bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between proteinuria and changes in antepartum and postpartum choroidal thickness in patients with pre-eclampsia
Authors: Lee You Hyun , Kim Do Yeon , Bae Jin Gon , Kim Yu Cheol 
Published: June 2024

AbstractPre-eclampsia (PE) is a hypertensive disorder characterised by systemic vascular resistance and endothelial dysfunction. It is known to influence choroidal thickness (CT). No previous studies have explored the antepartum and postpartum changes in CT with respect to the protein-creatinine ratio (PCR), a measure of proteinuria that is a clinical hallmark of PE. This study evaluated the correlations between antepartum and postpartum CT and the PCR in patients with PE. In this retrospective study, sixty-six eyes (66 patients) were analysed. The patients were divided into two groups according to the median PCR value (2.36 mg/mg): low PCR group (< 2.36 mg/mg) and high PCR group (≥ 2.36 mg/mg). Ophthalmologic clinical data were collected and assessed. We observed higher antepartum CT and higher mean arterial pressure in high PCR group than in low PCR group. Moreover, postpartum CT decreased significantly in high PCR group. In the multivariate analysis, CT changes were correlated with antepartum CT and antepartum PCR after logarithm transformation. In conclusion, a greater decrease in CT was observed in high PCR group than in low PCR group. Further, the antepartum PCR showed a correlation with the extent of CT reduction.
On-device query intent prediction with lightweight LLMs to support ubiquitous conversations
Authors: Dubiel Mateusz , Barghouti Yasmine , Kudryavtseva Kristina , Leiva Luis A. 
Published: June 2024

AbstractConversational Agents (CAs) have made their way to providing interactive assistance to users. However, the current dialogue modelling techniques for CAs are predominantly based on hard-coded rules and rigid interaction flows, which negatively affects their flexibility and scalability. Large Language Models (LLMs) can be used as an alternative, but unfortunately they do not always provide good levels of privacy protection for end-users since most of them are running on cloud services. To address these problems, we leverage the potential of transfer learning and study how to best fine-tunelightweightpre-trained LLMs to predict the intent of user queries. Importantly, our LLMs allow for on-device deployment, making them suitable for personalised, ubiquitous, and privacy-preserving scenarios. Our experiments suggest that RoBERTa and XLNet offer the best trade-off considering these constraints. We also show that, after fine-tuning, these models perform on par with ChatGPT. We also discuss the implications of this research for relevant stakeholders, including researchers and practitioners. Taken together, this paper provides insights into LLM suitability for on-device CAs and highlights the middle ground between LLM performance and memory footprint while also considering privacy implications.
Organic fertilizer application promotes the soil nitrogen cycle and plant starch and sucrose metabolism to improve the yield of Pinellia ternata
Authors: Wei Lu , Li Jinxin , Qu Kaili , Chen Hong , Wang Mingxing , Xia Shuaijie , Cai Huixia , Long Xi-En , Miao Yuhuan , Liu Dahui 
Published: June 2024

AbstractPinellia ternata (Thunb.) Breit is a traditional Chinese medicine with important pharmacological effects. However, its cultivation is challenged by soil degradation following excessive use of chemical fertilizer. We conducted an experiment exploring the effects of replacing chemical fertilizers with organic fertilizers (OF) on the growth and yield of P. ternata, as well as on the soil physicochemical properties and microbial community composition using containerized plants. Six fertilization treatments were evaluated, including control (CK), chemical fertilizer (CF), different proportions of replacing chemical fertilizer with organic fertilizer (OM1−4). Containerized P. ternata plants in each OF treatment had greater growth and yield than the CK and CF treatments while maintaining alkaloid content. The OM3 treatment had the greatest yield among all treatments, with an increase of 42.35% and 44.93% compared to the CK and CF treatments, respectively. OF treatments improved soil quality and fertility by enhancing the activities of soil urease (S-UE) and sucrase (S-SC) enzymes while increasing soil organic matter and trace mineral elements. OF treatments increased bacterial abundance and changed soil community structure. In comparison to the CK microbial groups enriched in OM3 were OLB13, Vicinamibacteraceae, and Blrii41. There were also changes in the abundance of gene transcripts among treatments. The abundance of genes involved in the nitrogen cycle in the OM3 has increased, specifically promoting the transformation of N-NO3− into N-NH4+, a type of nitrogen more easily absorbed by P. ternata. Also, genes involved in "starch and sucrose metabolism" and "plant hormone signal transduction" pathways were positively correlated to P. ternata yield and were upregulated in the OM3 treatment. Overall, OF in P. ternata cultivation is a feasible practice in advancing sustainable agriculture and is potentially profitable in commercial production.
Predicting seasonal influenza outbreaks with regime shift-informed dynamics for improved public health preparedness
Authors: Kim Minhye , Kim Yongkuk , Nah Kyeongah 
Published: June 2024

