bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nano-priming of Phaseolus vulgaris OTI cultivar with cobalt ferrite nanoparticles enhances the mineral composition of progeny seeds
Authors: Perea-Vélez Yazmín Stefani , Carrillo-González Rogelio , González-Chávez Ma. Carmen A. , Vangronsveld Jaco , Tapia-Maruri Daniel , López-Luna Jaime 
Published: July 2024

Abstract

Nano-priming is an emerging application of nanotechnology in agriculture intending to increase crop yield and nutritional quality, while reducing fertilizer applications. This study aimed to investigate the effects of seed priming with citrate-coated CoFe2O4 nanoparticles (NPs) suspensions (10, 20, and 40 mg NPs L− 1) on the life cycle of the Phaseolus vulgaris L. OTI cultivar and evaluate the technology costs. The effect of nano-priming was assessed in the germination, flowering, and harvest stages. Unprimed and hydro-primed seeds were negative and positive controls, respectively. Nano-priming with CoFe2O4 NPs had no effect neither on the germination nor on plant nutrition (in the flowering stage) of OTI beans compared to unprimed and hydro-primed seeds. In contrast, nitrogenase activity (343.3 ± 1.1 µmol h− 1 plant− 1 of C2H4 ) was detected in the plants from the 40 mg kg− 1 nano-primed seeds. The K concentration of progeny seeds from nano-priming with 10, 20, and 40 mg NPs L− 1 increased significantly by 3%, 16%, and 13% compared to the control seeds. The Zn concentration in the seeds from nano-priming with 10 mg NPs L− 1 was 27% higher than in the control and 28% higher than in the hydro-primed seeds. When nano-priming with 40 mg NPs L− 1, the Zn concentration was 5% and 6% higher than the control and hydro-primed seeds. The calculated cost of nano-priming seeds per ha ranged from 121 to 143 USD. In this regard, nano-priming of bean seeds with citrate-coated CoFe2O4 NPs could be a low-cost approach to achieve nutritional security and agricultural sustainability.
Enhancing prediction accuracy and data handling for environmental applications in innovative modeling of underground water level fluctuations based on tree ensembles technique
Authors: Chi Duong Thi Kim , Thiem Do Dac , Quynh Trinh Thi Nhu , Nguyen Thanh Q. 
Published: July 2024

Abstract

This study developed a model to evaluate and predict underground water level fluctuations based on various factors that affect water reserves. The process of calculating input data features was performed to improve forecast quality. The paper emphasizes the automatic handling of missing and noisy data before incorporating them into the training dataset. Subsequently, the Tree Ensembles learning method was applied to construct the underground water level prediction model. The results indicate that the model can accurately predict the trend of changes in water level in water storage areas such as aquifers and lakes. In particular, this method demonstrated flexibility in handling various input variables, including erroneous, missing, and noisy data, without requiring overly complex preprocessing. This opens up the potential for applying underground water level prediction models in real-world scenarios, where data is often highly diverse and complex. In conclusion, this study not only provides an effective method to predict fluctuations in the level of underground water at storage points, but also suggests significant potential for the development of evaluation and prediction models in the environmental field in the future.
Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles
Authors: Reingold Victoria , Faigenboim Adi , Matveev Sabina , Haviv Sabrina , Belausov Eduard , Vilcinskas Andreas , Ment Dana 
Published: July 2024

