bluuebunny/crossref_metadata_2025_split huggingface dataset:
Annual and geographical variations in the specific composition of jassids and their damage on cotton in Ivory Coast
Authors: Kouadio Houphouet , Kouakou Malanno , Bini Kouadio Kra Norbert , Koffi Kouakou Jean Innocent , Ossey Christian Landry , Kone Pitou Woklin Euloge , Adepo-Gourene Abouo Béatrice , Ochou Ochou Germain 
Published: January 2024

AbstractIn recent years, jassids have become a real problem for cotton growing in Ivory Coast. It is important to investigate the causes of this problem. The aim of this study was to highlight the diversity of jassid species and their impact on cotton growing in Ivory Coast. The collections carried out in 2021 identified three species. Jacobiasca lybica (Bergevin & Zanon, 1922) is the most abundant, with proportions ranging from 73.3 to 93.3% depending on the site. The other two species are Empoasca papayae (Oman, 1937) (8.3%) and Empoasca facialis (Jacobi, 1912) (5%). In 2022, collections revealed the invasion of a new species, Amrasca biguttula (Shiraki, 1913), which became dominant with proportions of 90 to 100% depending on the site. Two other species, Jacobiasca lybica (Bergevin & Zanon, 1922) (2.7%) and Empoasca facialis (Jacobi, 1912) (1.3%), cohabit with Amrasca biguttula (Shiraki, 1913). Thus, while the damage noted in 2021 was attributable to Jacobiasca lybica (Bergevin & Zanon, 1922), that observed in 2022 is essentially due to Amrasca biguttula (Shiraki, 1913), with incidences exceeding the economic impact threshold. The North-East of the cotton basin was the area most affected by attacks by these two species. The results of the study reveal significant changes in jassid species composition and climatic conditions in the cotton-growing areas of Ivory Coast, from 1 year to the next. This situation also explains the variations in damage levels.
A collaborative privacy-preserving approach for passenger demand forecasting of autonomous taxis empowered by federated learning in smart cities
Authors: Munawar Adeel , Piantanakulchai Mongkut 
Published: January 2024

AbstractThe concept of Autonomous Taxis (ATs) has witnessed a remarkable surge in popularity in recent years, paving the way toward future smart cities. However, accurately forecasting passenger demand for ATs remains a significant challenge. Traditional approaches for passenger demand forecasting often rely on centralized data collection and analysis, which can raise privacy concerns and incur high communication costs. To address these challenges, We propose a collaborative model using Federated Learning (FL) for passenger demand forecasting in smart city transportation systems. Our proposed approach enables ATs in different regions of the smart city to collaboratively learn and improve their demand forecasting models through FL while preserving the privacy of passenger data. We use several backpropagation neural networks as local models for collaborating to train the global model without directly sharing their data. The local model shares only the model updates with a global model that aggregates them, which is then sent back to local models to improve them. Our collaborative approach reduces privacy concerns and communication costs by facilitating learning from each other’s data without direct data sharing. We evaluate our approach using a real-world dataset of over 4500 taxis in Bangkok, Thailand. By utilizing MATLAB2022b, the proposed approach is compared with popular baseline methods and existing research on taxi demand forecasting systems. Results demonstrate that our proposed approach outperforms in passenger demand forecasting, surpassing existing methods in terms of model accuracy, privacy preservation, and performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and R-squared ($$R^2$$

R
2

). Furthermore, our approach exhibits improved performance over time through the collaborative learning process as more data becomes available.
Impact of CD 28, CD86, CTLA-4 and PD-1 genes polymorphisms on acute renal allograft rejection and graft survival among Egyptian recipients
Authors: Ghoneim Moatasem Elsayed , Sheashaa Hussein , Wafa Ehab , Awadalla Amira , Ahmed Asmaa E. , Sobh Mohamed , Shokeir Ahmed Abdulrahman 
Published: January 2024

