bluuebunny/crossref_metadata_2025 huggingface dataset:
The application of organoids in cancers associated with pathogenic infections
Authors: Zhang Yuyu , Liu Tao , He Wenting
Published: July 2024

Cancers associated with pathogen infections are gradually becoming important threats to human health globally, and it is of great significance to study the mechanisms of pathogen carcinogenesis. Current mechanistic studies rely on animal and two-dimensional (2D) cell culture models, but traditional methods have been proven insufficient for the rapid modeling of diseases caused by new pathogens. Therefore, research focus has shifted to organoid models, which can replicate the structural and genetic characteristics of the target tissues or organs in vitro, providing new platforms for the study of pathogen-induced oncogenic mechanisms. This review summarizes the application of organoid technology in the studies of four pathogen-associated cancers: gastric cancer linked to Helicobacter pylori, liver cancer associated with hepatitis B virus or hepatitis C virus, colorectal cancer caused by Escherichia coli, and cervical cancer related to human papillomavirus. This review also proposes several limitations of organoid technology to optimize organoid models and advance the treatment of cancer associated with pathogen infections in the future.
A systematic review and meta-analysis of the diagnostic accuracy of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in systemic lupus erythematosus
Authors: Zinellu Angelo , Paliogiannis Panagiotis , Mangoni Arduino A.
Published: July 2024

The wide range of clinical and serological manifestations in systemic lupus erythematosus (SLE) and the lack of accepted diagnostic criteria warrant the identification of novel, more accurate biomarkers. Hematological indices derived from full blood cell counts, particularly the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), have shown promise in SLE; however, a critical appraisal of their diagnostic accuracy is lacking. We sought to address this issue by conducting a systematic review and meta-analysis of the diagnostic accuracy of the NLR and PLR in SLE. The electronic databases PubMed, Scopus, and Web of Science were systematically searched from inception to 15 March 2024 for studies reporting the sensitivity and specificity of the NLR and PLR, obtained by receiver operating characteristic (ROC) curve analysis, for the presence of SLE, disease severity, organ involvement (lupus nephritis, pericarditis, and pleural disease), and complications (infections). The risk of bias was assessed using the JBI Critical Appraisal Checklist (PROSPERO registration number: CRD42024531446). The NLR exhibited good accuracy for the diagnosis of SLE (eight studies; area under the curve, AUC = 0.81, 95% CI 0.78–0.85) and lupus nephritis (nine studies; AUC = 0.81, 95% CI 0.77–0.84), but not for severe disease (nine studies; AUC = 0.69, 95% CI 0.65–0.73) or infections (six studies; AUC = 0.73, 95% CI 0.69–0.77). The PLR exhibited good accuracy for the diagnosis of severe disease (six studies; AUC = 0.85, 95% CI 0.81–0.87). There were an insufficient number of studies to assess the accuracy of the PLR for the diagnosis of SLE, lupus nephritis, or infections. No study investigated the NLR and PLR in SLE patients with pericarditis or pleural disease. Therefore, the NLR and the PLR have a relatively high diagnostic accuracy for the presence of SLE and lupus nephritis (NLR) and severe disease (PLR). Further studies are warranted to determine whether the NLR and PLR, in combination with clinical evaluation and other serological biomarkers, can enhance the diagnosis and management of SLE.
Acceptability of the Dapivirine Vaginal Ring and Daily Oral Pre-exposure Prophylaxis (PrEP) during Pregnancy in Malawi, South Africa, Uganda, and Zimbabwe
Authors: Young Alinda M. , Stoner Marie C.D. , Mathebula Florence , Mohuba Rebone , Baez Alejandro , Seyama Linly , Mutero Prisca , Etima Juliane , Fabiano Zayithwa , Fairlie Lee , Mayo Ashley J. , Balkus Jennifer E. , Song Mei , Bunge Katherine , Piper Jeanna , Balan Ivan C. , van der Straten Ariane , Montgomery Elizabeth T.
Published: July 2024

Pregnant and lactating persons in sub-Saharan Africa face a heightened risk of HIV acquisition, due to biological and behavioral factors, combined with limited access to prevention and treatment services. Oral pre-exposure prophylaxis (PrEP) and the dapivirine vaginal ring are promising tools for HIV prevention, and the ring’s recent approval in multiple African countries represents a significant advancement in expanding access to HIV prevention. In a nested qualitative study within the MTN-042 trial, we explored the acceptability of study products among pregnant persons in the second and early third trimesters. Interviews were conducted privately, using a semi-structured guide with 77 participants, in participants’ preferred language. Topics explored included product acceptability (using the theoretical framework of acceptability), user experience, satisfaction, disclosure, community attitudes, and sexual activity during pregnancy. Interview transcripts were analyzed using Dedoose software. We observed positive attitudes among participants towards the study products, which they found generally user-friendly, despite the added complexities of using them during pregnancy. Participants recognized that consistent and correct use would provide protection for both them and their unborn children. Although initial concerns existed, most of these worries dissipated over time, with study staff support and increased product use experience. These findings emphasize the importance of continued surveillance, support, and education to ensure the successful rollout of new HIV prevention measures during pregnancy.
Left ventricular diastolic function assessed by speckle tracking echocardiography in patients with left ventricular aneurysm
Authors: Nemchyna Olena , Solowjowa Natalia , Hrytsyna Yuriy , Dandel Michael , Merke Nicolas , Knierim Jan , Schoenrath Felix , Just Isabell Anna , Hennig Felix , Hohendanner Felix , Falk Volkmar , Knosalla Christoph
Published: July 2024

