bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deriving tropical cyclone associated flood hazard information using clustered GPM-IMERG rainfall signatures: a case study in Dominica
Authors: Nabukulu Catherine , Jetten Victor. G. , Ettema Janneke , Bout Bastian van den , Haarsma Reindert. J. 
Published: September 2022

Abstract

Different stakeholders are now looking for methods suitable for communicating the potential impacts of tropical cyclone (TC) associated rainfall and the subsequent flood hazard. We developed a new solution that utilizes GPM-IMERG satellite precipitation estimates to characterize TC rainfall spatial-temporal patterns and derives precipitation curves appropriate for TC-related flood hazard assessment. The method was demonstrated when modeling floods on Dominica due to the rainfall of Tropical Storm Erika in 2015. We performed three experiments on the procedure, starting with a time-series clustering analysis using the K-means algorithm for optimal clusters K = 5, 4, and 3. For each experiment, we excluded pixels associated with very low precipitation intensities and amounts likely disparate from the TC. We then introduced an intensity threshold of 10mm/hr to define the onset of the storm’s rain and align the pixel time series before deriving cluster representative precipitation signals (RPS) based on time step quantiles. The RPSs were used as precipitation inputs for the openLISEM, an event-based hydrological model, to simulate the resultant flood characteristics. RPSs from K = 4 were selected as Tropical Storm Erika’s final rainfall scenarios, which resulted in different flood scenarios. These results demonstrate the underlying variability in the rainfall of a single TC which should be accounted for to achieve a reliable flood hazard assessment.
The influence of the host sex on infection intensities of parasite lineages belonging to Haemoproteus majoris in a natural bird community
Authors: Berkel Caglar , Cacan Ercan 
Published: September 2022

Abstract
Immunological capability shows a sexual dimorphism in diverse animal species. Females are generally more immunocompetent than males, leading to the higher susceptibility of males to infection compared to females and thus greater infection-related pathology in males. This sex-differences in immunity remains to be understudied in birds. Here, we compared the infection intensities of three different parasite lineages belonging to the morphological species Haemoproteus majoris (namely PARUS1, PHSIB1 and WW2), a widespread blood parasite of birds, in terms of sex in birds species living in a natural community. We found that infection intensity by WW2 lineage, but not by other two lineages of H. majoris, is higher in male birds compared to female birds. Similarly, we showed that total infection intensities of these three H. majoris lineages (PARUS1 (%) + PHSIB1 (%) + WW2 (%)) are higher in male birds compared to female birds. Our study points that male birds at the community level may be more susceptible to infection by certain parasites than female birds. We propose that sexual dimorphism in infection intensities by certain parasites in host birds might be more common than previously thought, similar to that observed in other species, influencing host population dynamics in a sex-specific manner. Therefore, it can be speculated that infection by certain parasites might differentially effect male and female birds, possibly resulting in a bias in survival rates between sexes due to infections, in certain contexts.
The Value Evaluation Model Design and Business Innovation for P-RAN based on Multi-Party Interaction
Authors: Meng Fanrong , Liu Hua , Li Weimin , Chen Xin 
Published: September 2022

Abstract
This paper takes the P-RAN, a proximity wireless access network system for 5G and 6G, as an example, and uses the theory related to value evaluation to discuss how to realize the decentralization of underlying infrastructure from the perspective of different interactive players in the system. The analysis of P-RAN helps to promote mobile network operators to recognize network interaction and solve the problems of weak coverage, reduce the cost of network construction, and provides a new research idea for exploring more network evaluation indicators in the future.
Effects of invasive plant diversity on soil microbial communities
Authors: Wang Xiao-Yan , Wang Xue , Wang Wei , Wang Jiang , Yu Fei-Hai 
Published: September 2022