AbstractTo study the impact of four gene polymorphisms on acute renal allograft rejection (AR) and graft survival among Egyptian population. These 4 gene polymorphisms include: (1) CD 28 (rs3116496), (2) CD86 (rs1129055), (3) CTLA-4 (rs3087243), (4) PD-1 (rs2227982). This is a non-concurrent cohort study including 50 kidney transplant recipients diagnosed histopathologically as (AR) [study group] and another 50 matched allograft recipients without AR [control group]. Blood samples were taken from both groups and subjected to genotyping for the selected four genetic polymorphisms by TaqMan genotyping assay. The difference in genotypic distribution of CD 28: rs3116496 and CD86: rs1129055 wasn't statistically significant between the study and control groups (P = 0.22 and 0.33 respectively) and also both polymorphisms had no effect on graft survival (P = 0.36 and 0.74 respectively) while the addition of C allele to IVS3 +17T/C polymorphism in CD28 gene showed a protective effect against AR (P = 0.03). CTLA-4: rs3087243 AG genotype showed a protective effect against AR as it was more frequent in no rejection group compared to those with AR (P = 0.001) with a statistically significant impact on graft survival (P < 0.001), while PD-1: rs2227982 AG genotype was equally distributed between both groups (variant of unknown significance). There was no detected association between CD86 polymorphism: rs1129055 and CD 28 polymorphism: rs3116496 with the development of AR. However, C allele of CD 28 IVS3 +17T/C polymorphism and CTLA-4 polymorphism: rs3087243AG genotype both demonstrated a protective effect against AR.
Achalasia alters physiological networks depending on sex
Authors: Furuzawa-Carballeda Janette , Barajas-Martínez Antonio , Olguín-Rodríguez Paola V. , Ibarra-Coronado Elizabeth , Fossion Ruben , Coss-Adame Enrique , Valdovinos Miguel A. , Torres-Villalobos Gonzalo , Rivera Ana Leonor 
Published: January 2024

AbstractAchalasia is a rare esophageal motility disorder for which the etiology is not fully understood. Evidence suggests that autoimmune inflammatory infiltrates, possibly triggered by a viral infection, may lead to a degeneration of neurons within the myenteric plexus. While the infection is eventually resolved, genetically susceptible individuals may still be at risk of developing achalasia. This study aimed to determine whether immunological and physiological networks differ between male and female patients with achalasia. This cross-sectional study included 189 preoperative achalasia patients and 500 healthy blood donor volunteers. Demographic, clinical, laboratory, immunological, and tissue biomarkers were collected. Male and female participants were evaluated separately to determine the role of sex. Correlation matrices were constructed using bivariate relationships to generate complex inferential networks. These matrices were filtered based on their statistical significance to identify the most relevant relationships between variables. Network topology and node centrality were calculated using tools available in the R programming language. Previous occurrences of chickenpox, measles, and mumps infections have been proposed as potential risk factors for achalasia, with a stronger association observed in females. Principal component analysis (PCA) identified IL-22, Th2, and regulatory B lymphocytes as key variables contributing to the disease. The physiological network topology has the potential to inform whether a localized injury or illness is likely to produce systemic consequences and the resulting clinical presentation. Here we show that immunological involvement in achalasia appears localized in men because of their highly modular physiological network. In contrast, in women the disease becomes systemic because of their robust network with a larger number of inter-cluster linkages.
Identification of phenomic data in the pathogenesis of cancers of the gastrointestinal (GI) tract in the UK biobank
Authors: Tan Shirin Hui , Guan Catherina Anak , Bujang Mohamad Adam , Lai Wei Hong , Voon Pei Jye , Sim Edmund Ui Hang 
Published: January 2024