Speckle-tracking echocardiography (STE) parameters are an integral part of the assessment of left ventricular (LV) function. We aimed to evaluate established and novel STE parameters of LV diastolic function and their prognostic role in patients with LV anteroapical aneurysm undergoing surgical ventricular repair (SVR). We retrospectively examined the data of 137 patients with anteroapical LV aneurysm who underwent SVR. In 27 patients, the correlation of STE parameters with invasive hemodynamic parameters was evaluated. Preoperative echocardiographic parameters were assessed for their association with outcome, defined as all-cause mortality, LV assist device implantation, or heart transplantation. The late diastolic strain rate (GLSRa) showed a stronger correlation with mean pulmonary artery pressure (r =  − 0.75, p < 0.001) than all other parameters. GLSRa was also significantly correlated with mean pulmonary capillary wedge pressure and LV end-diastolic pressure. In the multivariate model, GLSRa and the ratio of early diastolic filling velocity to GLSRa demonstrated incremental prognostic value in addition to clinical and echocardiographic parameters. Patients with GLSRa < 0.59 s−1 had significantly shorter event-free survival than those with GLSRa > 0.59 s−1 (6.7 vs. 10.9 years, p < 0.001). Peak reservoir left atrial strain showed a weaker association with hemodynamic parameters and outcome compared to GLSRa. In patients with LV aneurysm, late diastolic strain rate and left atrial strain can be used for the assessment of LV diastolic function and have a predictive value for the outcome after surgical ventricular restoration.

Graphical abstract
Impact of Global Risk Factors on the Islamic Stock Market: New Evidence from Wavelet Analysis
Authors: Kazak Hasan , Saiti Buerhan , Kılıç Cüneyt , Akcan Ahmet Tayfur , Karataş Ali Rauf
Published: July 2024

The emergence of Islamic finance as an alternative financial investment area and the increasing political and economic uncertainty around the world necessitated an examination of the relationship between these two factors. This study examines the impact of four important global uncertainty and risk indicators “Global Economic Policy Uncertainty-GEPU, Geopolitical Risk Index-GPR, World Uncertainty Index-WUI, and CBOE Volatility Index-VIX” on two important Islamic stock market indices (Dow Jones Islamic Market Index and Bist Participation 100) using wavelet coherence (WTC) and asymmetric Fourier TY analyzes Quarterly data for the period March 2011–June 2023 were used in the study. The results of the analysis show that economic instability indicators impact Islamic equity market indices (both in Turkey and the world). This effect is determined as VIX, GEPU, GPR, and WUI. In addition, the fact that the GPR and WUI indices, which have an impact on conventional markets, have truly little and only a partial impact on Islamic equity markets is an important finding. The results of this study make important contributions to the literature and provide important findings for investors and policy makers.
Exploring silicon nanoparticles and nanographite-based anodes for lithium-ion batteries
Authors: Thombare Sohan , Patil Rohan , Humane Ranjit , Kale Bharat , Kalubarme Ramchandra , Malavekar Dhanaji , Phadatare Manisha , Lokhande Chandrakant
Published: July 2024

This study investigates the performance of silicon nanoparticles (Si NPs) and silicon nanographite (SiNG) composite-based anodes for lithium-ion batteries (LiBs). Si offers a promising alternative to traditional graphite anodes due to its higher theoretical capacity, despite encountering challenges such as volume expansion, pulverization, and the formation of a solid electrolyte interface (SEI) during lithiation. SiNPs anode exhibited initial specific capacities of 1568.9 mAh/g, decreasing to 1137.6 mAh/g after 100th cycles, with stable Li–Si alloy phases and high Coulombic efficiency (100.48%). It also showed good rate capability, retaining 1191.3 mAh/g at 8400 mA g−1 (2.82C), attributed to its carbon matrix structure. EIS indicated charge transfer with RB of 3.9 Ω/cm−2 and RCT of 11.4 Ω/cm−2. Contrastingly, SiNG composite anode had an initial capacity of 1780.7 mAh/g, decreasing to 1297.5 mAh/g after 100 cycles. Its composite structure provided cycling stability, with relatively stable capacities after 50 cycles. It exhibited good rate capability (1191.3 mAh/g at 8399.9 mA g−1), attributed to its carbon matrix structure. Electrochemical impedance spectroscopy showed higher resistances for RB of 4.2 Ω/cm−2 and RCT of 15.6 Ω/cm−2 compared to SiNPs anode. These findings suggest avenues for improving energy storage devices by selecting and designing suitable anode materials.
Artificial intelligence in chronic kidney diseases: methodology and potential applications
Authors: Simeri Andrea , Pezzi Giuseppe , Arena Roberta , Papalia Giuliana , Szili-Torok Tamas , Greco Rosita , Veltri Pierangelo , Greco Gianluigi , Pezzi Vincenzo , Provenzano Michele , Zaza Gianluigi
Published: July 2024

Chronic kidney disease (CKD) represents a significant global health challenge, characterized by kidney damage and decreased function. Its prevalence has steadily increased, necessitating a comprehensive understanding of its epidemiology, risk factors, and management strategies. While traditional prognostic markers such as estimated glomerular filtration rate (eGFR) and albuminuria provide valuable insights, they may not fully capture the complexity of CKD progression and associated cardiovascular (CV) risks.