AbstractIn this study, we propose a novel approach that integrates regime-shift detection with a mechanistic model to forecast the peak times of seasonal influenza. The key benefit of this approach is its ability to detect regime shifts from non-epidemic to epidemic states, which is particularly beneficial with the year-round presence of non-zero Influenza-Like Illness (ILI) data. This integration allows for the incorporation of external factors that trigger the onset of the influenza season-factors that mechanistic models alone might not adequately capture. Applied to ILI data collected in Korea from 2005 to 2020, our method demonstrated stable peak time predictions for seasonal influenza outbreaks, particularly in years characterized by unusual onset times or epidemic magnitudes.
Biosynthesis of copper nanoparticles using Solenostemma argel and their effect on enhancing salt tolerance in barley plants
Authors: Shaikhaldein Hassan O. , Al-Qurainy Fahad , Nadeem Mohammad , Khan Salim , Tarroum Mohamed , Salih Abdalrhaman M. , Al-Hashimi Abdulrahman 
Published: June 2024

AbstractThe distinctive characteristics of nanoparticles and their potential applications have been given considerable attention by scientists across different fields, particularly agriculture. However, there has been limited effort to assess the impact of copper nanoparticles (CuNPs) in modulating physiological and biochemical processes in response to salt-induced stress. This study aimed to synthesize CuNPs biologically using Solenostemma argel extract and determine their effects on morphophysiological parameters and antioxidant defense system of barley (Hordeum vulgare) under salt stress. The biosynthesized CuNPs were characterized by (UV–vis spectroscopy with Surface Plasmon Resonance at 320 nm, the crystalline nature of the formed NPs was verified via XRD, the FTIR recorded the presence of the functional groups, while TEM was confirmed the shape (spherical) and the sizes (9 to 18 nm) of biosynthesized CuNPs. Seeds of barley plants were grown in plastic pots and exposed to different levels of salt (0, 100 and 200 mM NaCl). Our findings revealed that the supplementation of CuNPs (0, 25 and 50 mg/L) to salinized barley significantly mitigate the negative impacts of salt stress and enhanced the plant growth-related parameters. High salinity level enhanced the oxidative damage by raising the concentrations of osmolytes (soluble protein, soluble sugar, and proline), malondialdehyde (MDA) and hydrogen peroxide (H2O2). In addition, increasing the activities of enzymatic antioxidants, total phenol, and flavonoids. Interestingly, exposing CuNPs on salt-stressed plants enhanced the plant-growth characteristics, photosynthetic pigments, and gas exchange parameters. Furthermore, CuNPs counteracted oxidative damage by lowering the accumulation of osmolytes, H2O2, MDA, total phenol, and flavonoids, while simultaneously enhancing the activities of antioxidant enzymes. In conclusion, the application of biosynthesized CuNPs presents a promising approach and sustainable strategy to enhance plant resistance to salinity stress, surpassing conventional methods in terms of environmental balance.
Trace fossils as mechanical discontinuities in shales, insight for the generation of bedding-parallel veins (BPV)
Authors: Zanella Alain , Ruiz Remigio , Varela Augusto N. , Arregui Mariano G. 
Published: June 2024