AbstractGastrointestinal (GI) cancers account for a significant incidence and mortality rates of cancers globally. Utilization of a phenomic data approach allows researchers to reveal the mechanisms and molecular pathogenesis of these conditions. We aimed to investigate the association between the phenomic features and GI cancers in a large cohort study. We included 502,369 subjects aged 37–73 years in the UK Biobank recruited since 2006, followed until the date of the first cancer diagnosis, date of death, or the end of follow-up on December 31st, 2016, whichever occurred first. Socio-demographic factors, blood chemistry, anthropometric measurements and lifestyle factors of participants collected at baseline assessment were analysed. Unvariable and multivariable logistic regression were conducted to determine the significant risk factors for the outcomes of interest, based on the odds ratio (OR) and 95% confidence intervals (CI). The analysis included a total of 441,141 participants, of which 7952 (1.8%) were incident GI cancer cases and 433,189 were healthy controls. A marker, cystatin C was associated with total and each gastrointestinal cancer (adjusted OR 2.43; 95% CI 2.23–2.64). In this cohort, compared to Asians, the Whites appeared to have a higher risk of developing gastrointestinal cancers. Several other factors were associated with distinct GI cancers. Cystatin C and race appear to be important features in GI cancers, suggesting some overlap in the molecular pathogenesis of GI cancers. Given the small proportion of Asians within the UK Biobank, the association between race and GI cancers requires further confirmation.
Music recommendation algorithms based on knowledge graph and multi-task feature learning
Authors: Liu Xinqiao , Yang Zhisheng , Cheng Jinyong 
Published: January 2024

AbstractDuring music recommendation scenarios, sparsity and cold start problems are inevitable. Auxiliary information has been utilized in music recommendation algorithms to provide users with more accurate music recommendation results. This study proposes an end-to-end framework, MMSS_MKR, that uses a knowledge graph as a source of auxiliary information to serve the information obtained from it to the recommendation module. The framework exploits Cross & Compression Units to bridge the knowledge graph embedding task with recommendation task modules. We can obtain more realistic triple information and exclude false triple information as much as possible, because our model obtains triple information through the music knowledge graph, and the information obtained through the recommendation module is used to determine the truth of the triple information; thus, the knowledge graph embedding task is used to perform the recommendation task. In the recommendation module, multiple predictions are adopted to predict the recommendation accuracy. In the knowledge graph embedding module, multiple calculations are used to calculate the score. Finally, the loss function of the model is improved to help us to obtain more useful information for music recommendations. The MMSS_MKR model achieved significant improvements in music recommendations compared with many existing recommendation models.
Simulation of the emergence of cell-like morphologies with evolutionary potential based on virtual molecular interactions
Authors: Ishida Takeshi 
Published: January 2024

AbstractThis study explored the emergence of life using a simulation model approach. The “multiset chemical lattice model” allows the placement of virtual molecules of multiple types in each lattice cell in a two-dimensional space. This model was capable of describing a wide variety of states and interactions, such as the diffusion, chemical reaction, and polymerization of virtual molecules, in a limited number of lattice cell spaces. Moreover, this model was capable of describing a wide variety of states and interactions, even in the limited lattice cell space of 100 × 100 cells. In this study, I assumed 18 types of virtual molecules, i.e., 18 virtual numbers that do not correspond to real molecules with chemical reactions represented by transformation of the numbers that occur with a specified reaction rate probability. Furthermore, it considered the energy metabolism and energy resources in the environment, and was able to reproduce “evolution,” in which a certain cell-like shape that adapted to the environment survived under conditions of decreasing amounts of energy resources in the environment. This enabled the simulation of the emergence of cell-like shapes with the four minimum cellular requirements, i.e., boundary, metabolism, replication, and evolution, based solely on the interaction of virtual molecules.
A deep multi-stream model for robust prediction of left ventricular ejection fraction in 2D echocardiography
Authors: Alvén Jennifer , Hagberg Eva , Hagerman David , Petersen Richard , Hjelmgren Ola 
Published: January 2024

AbstractWe propose a deep multi-stream model for left ventricular ejection fraction (LVEF) prediction in 2D echocardiographic (2DE) examinations. We use four standard 2DE views as model input, which are automatically selected from the full 2DE examination. The LVEF prediction model processes eight streams of data (images + optical flow) and consists of convolutional neural networks terminated with transformer layers. The model is made robust to missing, misclassified and duplicate views via pre-training, sampling strategies and parameter sharing. The model is trained and evaluated on an existing clinical dataset (12,648 unique examinations) with varying properties in terms of quality, examining physician, and ultrasound system. We report $$R^2 = 0.84$$

