to the iSyntax format used by the Philips Ultra Fast Scanner, the first digital pathology scanner approved by the United States Food and Drug Administration. OpenPhi is extensible and easily interfaced with existing vendor-neutral applications.

Availability and implementation
OpenPhi is implemented in Python and is available as open-source under the MIT license at: https://gitlab.com/BioimageInformaticsGroup/openphi. The Philips Software Development Kit is required and available at: https://www.openpathology.philips.com. OpenPhi version 1.1.1 is additionally provided as Supplementary Data.

Supplementary information
Supplementary data are available at Bioinformatics online.
Observing the Observers: How Participants Contribute Data to iNaturalist and Implications for Biodiversity Science
Authors: Di Cecco Grace J , Barve Vijay , Belitz Michael W , Stucky Brian J , Guralnick Robert P , Hurlbert Allen H 
Published: August 2021

Abstract
The availability of citizen science data has resulted in growing applications in biodiversity science. One widely used platform, iNaturalist, provides millions of digitally vouchered observations submitted by a global user base. These observation records include a date and a location but otherwise do not contain any information about the sampling process. As a result, sampling biases must be inferred from the data themselves. In the present article, we examine spatial and temporal biases in iNaturalist observations from the platform's launch in 2008 through the end of 2019. We also characterize user behavior on the platform in terms of individual activity level and taxonomic specialization. We found that, at the level of taxonomic class, the users typically specialized on a particular group, especially plants or insects, and rarely made observations of the same species twice. Biodiversity scientists should consider whether user behavior results in systematic biases in their analyses before using iNaturalist data.
Longitudinal strain is an independent predictor of survival and response to therapy in patients with systemic AL amyloidosis
Authors: Cohen Oliver C , Ismael Andreia , Pawarova Babita , Manwani Richa , Ravichandran Sriram , Law Steven , Foard Darren , Petrie Aviva , Ward Sevda , Douglas Brooke , Martinez-Naharro Ana , Chacko Liza , Quarta Candida Cristina , Mahmood Shameem , Sachchithanantham Sajitha , Lachmann Helen J , Hawkins Philip N , Gillmore Julian D , Fontana Marianna , Falk Rodney H , Whelan Carol J , Wechalekar Ashutosh D 
Published: August 2021

Abstract

Aims
Cardiac involvement, a major determinant of prognosis in AL (light-chain immunoglobulin) amyloidosis, is characterized by an impairment of longitudinal strain (LS%). We sought to evaluate the utility of LS% in a prospectively observed series of patients.

Methods and results
A total of 915 serial newly diagnosed AL patients with comprehensive baseline assessments, inclusive of echocardiography, were included. A total of 628/915 (68.6%) patients had cardiac involvement. The LS% worsened with advancing cardiac stage with mean −21.1%, −17.1%, −12.9%, and −12.1% for stages I, II, IIIa, and IIIb, respectively (P &lt; 0.0001). There was a highly significant worsening of overall survival (OS) with worsening LS% quartile: LS% ≤−16.2%: 80 months, −16.1% to −12.2%: 36 [95% confidence interval (CI) 20.9–51.1] months, −12.1% to −9.1%: 22 (95% CI 9.1–34.9) months, and ≥−9.0%: 5 (95% CI 3.2–6.8) months (P &lt; 0.0001). Improvement in LS% was seen at 12 months in patients achieving a haematological complete response (CR) (median improvement from −13.8% to −14.9% in those with CR and difference between involved and uninvolved light chain &lt;10 mg/L). Strain improvement was associated with improved OS (median not reached at 53 months vs. 72 months in patients without strain improvement, P = 0.007). Patients achieving an LS% improvement and a standard N-terminal pro-brain natriuretic peptide-based cardiac response survived longer than those achieving a biomarker-based cardiac response alone (P &lt; 0.0001).

Conclusion
Baseline LS% is a functional marker that correlates with worsening cardiac involvement and is predictive of survival. Baseline LS% and an absolute improvement in LS% are useful additional measures of prognosis and response to therapy in cardiac AL amyloidosis, respectively.
Global multi-environment resistance QTL for foliar late blight resistance in tetraploid potato with tropical adaptation
Authors: Lindqvist-Kreuze Hannele , De Boeck Bert , Unger Paula , Gemenet Dorcus , Li Xianping , Pan Zhechao , Sui Qinjun , Qin Junhong , Woldegjorgis Gebremedhin , Negash Kassaye , Seid Ibrahim , Hirut Betaw , Gastelo Manuel , De Vega Jose , Bonierbale Merideth 
Published: August 2021

