bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative analysis of simulation approaches for predicting permeability and compressive strength in pervious concrete
Authors: Ahmad Soran Abdrahman , Ahmed Hemn Unis , Rafiq Serwan Khurshid , Jafer Frya Shawkat , Fqi Kawa Omar 
Published: June 2024

AbstractPorous concrete plays a crucial role in addressing various environmental challenges and mitigating the impacts of climate change. It proves effective in reducing issues such as flooding, heat phenomena in the earth, and groundwater decline. Typically devoid of sand content, porous concrete’s key attributes lie in its permeability and compressive strength. Accurate prediction of these properties is essential for cost and time savings, ensuring precise proportions of materials in the concrete mixture. This article explores different models, including the linear model (LR), nonlinear model (NLR), and Artificial Neural Network (ANN), to predict and estimate permeability and compressive strength in porous concrete. The analysis incorporates 139 samples from various papers and experimental studies, utilizing significant parameters and variables like water-to-cement ratio, coarse aggregate content, cement content, porosity, and curing time as input variables. Statistical assessments, such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Scatter Index (SI), OBJ value, and coefficient of determination (R2), are employed to assess model performance. The results reveal that the ANN model outperforms other models in forecasting permeability and compressive strength of porous concrete. The SI and OBJ value of the ANN model are lower than those of all other models, indicating superior performance. The robust performance of the ANN model has significant implications for construction applications, ensuring precise material proportions and contributing to the durability of porous concrete structures. The success of the ANN model suggests avenues for refinement, including architecture adjustments and dataset expansion. These findings offer valuable insights into the ongoing efforts to optimize simulation techniques for predicting key properties of construction materials. On the other hand, the use of these models to optimize concrete mix design not only enhances efficiency but also significantly conserves raw materials and reduces energy consumption. These advancements contribute to lowering carbon emissions and promoting sustainable practices in the construction industry.
The stability of single-atom catalysts in thermocatalysis
Authors: Chae Sudong , Chen Yi , Yang Ji , Su Ji 
Published: June 2024

AbstractSingle-atom catalysts (SACs) featuring 100% atom utilization and uniform isolated active sites have been receiving sustainable attention over the last decade, as they offer exceptional performance in various catalytic applications. The motivation behind studying SACs is to develop highly active, selective, and stable catalysts for industrial applications with desirable economic and ecological benefits. Despite their promising potential, SACs face challenges related to stability, which need to be addressed for practical implementation. In this mini-review we discuss the existing stability issues of SACs, and summarize the deactivation mechanism and behaviors, protective strategies, and regeneration methods of SACs. We highlighted the challenges and prospects of future SACs study, aiming to pave the way for their widespread application in industrial processes.
Characteristic Slow‐Slip Events on the Superstition Hills Fault, Southern California
Authors: Vavra Ellis J. , Fialko Yuri , Rockwell Thomas , Bilham Roger , Štěpančíková Petra , Stemberk Jakub , Tábořík Petr , Stemberk Josef 
Published: June 2024

AbstractThe Superstition Hills Fault (SHF) exhibits a rich spectrum of slip modes, including M 6+ earthquakes, afterslip, quasi‐steady creep, and both triggered and spontaneous slow slip events (SSEs). Following 13 years of quiescence, creepmeters recorded 25 mm of slip during 16–19 May 2023. Additional sub‐events brought the total slip to 41 mm. The event nucleated on the northern SHF in early‐May and propagated bi‐laterally at rates on the order of kilometers per day. Surface offsets reveal a bi‐modal slip distribution, with slip on the northern section of the fault being less localized and lower amplitude compared to the southern section. Kinematic slip models confirm systematic variations in the slip distribution along‐strike and with depth and suggest that slip is largely confined to the shallow sedimentary layer. Observations and models of the 2023 SSE bear a strong similarity to previous slip episodes in 1999, 2006, and 2010, suggesting a characteristic behavior.
Revisiting Winter Southern Ocean CO2 Uptake Based on CALIPSO Observations
Authors: Huang Hao , Zhang Ke , Zhang Zhaoru , Smith Walker , He Jianfeng , Liu Na , Le Chengfeng 
Published: June 2024

AbstractThe absorption of atmospheric carbon dioxide (CO2) in the Southern Ocean represents a critical component of the global oceanic carbon budget. Previous assessments of air‐sea carbon flux variations and long‐term trends in polar regions during winter have faced limitations due to scarce field data and the lack of ocean color satellite imagery, causing uncertainties in estimating CO2 flux estimation. This study utilized the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite to construct a continuous 16‐year (2006–2021) time series of sea surface partial pressure of CO2 (pCO2) in the Southern Ocean. Our findings revealed that the polar region in South Ocean acts as a carbon sink in winter, with CO2 flux of ∼30 TgC in high‐latitude areas (South of 50°S). This work highlights the efficacy of active remote sensing for monitoring sea surface pCO2 and contributes insights into the dynamic carbonate systems of the Southern Ocean.
Evaluating Cosmic Ray Neutron Sensor Estimates of Snow Water Equivalent in a Prairie Environment Using UAV Lidar
Authors: Woodley M. , Kim H. , Sproles E. , Eberly J. , Tuttle S. 
Published: June 2024