AbstractUnderstanding shale petrophysical parameters is of interest due to its direct implications as cap rocks for CO2 or hydrogen storage, waste depositions, and as unconventional reservoirs. The generation and propagation of natural and induced fracture networks in such rocks is highly dependent on the mechanical behavior linked to several sedimentological parameters, as lithological discontinuities or bioturbation. This study is focused on a different sedimentological parameter that consists of trace fossils and their implication on the generation of fluid-assisted fractures, called bedding-parallel veins. In the Austral-Magallanes Basin, Southern Patagonia, Argentina, both geological features, Skolithos Ichnofacies (doomed pioneers trace fossils) and bedding-parallel veins, are numerous, especially at the top of the turbiditic bodies. The trace fossils exhibit U-shaped vertically oriented burrows composed of clean sandstone, partially cemented by calcite, and a spreite in the central part with heterogenous laminated siltstone. Bedding-parallel veins are composed of calcite fibers with some pyrite grains and bitumen. They are located on the top of the trace fossils along the lithological discontinuity between the turbiditic bodies and the impermeable shales. On their surfaces, a radial pattern starts growing from the trace fossils. Moreover, the number of bedding-parallel veins is dependent on the bioturbation intensity. With this study, we infer that trace fossils represent ichnological mechanical discontinuities (IMD) that have a key role in the generation and development of bedding-parallel veins. By correlation, we also suggest that these geological features must be thoroughly studied, especially regarding their potential for the development of induced fracturing networks.
The effectiveness of digital twins in promoting precision health across the entire population: a systematic review
Authors: Shen Mei-di , Chen Si-bing , Ding Xiang-dong 
Published: June 2024

AbstractDigital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions. Existing systematic reviews, however, mainly focus on the technological dimensions of digital twins, with a limited exploration of their impact on health-related outcomes. Therefore, this systematic review aims to explore the efficacy of digital twins in improving precision healthcare at the population level. The literature search for this study encompassed PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database to retrieve potentially relevant records. Patient health-related outcomes were synthesized employing quantitative content analysis, whereas the Joanna Briggs Institute (JBI) scales were used to evaluate the quality and potential bias inherent in each selected study. Following established inclusion and exclusion criteria, 12 studies were screened from an initial 1321 records for further analysis. These studies included patients with various conditions, including cancers, type 2 diabetes, multiple sclerosis, heart failure, qi deficiency, post-hepatectomy liver failure, and dental issues. The review coded three types of interventions: personalized health management, precision individual therapy effects, and predicting individual risk, leading to a total of 45 outcomes being measured. The collective effectiveness of these outcomes at the population level was calculated at 80% (36 out of 45). No studies exhibited unacceptable differences in quality. Overall, employing digital twins in precision health demonstrates practical advantages, warranting its expanded use to facilitate the transition from the development phase to broad application.PROSPERO registry: CRD42024507256.
Correlations reveal the hierarchical organization of biological networks with latent variables
Authors: Häusler Stefan 
Published: June 2024

AbstractDeciphering the functional organization of large biological networks is a major challenge for current mathematical methods. A common approach is to decompose networks into largely independent functional modules, but inferring these modules and their organization from network activity is difficult, given the uncertainties and incompleteness of measurements. Typically, some parts of the overall functional organization, such as intermediate processing steps, are latent. We show that the hidden structure can be determined from the statistical moments of observable network components alone, as long as the functional relevance of the network components lies in their mean values and the mean of each latent variable maps onto a scaled expectation of a binary variable. Whether the function of biological networks permits a hierarchical modularization can be falsified by a correlation-based statistical test that we derive. We apply the test to gene regulatory networks, dendrites of pyramidal neurons, and networks of spiking neurons.
Metal-organic frameworks for solar-driven desalination
Authors: Zhang Panyouwen , Hu Yue , Yao Bing , Guo Jingyun , Ye Zhizhen , Peng Xinsheng 
Published: June 2024