This paper reviews the current state of renal and CV risk prediction in CKD, highlighting the limitations of traditional models and the potential for integrating artificial intelligence (AI) techniques. AI, particularly machine learning (ML) and deep learning (DL), offers a promising avenue for enhancing risk prediction by analyzing vast and diverse patient data, including genetic markers, biomarkers, and imaging. By identifying intricate patterns and relationships within datasets, AI algorithms can generate more comprehensive risk profiles, enabling personalized and nuanced risk assessments.

Despite its potential, the integration of AI into clinical practice faces challenges such as the opacity of some algorithms and concerns regarding data quality, privacy, and bias. Efforts towards explainable AI (XAI) and rigorous data governance are essential to ensure transparency, interpretability, and trustworthiness in AI-driven predictions.
Hospital and municipal wastewater as a source of carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa in the environment: a review
Authors: Męcik Magdalena , Stefaniak Kornelia , Harnisz Monika , Korzeniewska Ewa
Published: July 2024

The increase in the prevalence of carbapenem-resistant Gram-negative bacteria, in particular Acinetobacter baumannii (CRAB) and Pseudomonas aeruginosa (CRPA), poses a serious threat for public health worldwide. This article reviews the alarming data on the prevalence of infections caused by CRAB and CRPA pathogens and their presence in hospital and municipal wastewater, and it highlights the environmental impact of antibiotic resistance. The article describes the key role of antibiotic resistance genes (ARGs) in the acquisition of carbapenem resistance and sheds light on bacterial resistance mechanisms. The main emphasis was placed on the transfer of ARGs not only in the clinical setting, but also in the environment, including water, soil, and food. The aim of this review was to expand our understanding of the global health risks associated with CRAB and CRPA in hospital and municipal wastewater and to analyze the spread of these micropollutants in the environment. A review of the literature published in the last decade will direct research on carbapenem-resistant pathogens, support the implementation of effective preventive measures and interventions, and contribute to the development of improved strategies for managing this problem.

Graphical Abstract
Rational Optimism
Authors: Wilson Matthew F. , VanderWeele Tyler J.
Published: July 2024

Optimistic beliefs have been criticized by philosophers as being irrational or epistemically deficient. This paper argues for the possibility of a rational optimism. We propose a novel four-fold taxonomy of optimistic beliefs and argue that people may hold optimistic beliefs rationally for at least two of the four types (resourced optimism and agentive optimism). These forms of rational optimism are grounded in facts about one’s resources and agency and may be epistemically justified under certain conditions. We argue that the fourth type of optimism in our taxonomy (perspectival optimism) is not subject to epistemic scrutiny in the same way. It is better evaluated on practical and moral grounds. This paper advances the discussion of optimism within both the philosophical and psychological literatures by providing a compelling and philosophically rich taxonomy of optimism that clarifies the sometimes-competing forms of optimism identified by psychologists. This advances the field by putting forward cases of epistemically justified optimism, in contrast with unrealistic optimism, that is sometimes justified for its instrumental or adaptive characteristics, and also by highlighting a form of optimism, perspectival optimism, that is not being considered in the mainstream optimism literature in psychology. The paper concludes by suggesting several avenues for future empirical and philosophical research.
Mirabai Seeks God: A Journey of Devotional Love and Longing
Authors: Patel Nirali
Published: July 2024

In this paper, I will be discussing, through the lens of this paradox, the experiences of a Hindu devotee of God, the 16th-century poet Mirabai. I will map out some contours of this interaction that seems to be conceptually impossible and yet animates the devotional life. I will explore how Mirabai seeks to transgress, through her poetic expressions alternating with joy and sorrow, the finite realm and somehow contain the divine non-finite reality, namely, Krishna. As we will see, her attempts to engage with Krishna, her non-finite beloved, and generate a loving interaction between herself and Krishna often leads to the disappearance of Krishna which encases her in a spiral of deep suffering and lament. However, it is precisely this agony that enables her to gradually withdraw herself from the finite world and, in turn, immerse herself devotionally in Krishna. I will explore, in the final section, the nature of Mirabai’s devotional victory, and how these moments of suffering, in the experience of separation from Krishna (viraha-bhakti), are yet charged with a liberating power. This spiritual telos allows for a deep devotional connection to be established between her finite self and Krishna, a connection that cannot be articulated straightforwardly on the logical plane.
Photophysical Properties and Photovoltaic Performance of Sensitizers with a Bipyrimidine Acceptor
Authors: Liu Shiling , Gong Kun , Li Wei , Liu Dongzhi , Zhou Xueqin
Published: July 2024