AbstractMonitoring snow cover in prairie environments is important for understanding water and energy fluxes, agricultural production, and flooding, but difficult due to shallow snowpack and considerable snow heterogeneity. Cosmic ray neutron sensors (CRNS) are sensitive to snow within a radius of 150–250 m, which allows for continuous estimation of snow water equivalent (SWE) over a large footprint and may better represent area‐averaged snow cover in prairies than conventional SWE instruments, such as snow pillows. A CRNS was installed at Montana State University's Central Agricultural Research Center (CARC; 47.06°, −109.95°) in Moccasin, MT in coordination with NASA's SnowEx 2021 field campaign. This work assesses the feasibility of a CRNS for SWE monitoring in prairies by comparing CRNS SWE estimates to spatially distributed SWE derived from uninhabited aerial vehicle lidar snow depths within the sensor's footprint and manual snow pit measurements. Lidar observations show snow cover was highly spatially variable, with the largest snow accumulation near barriers and the least in barren fields. Additionally, we evaluate our CRNS SWE estimates using Ultra Rapid Neutron Only Simulation (URANOS) Monte Carlo simulations. Comparisons of SWE estimates derived from lidar, CRNS, and URANOS for shallow snowpack at the site yielded root mean square values of about 2 mm (approximately 30% of the mean SWE). These results suggest that the CRNS is effective at integrating over significant spatial variability within its footprint at this site. However, the spatial distribution of snow exerts a strong influence on the CRNS signal and must be considered when interpreting CRNS observations.
Salinity Profiles in Coastal Aquifers: A Characterization Framework for Field Measurements
Authors: Huang Xinran , Werner Adrian D. , Solórzano‐Rivas S. Cristina , Jazayeri Amir 
Published: June 2024

AbstractThe freshwater‐seawater mixing zone (“interface”) is affected by tides, seawater intrusion, submarine groundwater discharge and aquifer heterogeneities. Our current understanding is based primarily on theoretical studies involving numerical simulation and sand‐tank experimentation, with limited field analyses of interface characteristics in coastal aquifers that serve as important freshwater reservoirs. The most common field evidence for interface characteristics is derived from electrical conductivity (EC) profiles, often obtained from long‐screen wells. However, the EC profiles from long‐screen wells have been assessed previously using only simple statistics like the depth to 50% of seawater concentration. This study introduces a methodology for characterizing EC profiles using curve fitting and objective assessment of multiple interface attributes, with application to 170 EC profiles from the Lower Burdekin Delta, Australia. The adopted fitting function showed an excellent match (mean R2 = 0.99). Fitting parameters were linked to the curvatures of transitions from fresh to brackish water and from brackish water to seawater, the elevation and gradient of the mid‐salinity value, and the thickness of the mixing zone. Field EC profiles showed approximately linear relationships between head changes averaged over the previous 5 months and the elevation of 5 mS/cm isochlor for some wells. The slope of this relationship was approximately one, which is approximately 1/40th of the value arising from the Ghyben‐Herzberg relation. The framework for characterizing salinity profiles presented in this article offers a new, objective approach for investigating the interface, providing future studies with a technique for examining relationships between interface behavior and key controlling forces.
Ketamine induced synaptic plasticity operates independently of long-term potentiation
Authors: Piazza Michelle K. , Kavalali Ege T. , Monteggia Lisa M. 
Published: June 2024