Abstract
Native plant communities can be invaded by different numbers of alien plant species or by the same number of alien plant species with different levels of evenness. However, little is known about how alien invasive plant species richness and evenness affect soil microbial communities. We constructed native herbaceous plant communities invaded by exotic plants with different richness (1, 2, 4 and 8-species) and evenness (high and low) and analyzed soil physico-chemical properties and the diversity and composition of soil fungal and bacterial communities. Overall, species richness and evenness of invasive plants had no significant effect on bacterial and fungal alpha diversity (OTUs, Shannon, Simpson, Chao1 and ACE) and soil physico-chemical properties. However, invasive species richness had a significant impact on the relative abundance of the most dominant fungi Ascomycota and Bipolaris , and the dominant bacteria Actinobacteriota, which increased with increasing invasive species richness. The relative abundance of the dominant microbial groups was significantly correlated with the relative abundance of some specific invasive plant species in the community. This study sheds new light on the effects of plant co-invasion on soil microbial communities, which may help understand the underlying mechanisms of multiple alien plant invasion processes from the perspective of soil microorganisms.
Genome-Wide Association Analysis Identifies Resistance Loci for Bacterial Blight in Diverse East African Rice Germplasm
Authors: Okello Moses , Ochwo Mildred , Lamo Jimmy , Onaga Geoffrey , Odong Thomas L , Geoffrey Tusiime , Tukamuhabwa Phinehas , Mukasa Settumba B , Peter Wasswa , Ogwal Jonathan , Oliva Ricardo 
Published: September 2022

Abstract
Background
Xanthomonas oryzae pv. Oryzae (Xoo), the causal agent of rice bacterial blight disease has been extensively characterized and loci against different races identified. Many rice cultivars have been developed and utilized to combat the disease, however due to rapid evolution of Xoo, a number of resistances have broken-down. The continuous challenge of ever evolving Xoo and breakdown of resistance in cultivated rice varieties makes it even more important to discover new loci to enable sustainable durable deployment of broad-spectrum resistance genes in elite breeding lines. African germplasm can be exploited as reservoirs of useful genetic variation for bacterial blight (BB) resistance. This study was conducted to identify loci associated to BB resistance and new genetic donors for breeding program.
Results
To identify candidate sources of resistance for advancing breeding, we used highly four virulent strains of Xoo (PXO99, MAI1, BAI3 and Xoo3-1) to screen 78 East African accessions by genome-wide association studies. The core genetic base of the diverse accessions exhibited high degree of resistance to the Xoo strains. 50.63% of the accessions were highly resistant to the Philippines strain PX099, while 20.25% were highly susceptible to the virulent West African strain MAI1. Two novel resistant loci significantly associated hotspots were identified using 1901 SNPs. The two hits were located on chromosome 12 (Xa25) and Chr. 6 (Xa7, Xa27, Xa33).
Conclusions
Our finding have identified novel loci that gives a useful basis for more investigation and a wide core genetic pool of high resistance for broad-spectrum resistance genetic improvement.
An endogenous lentivirus in the germline of a rodent
Authors: Kambol Roziah , Gatseva Anna , Gifford Robert J. 
Published: September 2022

Abstract
Lentiviruses (genus Lentivirus) are complex retroviruses that infect a broad range of mammals, including humans. Unlike many other retrovirus genera, lentiviruses have only rarely been incorporated into the mammalian germline. However, a small number of endogenous retrovirus (ERV) lineages have been identified, and these rare genomic “fossils” can provide crucial insights into the long-term history of lentivirus evolution. Here, we describe a previously unreported endogenous lentivirus lineage in the genome of the South African springhare (Pedetes capensis), demonstrating that the host range of lentiviruses has historically extended to rodents (order Rodentia). Furthermore, through comparative and phylogenetic analysis of lentivirus and ERV genomes, considering the biogeographic and ecological characteristics of host species, we reveal broader insights into the long-term evolutionary history of the genus.
Rail induced lateral migration of particles across intact co-flowing liquids
Authors: Ziemecka Iwona , Hemptinne Amaury , Misko Vyacheslav R. , Briet Matthieu , Gelin Pierre , Bihi Ilyesse , Maes Dominique , De Malsche Wim 
Published: September 2022