Molecular engineering is a crucial strategy for improving the photovoltaic performance of dye-sensitized solar cells (DSSCs). Despite the common use of the donor–π bridge–acceptor architecture in designing sensitizers, the underlying structure–performance relationship remains not fully understood. In this study, we synthesized and characterized three sensitizers: MOTP-Pyc, MOS2P-Pyc, and MOTS2P-Pyc, all featuring a bipyrimidine acceptor. Absorption spectra, cyclic voltammetry, and transient photoluminescence spectra reveal a photo-induced electron transfer (PET) process in the excited sensitizers. Electron spin resonance spectroscopy confirmed the presence of charge-separated states. The varying donor and π-bridge structures among the three sensitizers led to differences in their conjugation effect, influencing light absorption abilities and PET processes and ultimately impacting the photovoltaic performance. Among the synthesized sensitizers, MOTP-Pyc demonstrated a DSSC efficiency of 3.04%. Introducing an additional thienothiophene block into the π-bridge improved the DSSC efficiency to 4.47% for MOTS2P-Pyc. Conversely, replacing the phenyl group with a thienothiophene block reduced DSSC efficiency to 2.14% for MOS2P-Pyc. Given the proton-accepting ability of the bipyrimidine module, we treated the dye-sensitized TiO2 photoanodes with hydroiodic acid (HI), significantly broadening the light absorption range. This treatment greatly enhanced the short-circuit current density of DSSCs owing to the enhanced electron-withdrawing ability of the acceptor. Consequently, the HI-treated MOTS2P-Pyc-based DSSCs achieved the highest power conversion efficiency of 7.12%, comparable to that of the N719 dye at 7.09%. This work reveals the positive role of bipyrimidine in the design of organic sensitizers for DSSC applications.
Impact of European egg marking system in France: empirical time series analysis between 2017 and 2022
Authors: Bosseaux Jessica , Balcombe Kelvin , Aurier Philippe
Published: July 2024

Voluntary labeling strategies, such as Organic label or Label Rouge, have long been considered as a potential solution to address environmental and social issues in the food sector. As a complement, the European political authorities developed a mandatory marking system for fresh eggs. This article questions the effectiveness of public intervention to support sustainable practices using analysis of the demand for fresh eggs in France. Unit root (augmented Dickey Fuller) tests, stationarity (KPSS) tests, and Seasonal Autoregressive Integrated Moving Average (SARIMA) models are used to investigate the unit root behavior of the prices and expenditure shares of fresh eggs in France between 2017 and 2022. We use the Almost Ideal Demand System model on scanner data to analyze the demand of six eggs’ categories, including mandatory egg codes and two labels (Organic and Label Rouge). The results suggest that a low price does not compensate for low sustainability involvement in eggs from caged farming, favoring free range eggs. Label Rouge shows market weaknesses, while the organic label shows promising results with both a voluntary and a specific mandatory mark. The lack of elasticity observed, except between cage and free range eggs, implies that consumers who choose high-priced products with voluntary labeling strategies are less inclined to switch to alternatives. The mandatory marking system brings more transparency than voluntary labeling initiative, in favor of sustainable products. The case of eggs is a relevant example of how market intervention can push sustainable consumption and production without forbidding products in the market.
Interactions Between Biochar and Nano(Micro)Plastics in the Remediation of Aqueous Media
Authors: Cairns Stuart , Meza-Rojas Diana , Holliman Peter J. , Robertson Iain
Published: July 2024

Plastic is a material that has become ubiquitous since entering the marketplace in the 1930s and 1940s; as a result, the presence of nano and microplastics (NMPs) are pervasive in natural environments affecting air, soil and water ecosystems. These NMPs are varied in size (categorised as either microplastics at 5 mm–1 µm or nanoplastics at < 1 µm), shape and chemical composition. They represent a potential threat to aquatic life and human health through ingestion and inhalation. The toxicity of NMPs is attributed to chemical additives introduced during production and the absorbance of inorganic and organic chemical contaminants in environmental settings. This review is designed to discuss the use of biochar as a natural adsorbent for the remediation of water contaminated with NMPs. Biochar is a sustainable, affordable material which can remediate water and contribute to ecosystem restoration. Whilst it is well established as a material to sorb organic and inorganic contaminants, its use to remove NMPs is in its infancy and as such this review sets out to outline the mechanisms and modifications of biochar to remove NMPs from aqueous environments. Although removal mechanisms in laboratory settings are becoming clearer this review highlights that remediative studies need to be undertaken in conjunction with the systematic investigation of the effect of key environmental parameters on remediation and the use of environmentally aged NMPs. The future direction of this discipline also needs to incorporate field trials alongside laboratory work to develop a stronger understanding of the viability of biochar to remove NMPs from waterways.
Investigation on Heterostructured SeO2–TiO2 Nanofluoroprobe for Highly Selective and Sensitive Detection of a Neonicotinoid Insecticide, Imidacloprid in Soil and Water Matrixes
Authors: Kumar Jitesh , Sharma Aarti , Bansal Priti , Sud Dhiraj , Rai Ritu , Hnydiuk-Stefan Anna
Published: July 2024