Abstract
The identification of environmentally stable and globally predictable resistance to potato late blight is challenged by the clonal and polyploid nature of the crop and the rapid evolution of the pathogen. A diversity panel of tetraploid potato germplasm bred for multiple resistance and quality traits was genotyped by genotyping by sequencing (GBS) and evaluated for late blight resistance in three countries where the International Potato Center (CIP) has established breeding work. Health-indexed, in vitro plants of 380 clones and varieties were distributed from CIP headquarters and tuber seed was produced centrally in Peru, China, and Ethiopia. Phenotypes were recorded following field exposure to local isolates of Phytophthora infestans. QTL explaining resistance in four experiments conducted across the three countries were identified in chromosome IX, and environment-specific QTL were found in chromosomes III, V, and X. Different genetic models were evaluated for prediction ability to identify best performing germplasm in each and all environments. The best prediction ability (0.868) was identified with the genomic best linear unbiased predictors (GBLUPs) when using the diploid marker data and QTL-linked markers as fixed effects. Genotypes with high levels of resistance in all environments were identified from the B3, LBHT, and B3-LTVR populations. The results show that many of the advanced clones bred in Peru for high levels of late blight resistance maintain their resistance in Ethiopia and China, suggesting that the centralized selection strategy has been largely successful.
Genome assembly of two nematode-resistant cotton lines (Gossypium hirsutum L.)
Authors: Perkin Lindsey C , Bell Al , Hinze Lori L , Suh Charles P -C , Arick Mark A , Peterson Daniel G , Udall Joshua A 
Published: August 2021

Abstract
Upland cotton (Gossypium hirsutum L.) is susceptible to damage by the root-knot and the reniform nematodes, causing yield losses greater than 4% annually in the United States. In addition, these nematodes are synergistic with seeding disease and root rot pathogens that exacerbate diseases and subsequent yield losses. Production practices to minimize nematode damage include crop rotation and nematicides, but these techniques need to be repeated and are expensive. The use of resistant cultivars is deemed the most effective and economical approach for managing nematodes in cotton. Here, we describe the genomes of two nematode-resistant lines of cotton, BARBREN-713 and BAR 32-30. These genomes may expedite the development of DNA markers that can be used to efficiently introduce nematode resistance into commercially valuable Upland lines.
High-quality genome assembly of the soybean fungal pathogen Cercospora kikuchii
Authors: Kashiwa Takeshi , Suzuki Tomohiro 
Published: August 2021

Abstract
Plant diseases caused by the Cercospora genus of ascomycete fungi are a major concern for commercial agricultural practices. Several Cercospora species can affect soybeans, such as Cercospora kikuchii which causes soybean leaf blight. Speciation in Cercospora on soybean has not been adequately studied. Some cryptic groups of Cercospora also cause diseases on soybean. Moreover, it has been known C. kikuchii population genetic structure is different between countries. Consequently, further genomic information could help to elucidate the covert differentiation of Cercospora diseases in soybean. Here, we report for the first time, a chromosome-level genome assembly for C. kikuchii. The genome assembly of 9 contigs was 34.44 Mb and the N50 was 4.19 Mb. Based on ab initio gene prediction, several candidates for pathogenicity-related genes, including 242 genes for putative effectors, 55 secondary metabolite gene clusters, and 399 carbohydrate-active enzyme genes were identified. The genome sequence and the features described in this study provide a solid foundation for comparative and evolutionary genomic analysis for Cercospora species that cause soybean diseases worldwide.
The “Bipartite” Structure of the First Genome of Ampelomyces quisqualis, a Common Hyperparasite and Biocontrol Agent of Powdery Mildews, May Point to Its Evolutionary Origin from Plant Pathogenic Fungi
Authors: Huth Lauren , Ash Gavin J , Idnurm Alexander , Kiss Levente , Vaghefi Niloofar 
Published: August 2021

Abstract
Powdery mildews are among the most important plant pathogens worldwide, which are often attacked in the field by mycoparasitic fungi belonging to the genus Ampelomyces. The taxonomy of the genus Ampelomyces is unresolved, but well-supported molecular operational taxonomic units were repeatedly defined suggesting that the genus may include at least four to seven species. Some Ampelomyces strains were commercialized as biocontrol agents of crop pathogenic powdery mildews. However, the genomic mechanisms underlying their mycoparasitism are still poorly understood. To date, the draft genome of a single Ampelomyces strain, designated as HMLAC 05119, has been released. We report a high-quality, annotated hybrid draft genome assembly of A. quisqualis strain BRIP 72107, which, based on phylogenetic analyses, is not conspecific with HMLAC 05119. The constructed genome is 40.38 Mb in size, consisting of 24 scaffolds with an N50 of 2.99 Mb and 96.2% completeness. Our analyses revealed “bipartite” structure of Ampelomyces genomes, where GC-balanced genomic regions are interspersed by longer or shorter stretches of AT-rich regions. This is also a hallmark of many plant pathogenic fungi and provides further evidence for evolutionary affinity of Ampelomyces species to plant pathogenic fungi. The high-quality genome and annotation produced here provide an important resource for future genomic studies of mycoparasitisim to decipher molecular mechanisms underlying biocontrol processes and natural tritrophic interactions.