Abstract
This paper presents a rail guided method to apply Layer-by-Layer (LbL) coating on particles in a microfluidic device. The passive, microfluidic approach allows handling suspensions of particles to be coated in the system. The trajectory of the particles is controlled using engraved rails, inducing lateral movement of particles while keeping the axially oriented liquid flow (and the interface of different liquids) undisturbed. The depth and angle of the rails together with the liquid velocity were studied to determine a workable geometry of the device. A discontinuous LbL coating procedure was converted into one continuous process, demonstrating that the chip can perform seven consecutive steps normally conducted in batch operation, further easily extendable to larger cycle numbers. Coating of the particles with two bilayers was confirmed by fluorescent microscopy.
Total protein of Candida species inhibits human cervical cancer HeLa cells proliferation by down-regulating octamer binding transcription factor 4B
Authors: Kokhdan Esmaeel Panahi , Ataeyan Mohammad Hasan , Rameyan Payman , Alizadeh Fahimeh , Khodavandi Alireza 
Published: September 2022

Abstract
Cervical cancer is the fourth most common cause of cancer-related death among women globally. Microbial products represent an available source of anticancer drugs. Thus, this study aimed to extract the total protein from Candidaspecies (CanSp) and subsequently investigate its inhibitory effects against human cervical cancer HeLa cells. This study reports the five total protein of the yeast-to-hyphal transition culture of Candida species, which were then evaluated for their inhibitory potential by cell viability, cell apoptosis and nitrite assays against HeLa cells. Furthermore, transcriptional profile of OCT4B gene was determined using quantitative reverse transcription PCR. Total protein of CanSp1-5 were obtained from Candida species. The result of the protein quantitation assay indicated that the CanSp1-5 exhibited total protein values from 93.72 to 155.25 µg/mL and 89.88 to 144.33 µg/mL by Bradford and micro-Kjeldahl methods, respectively. The CanSp1 was most active with a half-maximal inhibitory concentration of 157.11 ± 0.001 μg/mL and half-maximal effective concentration of 102 ± 0.001 μg/mL. The distinct morphological changes of cells were showed a typical apoptosis. Moreover, a reduction in the nitric oxide concentration was observed in the HeLa cells. The expression level of OCT4B gene was significantly down regulated in the HeLa cells treated with CanSp1-5. These findings highlight the importance of investigating microbial products for the accelerated development new anticancer drugs. In addition, OCT4B gene could be probable molecular target of the CanSp1-5 in the HeLa cells.
Analysis of protein-protein interaction and weighted co-expression networks revealed key modules and genes in multiple tissues of Agave sisalana
Authors: de Carvalho Lucas Miguel , Silva Nicholas Vinícius , de Abreu Luís Guilherme F. , Marone Marina Püpke , Cardelli Alexandra Russolo , Raya Fabio Trigo , Araújo Guido , Carazzolle Marcelo Falsarella , Pereira Gonçalo Amarante Guimarães 
Published: September 2022

Abstract

Agave plants are well-known for their drought resilience and commercial applications. Among them, Agave sisalana (sisal) is the species most used to produce hard fibers, and it is of great importance for semiarid regions. Agaves also show potential as bioenergy feedstocks, as they can accumulate large amounts of biomass and fermentable sugar. This study aimed to reconstruct the A. sisalana interactome, and identify key genes and modules involved in multiple plant tissues (root, stem, and leaf) through RNA-Seq analysis. We integrated A. sisalana transcriptome sequences and gene expression generated from stem, leaf, and root tissues to build global and conditional co-expression networks across the entire transcriptome. By combining the co-expression network, module classification, and function enrichment tools, we identified 20 functional modules related to at least one A. sisalana tissue, covering functions such as photosynthesis, leaf formation, auxin-activated signaling pathway, floral organ abscission, response to farnesol, brassinosteroid mediated signaling pathway, and light-harvesting. The final interactome of A. sisalana contains 2,582 nodes and 15,083 edges. In the reconstructed interactome, we identified submodules related to plant processes to validate the reconstruction. In addition, we identified 6 hub genes that were searched for in the co-expression modules. The intersection of hub genes identified by both the protein-protein interaction networks (PPI networks) and co-expression analyses using gene significance and module membership revealed six potential candidate genes for key genes. In conclusion, we identified six potential key genes for specific studies in Agave transcriptome atlas studies, biological processes related to plant survival in unfavorable environments, and provide strategies for breeding programs.
Simulated slide tracheoplasty for congenital tracheal stenosis using three-dimensional printed models
Authors: Shimojima Naoki , Shimotakahara Akihiro , Tomita Hirofumi , Maeda Yutaro , Ito Yoshifumi , Miyaguni Kazuaki , Tsukizaki Ayano , Abe Kiyotomo , Hashimoto Makoto , Ishikawa Miki , Honda Masaki , Hirobe Seiichi 
Published: September 2022