R
2

=
0.84

and mean absolute error = 4.0% points for the test set. When evaluated on two public benchmarks, the model performs on par or better than all previous attempts on fully automatic LVEF prediction. Code and trained models are available on a public project repository.
Silicon via fertigation with and without potassium application, improve physiological aspects of common beans cultivated under three water regimes in field
Authors: Gonzalez-Porras Carlos Vital , Teixeira Gelza Carliane Marques , Prado Renato de Mello , Ferreira Patrícia Messias , Palaretti Luiz Fabiano , Oliveira Kamilla Silva 
Published: January 2024

AbstractFrequent droughts have led to an expansion of irrigated common bean (Phaseolus vulgaris L.) cultivation areas. An effective strategy to enhance water use efficiency and optimize crop growth is the application of silicon (Si) and potassium (K). However, the interaction between Si dosage, water regimes, and plant potassium status, as well as the underlying physiological mechanisms, remains unknown. This study aimed to assess the effects of Si doses applied via fertigation under various water regimes, in the presence and absence of potassium fertilization, on gas exchange, water use efficiency, and growth of Common beans in field conditions. Two experiments were conducted, one with and one without K supply, considering that the potassium content in the soil was 6.4 mmolc dm-3 in both experiments and a replacement dose of 50 kg ha was applied in the with K treatment, with the same treatments evaluated in both potassium conditions. The treatments comprised a 3 × 4 factorial design, encompassing three water regimes: 80% (no deficit), 60% (moderate water deficit), and 40% (severe water deficit) of soil water retention capacity, and four doses of Si supplied via fertigation: 0, 4, 8, and 12 kg ha−1. Where it was evaluated, content of photosynthetic pigments, fluorescence of photosynthesis, relative water content, leaf water potential and electrolyte extravasation, dry mass of leaves, stems and total. The optimal doses of Si for fertigation application, leading to increased Si absorption in plants, varied with decreasing soil water content. The respective values were 6.6, 7.0, and 7.1 kg ha−1 for the water regimes without deficit, with moderate water deficit, and with severe water deficit. Fertigation application of Si improved plant performance, particularly under severe water deficit, regardless of potassium status. This improvement was evident in relative water content, leaf water potential, and membrane resistance, directly impacting pigment content and gas exchange rates. The physiological effects resulted in enhanced photosynthesis in water-deficient plants, mitigating dry mass production losses. This research demonstrates, for the first time in common bean, the potential of Si to enhance irrigation efficiency in areas limited by low precipitation and water scarcity.
Natal factors affecting developmental defects of enamel in preterm infants: a prospective cohort study
Authors: Park Shang-yon , Jeong Su Jin , Han Jung Ho , Shin Jeong Eun , Lee Jae-Ho , Kang Chung-Min 
Published: January 2024

AbstractThis study investigated natal factors influencing developmental defects of enamel (DDE) in premature infants using a newly refined preterm developmental defects of enamel (PDDE) index. Dental examinations were conducted on a cohort of 118 preterm infants (average age 3.5 ± 1.4 years) to record PDDE scores, while reviewing their medical records to examine natal factors. According to the logistic regression analysis, factors related to DDE prevalence were advanced maternal age, gestational age < 28 weeks, birth weight < 1000 g, 1 min APGAR score < 7, and hospitalization period > 2 months, which were significantly higher by 2.91, 5.53, 7.63, 10.02, and 4.0 times, respectively. According to regression analysis with generalized linear models, the PDDE scores were approximately 7.65, 4.96, and 15.0 points higher in premature children diagnosed with bronchopulmonary dysplasia, intraventricular hemorrhage, and necrotizing enterocolitis, respectively. When endotracheal intubation was performed, the PDDE score was 5.06 points higher. The prevalence of PDDE was primarily observed bilaterally in the maxillary anterior teeth. Extremely preterm infants showed significantly delayed tooth eruption, suggesting that the influence of gestational age on dental development rates. Identifying the factors related to DDE in premature children can inform early dental interventions to support the oral health of high-risk children.
Plasmonic slanted slit gratings for efficient through-substrate light-plasmon coupling and sensing
Authors: Mahani Fatemeh Fouladi , Astorga Luis Angel Mayoral , Choi Hyung Woo , Mokhtari Arash , Berini Pierre 
Published: January 2024