AbstractThe rising demand for freshwater and the challenge of energy scarcity have fueled interest in solar interfacial water evaporation technology, which harnesses solar energy to produce clean water. Attaining high performance with this technology necessitates the development of highly efficient photothermal materials, heat management optimization, and the resolution of salt deposition issues to ensure equipment longevity. Metal-organic frameworks (MOFs) possess large specific surface areas and high porosity, making them ideal for various water treatment applications. In recent years, MOFs have been extensively employed for solar-driven desalination. Here, we review recent developments in the functionalization of MOFs thin films, composites and MOFs-based derivatives and strategies for achieving efficient seawater desalination with MOFs while preventing salt deposition. Furthermore, desalination systems that integrate pollutant degradation and power generation are discussed, which further expand the application scenarios of solar-driven interfacial water evaporation desalination technologies.
Enterprise’s strategies to improve financial capital under a climate change scenario – evidence of the leading country
Authors: Nguyen Quang-Loc , Nguyen Minh-Hoang , La Viet-Phuong , Bhatti Muhammad Ishaq , Hoang Vuong Quan 
Published: June 2024

AbstractClimate change poses manifold consequences to the world’s ecosystems and human well-being. Greenhouse gas emissions reduction and climate-friendly technological innovations at the corporate level are considered effective measures to mitigate climate change. Using the Bayesian Mindsponge Framework (BMF) to analyze 178 enterprises listed in the Standard and Poor’s 500 companies from 2016 to 2021, this paper examines how companies’ climate risk-mitigating efforts can affect their market value. We found that emitted carbon dioxide negatively affects the stock price. Meanwhile, companies’ income and climate risk-mitigating efforts, including producing eco-friendly products, using renewable energy, and environmental investments, are positively associated with their share value. However, the effects of these efforts are conditional on the companies’ income. Based on these findings, we suggest that building an eco-surplus culture among investors and improving their climate change knowledge can be a promising approach to promoting a corporation’s mitigation efforts.
The enablers of adaptation: A systematic review
Authors: Brullo Tia , Barnett Jon , Waters Elissa , Boulter Sarah 
Published: June 2024

AbstractKnowledge of the practice of climate change adaptation is slowly shifting from a focus on barriers and limits to an understanding of its enablers. Here we take stock of the knowledge on the enablers of adaptation through a systematic review of the literature. Our review of empirical articles explaining how adaptation is enabled finds that there is a tendency in the literature to focus on local-scale case studies. Across all studies, some factors seem to be more important than others, including resources (particularly money), awareness of climate risks and responses, leadership, bridging and bonding social capital, and the support of higher-level institutions. Our analysis also highlights significant gaps in knowledge about enablers, including those that affect change in regional/provincial and national governments, in the private sector, and in non-local not-for-profit and non-governmental organisations.
Studying and improving reasoning in humans and machines
Authors: Yax Nicolas , Anlló Hernán , Palminteri Stefano 
Published: June 2024

AbstractIn the present study, we investigate and compare reasoning in large language models (LLMs) and humans, using a selection of cognitive psychology tools traditionally dedicated to the study of (bounded) rationality. We presented to human participants and an array of pretrained LLMs new variants of classical cognitive experiments, and cross-compared their performances. Our results showed that most of the included models presented reasoning errors akin to those frequently ascribed to error-prone, heuristic-based human reasoning. Notwithstanding this superficial similarity, an in-depth comparison between humans and LLMs indicated important differences with human-like reasoning, with models’ limitations disappearing almost entirely in more recent LLMs’ releases. Moreover, we show that while it is possible to devise strategies to induce better performance, humans and machines are not equally responsive to the same prompting schemes. We conclude by discussing the epistemological implications and challenges of comparing human and machine behavior for both artificial intelligence and cognitive psychology.
Tracing household transmission of SARS-CoV-2 in New Zealand using genomics
Authors: Jelley Lauren , Aminisani Nayyereh , O’Neill Meaghan , Jennings Tineke , Douglas Jordan , Utekar Srushti , Johnston Helen , Welch David , Hadfield James ,   SHIVERS Investigation Team,   Clinical Advisors:, Turner Nikki , Dowell Tony , Nesdale Annette , Dobinson Hazel C. , Campbell-Stokes Priscilla , Balm Michelle , Grant Cameron C. , Daniells Karen , McIntyre Peter , Trenholme Adrian , Byrnes Cass ,   Study and Clinical and data team:, Seeds Ruth , Wood Tim , Rensburg Megan , Cueto Jort , Caballero Ernest , John Joshma , Penghulan Emmanuel , Currin Danielle , Ryan Mary , Bowers Andrea ,   Clinical Virology Team:, Tan Chor Ee , Bocacao Judy , Gunn Wendy , Bird Bryden , Slater Tegan , Ahmed Farjana , Sam Mai Anh , Glampe Elaisa , Davey Gabriella , de Ligt Joep , Winter David , French Nigel , Thomas Paul G. , Webby Richard J. , Huang Sue , Geoghegan Jemma L. 
Published: June 2024