Abstract

Background
The fungus Metarhizium brunneum has evolved a remarkable ability to switch between different lifestyles. It develops as a saprophyte, an endophyte establishing mutualistic relationships with plants, or a parasite, enabling its use for the control of insect pests such as the aphid Myzus persicae. We tested our hypothesis that switches between lifestyles must be accompanied by fundamental transcriptional reprogramming, reflecting adaptations to different environmental settings.
Results
We combined high throughput RNA sequencing of M. brunneum in vitro and at different stages of pathogenesis to validate the modulation of genes in the fungus and its host during early infection. In agreement with our hypothesis, we observed transcriptional reprogramming in M. brunneum following conidial attachment, germination on the cuticle, and early-stage growth within the host. This involved the upregulation of genes encoding degrading enzymes and gene clusters involved in synthesis of secondary metabolites that act as virulence factors. The transcriptional response of the aphid host included the upregulation of genes potentially involved in antifungal activity, but antifungal peptides were not induced. We also observed the induction of a host flightin gene, which may be involved in wing formation and flight muscle development.
Conclusions
The switch from saprophytic to parasitic development in M. brunneum is accompanied by fundamental transcriptional reprogramming during the early phases of infection. The aphid host responds to fungal infection with its own transcriptional reprogramming, reflecting its inability to express antifungal peptides but featuring the induction of genes involved in winged morphs that may enable offspring to avoid the contaminated environment.
Ternary RGO/PANI/UCNT nanohybrid for high performance electrochemical supercapacitors
Authors: Soleimani Amirhosein , Taleghani Hamidreza Ghafouri , Lashkenari Mohammad Soleimani 
Published: July 2024

Abstract

In this work, Ternary reduced graphene oxide/ polyaniline/unzipped carbon nanotube nanocomposite namely RGO/PANI/UCNT was prepared for supercapacitor applications. To confirm the synthesis of nanocomposites, the prepared materials were examined by different analytical methods such as FT-IR, XRD, FE-SEM and BET. Results shows that exist a porous and layered structure of RGO, and proper distribution of UCNT into nanocomposite with unzipping. Also, RGO/PANI/UCNT have an active surface area of 84.70 m2 g− 1. Electrochemical properties of the nanocomposite were investigated through cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and impedance spectroscopy (EIS) tests. Results of the GCD test revealed a capacity of 640 F g− 1 at a current density of 1 A g− 1, which is higher than that of other electrodes. Furthermore, the synthesized nanocomposite displays excellent stability by maintaining 85% of its initial capacity after 1000 charge-discharge cycles. The results indicated that unzipping of carbon nanotubes leads to increased surface area and improved conductivity, contributing to the enhanced capacitance. This underscores the pivotal role of UCNT in optimizing the energy storage capacity of the nanocomposite, further affirming its potential as a promising electrode material for advanced energy storage devices.
Enhanced by Visual and Semantic Consistency for Continuous Sign Language Recognition
Authors: Xiong Sije , Zou Chunlong , Yun Juntong , Jiang Du , Huang Li , Liu Ying , Li Gongfa , Xie Yuanmin 
Published: July 2024

Abstract

Camera-based interface enables simple human-computer interaction with intuitive sign language for hearing-impaired users. Sign language, as a visual language, utilizes changes in hand shape, body movements, and facial expressions to collaboratively convey information. Most of the current continuous sign language recognition (CSLR) models focus their attention on the extraction of information from each frame of the image and ignore the dynamically changing characteristics of the signer across multiple frames. The contrasts with the essence of sign language recognition: which aims to learn the most essential feature representations of changes in the hand-controlled part and the non-hand-controlled part, and convert them into language. In this paper, we first use the feature alignment method to explicitly capture the spatial position offset and motion direction information between neighboring frames, direct a dynamic attention mechanism to focus on the subtle change region, enhance visual representation extraction. And we propose a dynamic decoding method based on maximum backtracking probability to decode word-level features and achieve word consistency constraints without increasing computational resources, enhance semantic consistency. We propose a comprehensive CSLR model utilizing a Dynamic Attention Mechanism and Maximum Backtracking Probability Dynamic Decoding (DAM-MCD), enhancing the model's inference capability and robustness. Experiments were conducted on two publicly accessible datasets, PHOENIX14 (Koller et al. Comput Vis Image Underst 141:108–125, 2015), PHOENIX14-T (Camgoz et al., in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7784–7793, 2018), demonstrating that the DAM-MCD model achieves higher accuracy compared to methods employing multi-cue input. The results further show that the DAM-MCD model effectively captures sign language motion information in videos. Models will be made public on: https://github.com/smellno/Continuous-Sign-Language-Recognition-.
Co-producing and co-assessing a new service solution for enhancing health and social care integration: a participatory research protocol
Authors: Gheduzzi Eleonora , Savarese Mariarosaria , Mangini Alberto , Mitidieri Silvia , Paleologo Michele , Masella Cristina , Graffigna Guendalina 
Published: July 2024