Heterostructured SeO2–TiO2 nanoparticles were used as a highly sensitive and selective fluoroprobe for the detection and determination of neonicotinoid insecticide imidacloprid. The sonication-assisted co-precipitation technique was used to create nanoparticles, which were then characterized using UV–Vis, SEM–EDS, HRTEM, XRD, and TGA. These analyses revealed that the nanoparticles had globular morphology, a crystallite size of 14 nm, a bandgap of 2.45 eV, and stability at high temperatures. Fluorescence emission at 548 nm wavelength exhibits high sensitivity and selectivity for imidacloprid over other pesticides with complete fluorescent quenching at 2 × 10–4 M concentration of imidacloprid. Stern–Volmer equation and thermodynamic parameters applied to the experimental data over a temperature range of 20–50 °C provide the Ksv value in the range of 1.56 × 105 to 2.69 × 105 M−1 and indicate strong interactions, dynamic, spontaneous, and endothermic quenching process. Furthermore, the excellent salient features and notably the unaffected performance even in the presence of various anions, fertilizer, and binary mixture of pesticides often sprayed on plants, will pave the way for the development of rapid, affordable, selective fluoroprobe for onsite monitoring of imidacloprid. The reliability for determination is also examined for spiked soil samples to develop a hybrid SeO2–TiO2 nanoparticles fluoroprobe as a simple alternative to existing techniques for the detection of imidacloprid.

Graphical Abstract
Bacterial barriers
Authors: Guasto Jeffrey S.
Published: July 2024

Microbes play a primary role in wide-ranging biogeochemical and physiological processes, where ambient fluid flows are responsible for cell dispersal as well as mixing of dissolved resources, signalling molecules and biochemical products. Determining the simultaneous (and often coupled) transport properties of actively swimming cells together with passive scalars is key to understanding and ultimately predicting these complex processes. In recent work, Ran & Arratia (J. Fluid Mech., vol. 988, 2024, A25) present the striking observation that dilute concentrations of swimming bacteria severely hinder scalar transport through Lagrangian vortex boundaries in a chaotic flow. Analysis of rotation-dominated regions suggests that local accumulation of bacteria enhances the strength of transport barriers and highlights the role of understudied elliptical Lagrangian coherent structures in bacterial and multicomponent transport.
On the relevance of lift force modelling in turbulent wall flows with small inertial particles
Authors: Gao Wei , Shi Pengyu , Parsani Matteo , Costa Pedro
Published: July 2024

In particle-laden turbulent wall flows, lift forces can influence the near-wall turbulence. This has been observed recently in particle-resolved simulations, which, however, are too expensive to be used in upscaled models. Instead, point-particle simulations have been the method of choice to simulate the dynamics of these flows during the last decades. While this approach is simpler, cheaper and physically sound for small inertial particles in turbulence, some issues remain. In the present work, we address challenges associated with lift force modelling in turbulent wall flows and the impact of lift forces in the near-wall flow. We performed direct numerical simulations of small inertial point particles in turbulent channel flow for fixed Stokes number and mass loading while varying the particle size. Our results show that the particle dynamics in the buffer region, causing the apparent particle-to-fluid slip velocity to vanish, raises major challenges for modelling lift forces accurately. While our results confirm that lift forces have little influence on particle dynamics for sufficiently small particle sizes, for inner-scaled diameters of order one and beyond, lift forces become quite important near the wall. The different particle dynamics under lift forces results in the modulation of streamwise momentum transport in the near-wall region. We analyse this lift-induced turbulence modulation for different lift force models, and the results indicate that realistic models are critical for particle-modelled simulations to correctly predict turbulence modulation by particles in the near-wall region.
Tracking the Evolution of Snow Drought in the U.S. Pacific Northwest at Variable Scales
Authors: Roberts‐Pierel B. M. , Raleigh M. S. , Kennedy R. E.
Published: July 2024

Long‐term and year‐to‐year changes in climate can cause anomalously warm and/or dry conditions, leading to periods with snowfall deficits known as snow droughts. How the occurrence of distinct types of snow drought has evolved at different spatial and temporal scales is not well understood. Here, we investigate how snow droughts and associated seasonal snow conditions vary subseasonally in the US Pacific Northwest. We specifically consider differences with spatial unit (point vs. river basin), data set and intra‐annual timing of snow drought. Data sets included in the research come from in situ observations, gridded model outputs and optical remote sensing. We found that overall, snow drought occurrences have increased 10%–15% over the last 30 years based on decadal counts, but the change was non‐uniform across snow drought types and winter periods. Our research showed a decrease in dry snow droughts but an increase in warm/dry snow droughts according to in situ observations and only a modest increase in the model record. We also found that dry snow droughts were more prevalent in the eastern portion of our study region while warm/dry snow droughts were generally more common in the western part of the study area. With optical remote sensing data, it was possible to identify warm/dry snow drought conditions in the mid to late winter (January–May), but not possible to distinguish other types of snow drought in the early winter. This research points to the importance of data set choice, spatial resolution and spatial/temporal aggregation when selecting parameters for snow drought research.
Hydrological Drought‐To‐Flood Transitions Across Different Hydroclimates in the United States
Authors: Götte Jonas , Brunner Manuela I.
Published: July 2024