Abstract
Purpose: The slide tracheoplasty (STP) is the standard treatment for severe congenital tracheal stenosis (CTS). Understanding the features of the tracheal stenosis in each case and choosing an appropriate incision design are very important for successfully executing the procedure. The present study aimed to evaluate the advantages of three-dimensional (3D) printed models of the trachea for improving CTS.
Methods: Three-D tracheal models were created using computed tomography (CT) data from ten patients undergoing STP for CTS. Simulated surgery was performed using the hollow models after reinforcing with them with a coating of gum spray. Clinical outcomes, including patient survival, postoperative surgical interventions, and time required for STP, were compared with the corresponding values in the last ten patients before the introduction of 3D model simulations.
Results: All ten patients for whom simulated surgery using a 3D tracheal model were conducted achieved good airway patency after their STP. The surgeons reported feeling that the 3D model simulations were highly effective although there was no significant difference in the clinical outcomes of the groups with or without simulated STP. The models were useful not only for surgical planning but also for sharing important information among the multidisciplinary team and the patients’ family.
Conclusion: Our experience using 3D tracheal models demonstrated several features enabling improvement in the surgical treatment of CTS.
The diel vertical distribution and carbon biomass of the zooplankton community in the Caroline Seamount area of the western tropical Pacific Ocean
Authors: Tao Zhencheng , Xian Haochen , Luan Zhendong , Nan Feng , Wang Yanqing , Sun Song 
Published: September 2022

Abstract
Zooplankton can affect and regulate the biological carbon pump in the biogeochemical cycles of marine ecosystems through diel vertical migration (DVM) behaviour. The diel vertical distribution and migration of a zooplankton community were studied at a continuous survey station in the Caroline Seamount area of the western tropical Pacific Ocean. Using a MultiNet sampling system, 346 zooplankton species/taxa were collected and identified. The vertical distribution patterns of abundance and composition of the zooplankton community differed between daytime and nighttime. The highest biodiversity index occurred in the 100–200-m ocean depth layer, but some zooplankton species remained in the deep-water layer below 300 m. The DVM patterns of the various dominant species differed, even when the species belonged to the same order or family. Dissolved oxygen and seawater temperature were the main environmental factors affecting the diel vertical distribution of the zooplankton community. The oxygen minimum zone was identified as performing the dual role of “ecological barrier” and “refuge” for zooplankton. The active carbon flux mediated by the zooplankton DVM in the Caroline Seamount area was 14.5 mg C/(m2·d). Our findings suggest that zooplankton DVM can affect and mediate the biological carbon pump in the Caroline Seamount area.
Efficacy of Drought-tolerant and Insect-protected Transgenic TELA® Maize Traits in Nigeria
Authors: Oyekunle M. , Adamu R. S. , Ndou E. , Beyene Y. , Abdulmalik M. M. , Oikeh S. O. 
Published: September 2022

