bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractHeterostructured 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
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

AbstractLong‐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

AbstractFloods 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

AbstractBiogenic 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

AbstractNOAA 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

AbstractComplex 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

AbstractFluid‐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

AbstractTemperature 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

AbstractChanges 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

AbstractNon-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

AbstractIn 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

AbstractDetermination 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

AbstractIn 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

AbstractPeople 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.
Non-invasive mapping of brown adipose tissue activity with magnetic resonance imaging
Authors: Cai Zimeng , Zhong Qiaoling , Feng Yanqiu , Wang Qian , Zhang Zuoman , Wei Cailv , Yin Zhinan , Liang Changhong , Liew Chong Wee , Kazak Lawrence , Cypess Aaron M. , Liu Zaiyi , Cai Kejia 
Published: July 2024

AbstractThermogenic brown adipose tissue (BAT) has a positive impact on whole-body metabolism. However, in vivo mapping of BAT activity typically relies on techniques involving ionizing radiation, such as [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) and computed tomography (CT). Here we report a noninvasive metabolic magnetic resonance imaging (MRI) approach based on creatine chemical exchange saturation transfer (Cr-CEST) contrast to assess in vivo BAT activity in rodents and humans. In male rats, a single dose of the β3-adrenoceptor agonist (CL 316,243) or norepinephrine, as well as cold exposure, triggered a robust elevation of the Cr-CEST MRI signal, which was consistent with the [18F]FDG PET and CT data and 1H nuclear magnetic resonance measurements of creatine concentration in BAT. We further show that Cr-CEST MRI detects cold-stimulated BAT activation in humans (both males and females) using a 3T clinical scanner, with data-matching results from [18F]FDG PET and CT measurements. This study establishes Cr-CEST MRI as a promising noninvasive and radiation-free approach for in vivo mapping of BAT activity.