Floods following on streamflow droughts can have severe impacts. While they have been prominently featured by the media in recent years, we know little about their spatio‐temporal variability. In this study, we analyze the occurrence and drivers of such drought‐to‐flood transitions by calculating transition lengths from droughts to floods for natural and regulated catchments across the Contiguous United States between 1970 and 2022. We find that drought‐to‐flood transitions strongly vary in their lengths and their spatial distribution. We identify snowmelt as the main driver of transitions in high‐elevation catchments, while transitions in low‐elevation catchments are more variable in their time of occurrence and drivers. Reservoir management reduces the number of short drought‐to‐flood transitions, particularly in catchments with a high amount of snow where snowmelt is crucial for filling reservoirs in early summer. These findings suggest that projected changes in the snowmelt season will lead to changes in transitions from streamflow droughts to floods and that reservoir management may be used to adapt to these changes.
Sea Spray Aerosol Over the Remote Oceans Has Low Organic Content
Authors: Lawler Michael J. , Schill Gregory P. , Brock Charles A. , Froyd Karl D. , Williamson Christina , Kupc Agnieszka , Murphy Daniel M.
Published: July 2024

Biogenic organic compounds in the surface ocean may significantly alter the cloud‐forming ability of sea spray aerosol and thereby affect the amount of solar radiation reaching the ocean surface. Estimates of the organic mass fraction of sea spray vary widely, and some results show a significant dependence on biological activity in the source seawater. We present airborne observations of the organic mass fraction of individual sea spray particles measured using the Particle Analysis by Laser Mass Spectrometry (PALMS) instrument during the Atmospheric Tomography (ATom) mission, which sampled a wide range of latitudes and altitudes over the remote Atlantic and Pacific Oceans across four seasons, from the marine boundary layer to the upper troposphere. The measured sea spray particles of about 0.15–0.7 μm dry diameter showed higher average organic mass fractions at smaller sizes, but values were low overall, with regional integrated submicron means almost always <10%. Atmospheric aging adds organics to sea spray particles, leading to higher mean organic mass fractions (sometimes exceeding 50%) in the free troposphere than in the marine boundary layer. The average submicron sea spray organic mass fractions are on the low end of previously reported values and show weak seasonal variability for most regions. These results imply that recent biological activity in the surface ocean has only weak control over how much organic matter is in nascent submicron sea spray particles over the remote oceans, in contrast to findings from some observational studies and global numerical simulations.
Record High Sea Surface Temperatures in 2023
Authors: Huang Boyin , Yin Xungang , Carton James A. , Chen Ligang , Graham Garrett , Hogan Patrick , Smith Thomas , Zhang Huai‐Min
Published: July 2024

NOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) and other similar sea surface temperature (SST) products indicate that the globally averaged SST set a new daily record in March 2023. The record‐high SST in March was immediately broken in April, and new daily records were set again in July and August 2023. The SST anomaly (SSTA) persisted at a record high from mid‐March to the remainder of 2023. Our analysis indicates that the record‐high SSTs, and associated marine heatwaves (MHWs) and even super‐MHWs, are attributed to three factors: (a) a long‐term warming trend, (b) a shift to the warm phase of the multi‐decadal Pacific‐Atlantic‐Arctic (PAA) mode, and (c) the transition from the triple‐dip succession of La Niña events to the 2023–24 El Niño event.
A Novel Connectivity Metric of Identified Multi‐Cluster Fracture Networks in Permeable Formations
Authors: Zhu Weiwei , He Xupeng , Patzek Tadeusz Wiktor , Chen Zhiqiang , Hoteit Hussein , Elsworth Derek , Qi Shengwen , Wang Moran
Published: July 2024

Complex natural fracture networks typically consist of multiple clusters, whose connectivity is rarely quantified. Therefore, for each identified fracture network, we propose a connectivity metric that accounts for individual fracture clusters and their interactions. This metric evaluates contributions from all fracture clusters, considering their relative sizes and interactions among the isolated clusters, which in turn depend on the hydraulic conductance of the interconnecting rock matrix. Furthermore, we investigate how the system connectivity depends on fracture sealing, alterations of central clusters, and cluster linkage. Fracture sealing strongly impacts overall fracture connectivity, with 5 percent of sealed fractures reducing connectivity by 20 percent. The connectivity reduction is small when transitioning the central cluster from the largest to the smallest one. However, the largest cluster significantly contributes to overall connectivity, while the smallest one contributes minimally. Natural fracture networks increase connectivity by linking more clusters, with heterogeneity and anisotropy playing pivotal roles.
Fault (Re)Activation and Fluid‐Induced Seismicity: An Example From the Val d’Agri Intermontane Basin (Southern Italy)
Authors: Lavecchia Alessio , Serlenga Vincenzo , Filippucci Marilena , Stabile Tony Alfredo , Prosser Giacomo , Tallarico Andrea
Published: July 2024