Abstract
Assessment of efficacy of drought tolerance (DT) and insect protection (Bt) genes in maize genotypes is invaluable for commercialization and production of transgenic maize in Nigeria. Seven maize hybrids, known as TELA® maize, with stacked events of Bt insect protection (MON89034) and drought tolerance (MON87460; DroughtGard®) and their respective non-GM versions (isohybrids) developed through the TELA Maize Project were evaluated in confined field trial site at Zaria in 2020 and 2021. The objective was to assess the efficacy of stacked DT and Bt genes to seek deregulation and commercialization of both traits in Nigeria. Significant (P < 0.05–0.01) differences were observed among genotypes (G), environments (E) and genotype × environment interaction (GEI) for grain yield and most other traits under stem borer and fall armyworm infested, drought stress, and optimum-moisture conditions, except E and GEI under drought. TELA® GM hybrids with Bt MON89034 gave 19% higher yield than their non-GM isogenic versions, and 40% higher yield than the commercial checks under the target pests infestation. The foliar damage score of all the TELA® GM genotypes was ≤ 2 relative to their non-GM isogenic versions which scored ≥ 4, indicating the effectiveness of the Bt MON89034 gene in conferring resistance against stem borer and fall armyworm. Under moderate drought, pairwise comparison showed TELA® GM Hybrid 1–1 and Hybrid 2 − 1 gave 12.4–20.4% higher (P < 0.01) yield than their isogenic versions. Under optimum-moisture condition with pests’ control, the TELA® GM and their isogenic hybrids were similar, but both had 32% higher yield than the commercial checks. Adoption of TELA® GM technology by farmers as adaptation strategy to cope with climate-change, will ensure sustainability of maize production and productivity in Nigeria.
Modified Symbiotic Organism Search (mSOS) for Inversion Time-Domain Electromagnetic Data
Authors: Widodo Widodo , Zamani Muhammad Rezha , Patimah Sindi Hajah , Agustiana Elis 
Published: September 2022

Abstract
One of the most common ways to model central-loop configuration Time-Domain Electromagnetic (TDEM) data is using 1D inversion model. The Born Approximation method used for this study to accommodate problem in calculations and speed of convergence when calculated the TDEM response, meanwhile for inversion modelling of TDEM observation data modified Symbiotic Organism Search (mSOS) was chose, which is one of the global optimization algorithms to accommodate multi-minimum problem ​​in non-linear objective functions, so the optimal global solution is obtained. Inversion modeling was carried out on synthetic and field data to test accuracy in inversion, the accuracy of synthetic data tested based on the capability of the algorithm to retrieve value of synthetic data indicated by small relative error value between synthetic model parameters and calculated model, while for modeling of field data, the accuracy of modeling was depending on consistency when the data was modeling with different number of layer, in addition time to perform inversion are considered evaluate inversion performance. In synthetic data case, the algorithm produced a relatively good model based on the accuracy of the model in terms of misfit values which has a misfit value round about 0%, relative error values, while for field data case the inversion model attain consistency and experienced lessen misfit value when the data was modeled using different number of layer specifically 8.72% for 2-layers model, 3.92% for 3-layers model, and 2.61% for 4- and 5- layers model. According to both data required under 19 minutes for 10.000 iterations.
Spatial and Temporal Deep Learning in Air-coupled Ultrasonic Testing for Enabling NDE 4.0
Authors: Schmid Simon , Dürrmeier Florian , Grosse Christian 
Published: September 2022

Abstract
Air-coupled ultrasonic (ACU) testing has been used for several years to detect defects in plate-like structures. Especially, for automated testing procedures, ACU testing is advantageous in comparison to conventional testing. However, the evaluation of the measurement data is usually done in a manual manner, which is an obstruction to the application of ACU testing. The goal of this study is to automate and improve defect characterization and NDE 4.0 accordingly with deep learning. In conventional ACU testing the measurement data contains temporal (A-scans) and spatial (C-scans) information. Both data types are investigated in this study. For the A-scans, which represent time series data, neural networkarchitectures tailored to such data types are applied. In addition, it is evaluated if further adaptions of the training procedure increase the performance. The C-scans are segmented by applying differentU-net similar architectures and training strategies. In order to use spatial and temporal information, a further approach is taken. The prediction of the time series models is segmented with imagemodels. To the performance of all trained models and training strategies is compared with the F1-score. As specimens, artificial defects in acrylic and carbon fiber-reinforced polymers plates are investigated.