AbstractWe present an experimental study of plasmonic slanted slit gratings (PSSGs) designed to achieve directional coupling between an incident light beam and surface plasmon polaritons (SPPs) propagating along the surface of the structure. We also investigate mirrored PSSG pairs interconnected by a plasmonic slab waveguide. The structures are fabricated using direct milling by a gallium focused ion beam (FIB). In a mirrored pair arrangement, the first PSSG couples a perpendicularly-incident light beam to SPPs propagating in one direction along the waveguide, while the second PSSG decouples SPPs to perpendicularly-emerging light. This configuration shows promise for sensing applications due to the high sensitivity of the excited SPPs to changes in the refractive index of the bounding medium, and the separation of the optics from the fluidics by the substrate. The design also exhibits robustness to fabrication tolerances. The optical characteristics and sensing potential are investigated theoretically and experimentally, highlighting its potential for a wide range of applications.
Variation of floristic diversity, community composition, endemism, and conservation status of tree species in tropical rainforests of Sri Lanka across a wide altitudinal gradient
Authors: Sanjeewani Nimalka , Samarasinghe Dilum , Jayasinghe Himesh , Ukuwela Kanishka , Wijetunga Asanga , Wahala Sampath , De Costa Janendra 
Published: January 2024

AbstractTropical rainforests in Sri Lanka are biodiversity hotspots, which are sensitive to anthropogenic disturbance and long-term climate change. We assessed the diversity, endemism and conservation status of these rainforests across a wide altitudinal range (100–2200 m above sea level) via a complete census of all trees having ≥ 10 cm diameter at breast height in ten one-hectare permanent sampling plots. The numbers of tree families, genera and species and community-scale tree diversity decreased with increasing altitude. Tree diversity, species richness and total basal area per ha across the altitudinal range were positively associated with long-term means of maximum temperature, annual rainfall and solar irradiance. Percentage of endangered species increased with increasing altitude and was positively associated with cumulative maximum soil water deficit, day-night temperature difference and high anthropogenic disturbance. Percentage of endemic species was greater in the lowland rainforests than in high-altitude montane forests. Nearly 85% of the species were recorded in three or less plots, which indicated substantial altitudinal differentiation in their distributions. Less than 10 individuals were recorded in 41% of the endemic species and 45% of the native species, which underlined the need for urgent conservation efforts across the whole altitudinal range.
A pilot feasibility randomised controlled trial of bone antiresorptive agents on bone turnover markers in critically ill women
Authors: Orford Neil R. , Bone Allison , Kotowicz Mark A. , Bailey Michael , Pasco Julie A. , Maiden Matthew , Kakho Nima , Cattigan Claire , Nichonghaile Martina , Jones Claire , Hodgson Carol , Nair Priya , Center Jacqueline , Bellomo Rinaldo 
Published: January 2024

AbstractCritical illness is associated with increased bone turnover, loss of bone density, and increased risk of fragility fractures. The impact of bone antiresorptive agents in this population is not established. This trial examined the efficacy, feasibility, and safety of antiresorptive agents administered to critically ill women aged fifty years or greater. Women aged 50 years or greater admitted to an intensive care unit for at least 24 h were randomised to receive an antiresorptive agent (zoledronic acid or denosumab) or placebo, during critical illness and six months later (denosumab only). Bone turnover markers and bone mineral density (BMD) were monitored for 1 year. We studied 18 patients over 35 months before stopping the study due to the COVID-19 pandemic. Antiresorptive medications decreased the bone turnover marker type 1 cross-linked c-telopeptide (CTX) from day 0 to 28 by 43% (± 40%), compared to an increase of 26% (± 55%) observed with placebo (absolute difference − 69%, 95% CI − 127% to − 11%), p = 0.03). Mixed linear modelling revealed differences in the month after trial drug administration between the groups in serum CTX, alkaline phosphatase, parathyroid hormone, and phosphate. Change in BMD between antiresorptive and placebo groups was not statistically analysed due to small numbers. No serious adverse events were recorded. In critically ill women aged 50-years and over, antiresorptive agents suppressed bone resorption markers without serious adverse events. However, recruitment was slow. Further phase 2 trials examining the efficacy of these agents are warranted and should address barriers to enrolment.Trial registration: ACTRN12617000545369, registered 18th April 2017.