Abstract

Background This paper describes a study protocol for co-producing and co-assessing a new sustainable and scalable service solution that enhances health and social integration by involving providers and volunteers delivering services for elderly people in the province of Cremona (Italy), where the elderly population will reach 27% in 2023.Methods This upcoming study involves mixed-method participatory research and is structured in three study phases and related objectives. First, it will co-produce a new, accessible and sustainable service solution using an iterative design and management method, Plan-Do-Check-Act by involving professionals and volunteers of a heterogeneous group of health, social and third sector organizations located in the city of Cremona (Italy). Second, the study protocol will co-assess the outcomes of the new service solution using a mixed-method approach for measuring the outcomes on: professionals and volunteers (micro level) and their health, social and third sector organizations (meso level). Third, this study will co-investigate the scalability of the new solution promoting health and social integration in other similar urban areas of the Province of Cremona via the Intervention Scalability Assessment Tool (macro level). The data will be collected through the analysis of official documents, websites, policies and participatory workshops.Discussion This protocol proposes an innovative intervention, a novel participatory approach, and an unexplored scalability assessment tool in the context of health and social care integration. This study aims to support professionals from health and social care service providers and volunteers from third-sector organizations to collaborate and integrate each other’s resources. In doing so, the participatory approach will facilitate the co-creation of an effective response to the need of health and social integration, and the development of trustful relationships between health and social care service providers. Moreover, the adoption of Plan-Do-Check-Act and Intervention Scalability Assessment Tool will ensure the quality, scalability and sustainability of the new service solution in other settings.
A Modified Genetic-Based solution for Power-Aware Placement of Virtual Machines
Authors: Panwar Suraj Singh , Rauthan M. M.S. , Barthwal Varun 
Published: July 2024

Abstract

Cloud computing has developed as a ubiquitous technology for delivering services like storage, computing, etc. via the Internet. With the rising demand by customers for cloud computation and associated services, cloud service providers are developing various approaches that enhance the performance, reliability, and availability of cloud systems. Cloud computing uses virtualization to optimise resource usage and minimise power utilisation in data centers (DC). Efficient virtual machine (VM) placement strategies are crucial, especially when using advanced genetic techniques. This research paper introduces the use of a genetic meta-heuristic approach, named PowerGA, to optimise the integration of virtual machines (VM) onto the least number of physical machines (PMs) in cloud DCs. PowerGA optimises VM deployment in cloud DCs to minimise energy utilisation and Service Level Agreement (SLA) breaches, considering factors such as VM migration, host shutdown, overload count, and active physical machines. Extensive simulations using real workload data showed significant improvements over traditional strategies like PABFD, with PowerGA achieving a 25% reduction in energy consumption (EC), 43% fewer VM migrations, a 58% improvement in SLA violations, and a 72% reduction in host shutdowns over ten days of data from PlanetLab. These results highlight PowerGA's effectiveness in energy management and SLA enhancement, demonstrating the benefits of a meta-heuristic genetic algorithm in optimising VM placement for cloud computing efficiency.
Influence of Helical Spring Diameter on the Mechanical Response of Spiral Reinforcement Columns: A Finite Element Analysis
Authors: Karmaker Rajib , Deb Ujjwal Kumar 
Published: July 2024

Abstract

This research examines the behavior of Spiral Reinforcement Columns (SRCs), an innovative structural system consisting of concrete-filled steel tubes augmented with spiral springs, under diverse loading scenarios. Utilizing Finite Element Analysis (FEA), the study evaluates the impact of varying spiral spring diameters on the SRCs' performance. The findings reveal that springs with an 84 mm diameter significantly improve suspension efficiency over those with diameters of 64 mm and 80 mm. Springs with larger diameters demonstrate enhanced resistance to deformation, diminished bending, and lower stress levels. As a result, SRCs equipped with larger diameter springs exhibit superior stiffness, strength, ductility, and energy absorption capabilities compared to their counterparts with smaller diameters. The outcomes support the potential of SRCs with spiral springs as an effective seismic-resistant structural alternative.
Effects of Yacon (Smallanthus sonchifolius) Syrup on the Glycemic Metabolism, and Intestinal Microbiota of Rats on a High-Fat Diet
Authors: Andrade Bruna Kelly Medeiros , Danziato-Neto Milton Alves , de Oliveira Ariclécio Cunha , de Freitas Paula Alexandre , Melo Vânia Maria Maciel , Quintela Bárbara Cibelle Soares Farias , Oliveira Francisca Andréa Silva , Monteiro-Moreira Ana Cristina Oliveira , Dionísio Ana Paula , Adriano Lia Silveira , Costa Matheus Augusto Ferreira , Almeida Izaak Ferreira , Carioca Antonio Augusto Ferreira 
Published: July 2024