Fluid‐induced seismicity has been a particularly emphasized mechanism over the last few years, especially after fluid‐related, moderate‐to‐large earthquakes have been observed in several locations around the globe. Several studies suggest that the relationships between seismicity and fluid presence are related to variations in the stress state of rocks, due to the increase or drop of the pore fluid pressure. In this scenario, the Val d’Agri represents a precious case study where fluid‐induced seismicity is observed. In this area, two seismic clusters are observed in the Apulian Carbonate Platform, caused by (a) wastewater reinjection that reactivated the Costa Molina Fault blind thrust, and (b) seasonal water loading from the Pertusillo reservoir. The mechanisms behind these reactivated faults' evolution are still uncertain, especially in the compressive/extensional tectonic setting characterizing the area's evolution. Consequently, the distribution of the seismic potential in the region is largely unconstrained. We constructed a numerical thermo‐mechanical model to identify the main mechanisms that promoted the Val d’Agri present‐day tectonic setting and to assess the seismic hazard characterizing this region. We show that deformation within the Sedimentary Cover and the Crystalline Basement decoupled along a major décollement layer, represented by the Triassic Burano Formation. We also estimate the Coulomb stress (σC) in the region, assessing the crust's potential to generate earthquakes. Our results suggest that σC > 0 in a large part of the crust, and therefore that fluid injection may be particularly effective for the reactivation of buried structures, especially at a depth between ≃2 and ≃6 km.
Micro‐Thermomechanical Modeling of Rocks With Temperature‐Dependent Friction and Damage Laws
Authors: Lv Zhaomin , Ren Lu , Lai Yuanming , Zhao Lunyang
Published: July 2024

Temperature serves as a critical yet elusive factor impacting the mechanical properties of deep rocks. In this work, we shall develop a new micro‐thermomechanical model for rocks based on the Mori‐Tanaka homogenization scheme. Free energy and thermodynamic forces are deduced within the framework of irreversible thermodynamics, including the local stress applied on the mesocracks, damage driving force, macroscopic stress, and entropy. The salient innovation of this study lies in formulating subtle physically based temperature‐dependent friction and damage laws, considering the influence of ambient temperature on the mesocracking in rocks. Through a coupled friction‐damage analysis, a temperature‐dependent quasi‐static strength criterion and analytical stress‐strain‐damage relations are then derived. Physical implications and calibration methods of each parameter in the proposed model are meticulously presented. Furthermore, a semi‐implicit plasticity damage decoupled procedure (SIPDDC) integration algorithm is employed for the numerical implementation of the proposed model. Subsequently, numerical simulations are conducted to obtain the mechanical response of Jinping marble, Beibei sandstone, and Gongjue granite under various real‐time temperature‐confining pressure coupling conventional triaxial compression tests (TP‐CTC). The congruence of stress‐strain curves between model predictions and experimental data validates the robust performance and potential applicability of the proposed model.
Orbital‐Scale Global Ocean Sea Surface Temperatures Coupling With Cryosphere‐Carbon Cycle Changes Over the Past 4 Million Years
Authors: Zhang Ze , Rohling Eelco J. , Kemp David B. , Wang Zhixiang , Huang Chunju
Published: July 2024

Changes in the thermal conditions of the ocean surface, the interface for air‐sea exchange, are critical for understanding global climate and environmental change. Here we explore the evolution of sea surface temperature (SST) and the meridional SST gradient (STG) at orbital timescales since 4 million years ago (Ma), along with interactions between SSTs, the cryosphere, and the global carbon cycle. We observe orbital eccentricity and obliquity influences on SST evolution and infer that SST changes may have played a key role in atmospheric CO2 and cryosphere changes through key climate transitions in the past 4 Ma. We find a major equator‐to‐pole STG increase in the Northern Hemisphere (NH) close to the initiation of major NH glaciation (at ∼2.7 Ma). In addition, we find substantial increases in the obliquity sensitivity (Sobl) of NH STG at ∼2.7 Ma and in Southern Hemisphere (SH) STG at ∼1 Ma, which may be responses to important expansions of NH and SH ice sheets, respectively. Phase analysis shows that SST changes typically lead global ice volume changes throughout the last 4 Ma. SST changes also lead atmospheric CO2 changes since ∼1.5 Ma, which indicates that SST changes either drove, or directly reflect, processes that changed ocean‐atmosphere carbon exchange and, thus, atmospheric CO2 concentrations. Overall, our study emphasizes that SST changes were a critical component of climate change throughout the last 4 Ma.
Non-Hermitian dynamics and non-reciprocity of optically coupled nanoparticles
Authors: Reisenbauer Manuel , Rudolph Henning , Egyed Livia , Hornberger Klaus , Zasedatelev Anton V. , Abuzarli Murad , Stickler Benjamin A. , Delić Uroš
Published: July 2024

Non-Hermitian dynamics, as observed in photonic, atomic, electrical and optomechanical platforms, holds great potential for sensing applications and signal processing. Recently, fully tuneable non-reciprocal optical interaction has been demonstrated between levitated nanoparticles. Here we use this tunability to investigate the collective non-Hermitian dynamics of two non-reciprocally and nonlinearly interacting nanoparticles. We observe parity–time symmetry breaking and, for sufficiently strong coupling, a collective mechanical lasing transition in which the particles move along stable limit cycles. This work opens up a research avenue of non-equilibrium multi-particle collective effects, tailored by the dynamic control of individual sites in a tweezer array.
A hybrid recommendation algorithm based on user nearest neighbor model
Authors: Lv Sheng , Wang Jiabin , Deng Fan , Yan Penggui
Published: July 2024