AbstractBy early 2022, the highly transmissible Omicron variant of SARS-CoV-2 had spread across most of the world. For the first time since the pandemic began, New Zealand was experiencing high levels of community transmission of SARS-CoV-2. We enroled a cohort of households to better understand differences in transmission dynamics among subvariants of Omicron. We enroled 71 households, comprising 289 participants, and aimed to use viral genomes to gain a clearer understanding of variant-specific differences in epidemiological parameters affecting transmission dynamics. Approximately 80% of the households enroled experienced transmission of BA.2, while most of the remaining households had infections with BA.1 or BA.5. Using a logistic regression generalised linear mixed model, we found no difference in household secondary infection rate between Omicron subvariants BA.1, BA.2 and BA.5. Of the households recruited, the vast majority (92%) experienced a single chain of transmission with one inferred introduction. Further, we found that in 48% of the households studied, all household participants became infected following an index case. Most household participants tested positive within a week following an introduction, supporting the seven-day isolation requirement for household contacts that was in place in New Zealand at the time. By integrating genomic and epidemiological data, we show that viral transmission dynamics can be investigated with a higher level of granularity than with epidemiological data alone. Overall, households are a high risk setting for viral transmission in New Zealand.
Assessing the myth of disaster risk reduction in the wake of catastrophic floods
Authors: Nohrstedt Daniel , Mondino Elena , Di Baldassarre Giuliano , Parker Charles F. 
Published: June 2024

AbstractWhether disasters serve as focusing events leading to measures that reduce future disaster risks is contested. Here, we study flood disasters in 23 of the world’s most flood-prone countries to assess whether catastrophic floods, those milestone events with the highest fatalities, have been followed by decreasing mortality in subsequent floods. Results from a trend analysis, controlling for flood magnitude and subtypes, find that reductions in mortality rates have rarely followed the most devastating floods.
Stochastic coastal flood risk modelling for the east coast of Africa
Authors: Benito Irene , Aerts Jeroen C. J. H. , Eilander Dirk , Ward Philip J. , Muis Sanne 
Published: June 2024

AbstractCoastal flooding resulting from tropical cyclones can have large repercussions in many low-lying regions around the world. Accurate flood risk assessments are crucial for designing measures to reduce the societal impacts of coastal flooding. At continental to global scales, however, traditional flood risk assessments mostly use methods that do not capture the spatiotemporal dynamics of coastal flood risk patterns. In this study, we address these deficiencies by applying a novel modelling framework that dynamically simulates stochastic coastal flood risk for the east coast of Africa. Using 10,000 years of synthetic tropical cyclones and a cascade of hydrodynamic models to simulate storm tides and flooding, we calculate the damage of each individual tropical cyclone event and empirically derive the risk curve for each country. Results show that the largest aggregated annual losses in the region come from multiple events rather than from a single low-probability event. Results also reveal that events with the highest return periods in terms of storm surge residual levels and flood extents are not necessarily the most damaging events. Here, the 1 in 10,000-year damage event is associated with a 1 in 45-year event in terms of flood extent, showing that addressing exposure and vulnerability is essential in determining risk. Our modelling framework enables a high-resolution continental-scale risk analysis that takes the spatial dependencies of flood events into account.