Abstract

High-fat diets adversely affect both glycemic control and the composition of the intestinal microbiota. Yacon syrup, which is rich in fructooligosaccharides (FOS) and antioxidants, offers a promising nutritional solution. This study aimed to investigate the impact of Yacon syrup consumption on the intestinal microbiota profile, body weight, food consumption, and glycemic control in rats exposed to a high-fat diet (HFD). Our experimental design involved placing the animals into four distinct groups:1. Rats maintained on a standard diet throughout the experimental protocol, 2. Rats consistently fed a high-fat diet, 3. Rats exposed to an initial phase of HFD followed by HFD supplemented with 1% FOS in the second phase, and 4. Rats following a similar two-phase HFD regimen but with 2% FOS supplementation. We carefully monitored dietary intake and conducted glucose tolerance tests. After the treatment, we performed a 16S rRNA gene analysis of the intestinal microbiota. Our findings revealed a notable increase in the glycemic peak within the first 15 minutes of high-fat consumption when compared to the supplemented groups. Further, we observed a significant increase in specific pathogenic phyla (notably Proteobacteria and Firmicutes) in the group with rats consistently consuming a high-fat diet. There were no statistically significant differences in food intake between the experimental groups. The administration of Yacon syrup effectively mitigated the adverse effects of the high-fat diet on glycemic control and the composition of the intestinal microbiota. This underscores the prebiotic potential of Yacon syrup and its promise as a valuable dietary intervention in the context of high-fat diets.
Glomerulonephritis associated with Takayasu arteritis
Authors: Kardaş Rıza Can , Yıldırım Derya , Kaya Burcugül , Vasi İbrahim , Duran Rahime , Erden Abdulsamet , Küçük Hamit , Göker Berna , Öztürk M. Akif 
Published: July 2024

Abstract

Purpose: Takayasu arteritis (TAK) is a large vessel granulomatous vasculitis usually seen before 50 years of age. While TAK may involve renal artery and its branches, its association with glomerulonephritis is rare. Main objective of this study is to introduce three new cases of TAK-associated glomerulonephritis with a review of literature.
Methods: TAK cases followed in Gazi University rheumatology clinic were retrospectively analyzed using chart review. Cases associated with glomerulonephritis were selected. Demographic, clinical, laboratory, radiological and pathological data were extracted from patient charts. Literature review was conducted using keywords “Takayasu” and “glomerulonephritis” via PubMed. Cases with patients younger than 16 years of age and potential confounding co-morbidities such as presence of SLE or ANCA positivity were excluded.
Results: Three cases of glomerulonephritis were found among 72 TAK cases (4%). All cases of glomerulonephritis were diagnosed after the diagnosis of TAK. Two of the cases were mesangioproliferative glomerulonephritis and one case was focal segmental glomerulosclerosis.
The literature review identified 28 cases of TAK-associated glomerulonephritis. Median duration of disease was 9 years. Majority of TAK cases were Numano type V or I, with about 22% of cases involving renal artery. Most common type of glomerulonephritis associated with TAK was mesangial glomerulonephritis, followed by membranoproliferative glomerulonephritis.
Conclusions: Glomerulonephritis is rarely associated with TAK. However, it should be considered when evaluating a TAK patient with clinical features indicative of glomerulonephritis, such as new-onset proteinuria that cannot be explained otherwise
Interactions between eagles and semi-domestic reindeer – lessons learned from field surveys and deterrents
Authors: Meiden Aemilius Johannes , López-Peinado Andrés , Sunesson Peter , Emilsson Christian , Singh Navinder J 
Published: July 2024