In the realm of e-commerce, personalized recommendations are a crucial component in enhancing user experience and optimizing sales efficiency. To address the inherent sparsity challenge prevalent in collaborative filtering algorithms within personalized recommendation systems, we propose a novel hybrid e-commerce recommendation algorithm based on the User-Nearest-Neighbor model. By integrating the user nearest neighbor model with other recommendation algorithms, this approach effectively mitigates data sparsity and facilitates a more nuanced understanding of the user-product relationship, consequently elevating recommendation quality and enhancing user experience. Taking into account considerations such as data scale and recommendation performance, we conducted experiments utilizing the Spark distributed platform. Empirical findings demonstrate the superiority of our hybrid algorithm over standalone collaborative filtering algorithms across various recommendation indicators.
Use of low cost near-infrared spectroscopy, to predict pasting properties of high quality cassava flour
Authors: Abubakar Mikidadi , Wasswa Peter , Masumba Esther , Ongom Patrick , Mkamilo Geoffrey , Kanju Edward , Abincha Wilfred , Edema Richard , Sichalwe Karoline , Tukamuhabwa Phinehas , Kayondo Siraj , Rabbi Ismail , Kulembeka Heneriko
Published: July 2024

Determination of pasting properties of high quality cassava flour using rapid visco analyzer is expensive and time consuming. The use of mobile near infrared spectroscopy (SCiO™) is an alternative high throughput phenotyping technology for predicting pasting properties of high quality cassava flour traits. However, model development and validation are necessary to verify that reasonable expectations are established for the accuracy of a prediction model. In the context of an ongoing breeding effort, we investigated the use of an inexpensive, portable spectrometer that only records a portion (740–1070 nm) of the whole NIR spectrum to predict cassava pasting properties. Three machine-learning models, namely glmnet, lm, and gbm, implemented in the Caret package in R statistical program, were solely evaluated. Based on calibration statistics (R2, RMSE and MAE), we found that model calibrations using glmnet provided the best model for breakdown viscosity, peak viscosity and pasting temperature. The glmnet model using the first derivative, peak viscosity had calibration and validation accuracy of R2 = 0.56 and R2 = 0.51 respectively while breakdown had calibration and validation accuracy of R2 = 0.66 and R2 = 0.66 respectively. We also found out that stacking of pre-treatments with Moving Average, Savitzky Golay, First Derivative, Second derivative and Standard Normal variate using glmnet model resulted in calibration and validation accuracy of R2 = 0.65 and R2 = 0.64 respectively for pasting temperature. The developed calibration model predicted the pasting properties of HQCF with sufficient accuracy for screening purposes. Therefore, SCiO™ can be reliably deployed in screening early-generation breeding materials for pasting properties.
A chatbot based question and answer system for the auxiliary diagnosis of chronic diseases based on large language model
Authors: Zhang Sainan , Song Jisung
Published: July 2024

In recent years, artificial intelligence has made remarkable strides, improving various aspects of our daily lives. One notable application is in intelligent chatbots that use deep learning models. These systems have shown tremendous promise in the medical sector, enhancing healthcare quality, treatment efficiency, and cost-effectiveness. However, their role in aiding disease diagnosis, particularly chronic conditions, remains underexplored. Addressing this issue, this study employs large language models from the GPT series, in conjunction with deep learning techniques, to design and develop a diagnostic system targeted at chronic diseases. Specifically, performed transfer learning and fine-tuning on the GPT-2 model, enabling it to assist in accurately diagnosing 24 common chronic diseases. To provide a user-friendly interface and seamless interactive experience, we further developed a dialog-based interface, naming it Chat Ella. This system can make precise predictions for chronic diseases based on the symptoms described by users. Experimental results indicate that our model achieved an accuracy rate of 97.50% on the validation set, and an area under the curve (AUC) value reaching 99.91%. Moreover, conducted user satisfaction tests, which revealed that 68.7% of participants approved of Chat Ella, while 45.3% of participants found the system made daily medical consultations more convenient. It can rapidly and accurately assess a patient’s condition based on the symptoms described and provide timely feedback, making it of significant value in the design of medical auxiliary products for household use.
Conversational presentation mode increases credibility judgements during information search with ChatGPT
Authors: Anderl Christine , Klein Stefanie H. , Sarigül Büsra , Schneider Frank M. , Han Junyi , Fiedler Paul L. , Utz Sonja
Published: July 2024

People increasingly use large language model (LLM)-based conversational agents to obtain information. However, the information these models provide is not always factually accurate. Thus, it is critical to understand what helps users adequately assess the credibility of the provided information. Here, we report the results of two preregistered experiments in which participants rated the credibility of accurate versus partially inaccurate information ostensibly provided by a dynamic text-based LLM-powered agent, a voice-based agent, or a static text-based online encyclopedia. We found that people were better at detecting inaccuracies when identical information was provided as static text compared to both types of conversational agents, regardless of whether information search applications were branded (ChatGPT, Alexa, and Wikipedia) or unbranded. Mediation analysis overall corroborated the interpretation that a conversational nature poses a threat to adequate credibility judgments. Our research highlights the importance of presentation mode when dealing with misinformation.