Abstract

1) Predation by eagles on semi-domesticated reindeer (Rangifer tarandus) is an emerging human wildlife conflict in Fennoscandia. Both the Golden (Aquila chrysaetos) and the White-tailed eagle (Haliaeetus albicilla) are believed by herders to predate on reindeer, however, there is a considerable knowledge gap regarding extent of predation and scavenging by each species, and their distribution and behaviour within the reindeer herding areas. Currently, the compensation for Golden eagle predation to herders is based on the herd size, and reindeer herders claim that the predation levels are much higher than assumed and hence the compensations are insufficient. Lethal and non-lethal methods have been suggested to reduce this conflict with eagles. 2) We developed this pilot project to fill the existing knowledge gaps by investigating the patterns of eagle abundance before, during, and after reindeer calving in a reindeer herding district in northern Sweden, and testing the effect of two potential deterrents (air ventilators and rotating prisms) in diverting eagles away from reindeer calving areas. 3) During the single study period, we made 12, 47, and 17 eagle observations before, during, and after calving respectively. Out of these observations, 34 were of Golden eagles, 33 of White-tailed eagles, and for 9 observations the species could not be confirmed. Eagle abundance increased during calving and decreased again after calving ended. No attacks by eagles on calves were observed. Two dead calves were found, but the cause of death could not be assigned to any eagle species. Most eagle observations were made in the control area, with significantly higher odds of observing eagles in the control area compared to areas with deterrents. 4) We show that the eagle abundance clearly increased during the calving period and declined afterwards, more sub-adults were observed during calving, and both species were present in the area. The extent of predation was difficult to infer using direct observations and deterrents seem to show promise in diverting eagles away from calving grounds. These studies should be replicated to get a general picture of the issue and testing the efficiency of deterrents in diverting eagles away from reindeer across reindeer herding districts.
The Hierarchical Stochastic Block Model for Multiple Networks
Authors: Battiston Marco , Lee Clement 
Published: July 2024

Abstract

In many research fields, there is an increased availability of network data arising as multiple networks. However, most statistical models for network data in the literature are designed for a single network. Among these, the Stochastic Block Model is arguably the most popular model to perform vertex clustering and community detection. We propose the Hierarchical Stochastic Block Model, a generalization of the SBM to the setting of multiple networks. This model uses a Hierarchical Pitman-Yor prior for the block allocation vector of each graph. The proposed model has two main advantages: 1) it allows different networks to share the same latent blocks and the level of sharing is learnt from the data; 2) the number of blocks in each graph and the overall number of blocks are learnt from the data too, hence avoiding complicated model selection procedures. We derive both MCMC and Variational Inference algorithms. The former targets the correct posterior and is tuning-free, while the latter relies on an approximation of the posterior distribution, but is potentially more scalable than MCMC. We apply the HSBM to a co-authorship network and a brain connectomic network, to illustrate how the model is able to capture different levels of block sharing.
Rainfall Projections for the Brazilian Legal Amazon using Recurrent Neural Networks
Authors: Monteiro Luiz Augusto Ferreira , Oliveira-Júnior José Francisco , Nunes Dorisvalder Dias , Mendes David , Gois Givanildo , Sanches Fabio Oliveira , Wollmann Cassio Arthur , Watanabe Michel , Gobo João Paulo Assis 
Published: July 2024

Abstract

Rainfall in the Brazilian Legal Amazon (BLA) is vital for climate and water resource management. This research uses spatial downscaling and validated rainfall data from the National Water and Sanitation Agency (ANA) to ensure accurate rain projections with artificial intelligence. Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM) were employed to forecast rainfall from 2012 to 2020. The RNN model showed strong alignment with observed patterns, accurately predicting rainfall seasonality. However, median comparisons revealed fair approximations with discrepancies. The Root Mean Square Error (RMSE) ranged from 6.7mm to 11.2mm, and the coefficient of determination (R²) was low in some series. Extensive analyses showed low Wilmott agreement and high Mean Absolute Percentage Error (MAPE), highlighting limitations in projecting anomalies and days without rain. Despite challenges, the study lays a foundation for future advancements in climate modeling and water resource management in the BLA.