AbstractSynaptic plasticity occurs via multiple mechanisms to regulate synaptic efficacy. Homeostatic and Hebbian plasticity are two such mechanisms by which neuronal synapses can be altered. Although these two processes are mechanistically distinct, they converge on downstream regulation of AMPA receptor activity to modify glutamatergic neurotransmission. However, much remains to be explored regarding how these two prominent forms of plasticity interact. Ketamine, a rapidly acting antidepressant, increases glutamatergic transmission via pharmacologically-induced homeostatic plasticity. Here, we demonstrate that Hebbian plasticity mechanisms are still intact in synapses that have undergone homeostatic scaling by ketamine after either systemic injection or perfusion onto hippocampal brain slices. We also investigated this relationship in the context of stress induced by chronic exposure to corticosterone (CORT) to better model the circumstances under which ketamine may be used as an antidepressant. We found that CORT induced an anhedonia-like behavioral phenotype in mice but did not impair long-term potentiation (LTP) induction. Furthermore, corticosterone exposure does not impact the intersection of homeostatic and Hebbian plasticity mechanisms, as synapses from CORT-exposed mice also demonstrated intact ketamine-induced plasticity and LTP in succession. These results provide a mechanistic explanation for how ketamine used for the treatment of depression does not impair the integrity of learning and memory processes encoded by mechanisms such as LTP.
Dependence on mitochondrial respiration of malignant T cells reveals a new therapeutic target for angioimmunoblastic T-cell lymphoma
Authors: Krug Adrien , Mhaidly Rana , Tosolini Marie , Mondragon Laura , Tari Gamze , Turtos Adriana Martinez , Paul-Bellon Rachel , Asnafi Vahid , Marchetti Sandrine , Di Mascio Léa , Travert Marion , Bost Frédéric , Bachy Emmanuel , Argüello Rafael J. , Fournié Jean-Jacques , Gaulard Philippe , Lemonnier François , Ricci Jean-Ehrland , Verhoeyen Els 
Published: June 2024

AbstractCancer metabolic reprogramming has been recognized as one of the cancer hallmarks that promote cell proliferation, survival, as well as therapeutic resistance. Up-to-date regulation of metabolism in T-cell lymphoma is poorly understood. In particular, for human angioimmunoblastic T-cell lymphoma (AITL) the metabolic profile is not known. Metabolic intervention could help identify new treatment options for this cancer with very poor outcomes and no effective medication. Transcriptomic analysis of AITL tumor cells, identified that these cells use preferentially mitochondrial metabolism. By using our preclinical AITL mouse model, mimicking closely human AITL features, we confirmed that T follicular helper (Tfh) tumor cells exhibit a strong enrichment of mitochondrial metabolic signatures. Consistent with these results, disruption of mitochondrial metabolism using metformin or a mitochondrial complex I inhibitor such as IACS improved the survival of AITL lymphoma-bearing mice. Additionally, we confirmed a selective elimination of the malignant human AITL T cells in patient biopsies upon mitochondrial respiration inhibition. Moreover, we confirmed that diabetic patients suffering from T-cell lymphoma, treated with metformin survived longer as compared to patients receiving alternative treatments. Taking together, our findings suggest that targeting the mitochondrial metabolic pathway could be a clinically efficient approach to inhibit aggressive cancers such as peripheral T-cell lymphoma.
The spectrum of giant cell arteritis through a rheumatology lens
Authors: Khalique Muhammad Irfan , Arjunan Mousindha , Wood Samuel , Mackie Sarah L. 
Published: June 2024

AbstractTreatment of giant cell arteritis (GCA) aims initially to prevent acute visual loss, and subsequently to optimise long-term quality of life. Initial prevention of acute visual loss in GCA is well-standardised with high-dose glucocorticoid therapy but in the longer term optimising quality of life requires tailoring of treatment to the individual. The licensing of the IL-6 receptor inhibitor tocilizumab combined with advances in vascular imaging have resulted in many changes to diagnostic and therapeutic practice. Firstly, GCA is a systemic disease that may involve multiple vascular territories and present in diverse ways. Broadening of the “spectrum” of what is called GCA has been crystallised in the 2022 GCA classification criteria. Secondly, the vascular inflammation of GCA frequently co-exists with the extracapsular musculoskeletal inflammation of the related disease, polymyalgia rheumatica (PMR). Thirdly, GCA care must often be delivered across multiple specialities and healthcare organisations requiring effective interprofessional communication. Fourthly, both GCA and PMR may follow a chronic or multiphasic disease course; long-term management must be tailored to the individual patient’s needs. In this article we focus on some areas of current rheumatology practice that ophthalmologists need to be aware of, including comprehensive assessment of extra-ocular symptoms, physical signs and laboratory markers; advanced imaging techniques; and implications for multi-speciality collaboration.
Climate and urbanization drive changes in the habitat suitability of Schistosoma mansoni competent snails in Brazil
Authors: Glidden Caroline K. , Singleton Alyson L. , Chamberlin Andrew , Tuan Roseli , Palasio Raquel G. S. , Caldeira Roberta Lima , Monteiro Antônio Miguel V. , Lwiza Kamazima M. M. , Liu Ping , Silva Vivian , Athni Tejas S. , Sokolow Susanne H. , Mordecai Erin A. , De Leo Giulio A. 
Published: June 2024

AbstractSchistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria and Bulinus snails, thus controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we used machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of forward-transmitting Biomphalaria hosts throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution—while accounting for non-linearities that are difficult to detect from local case studies—can help inform schistosomiasis control strategies.
Camrelizumab-based induction chemoimmunotherapy in locally advanced stage hypopharyngeal carcinoma: phase II clinical trial
Authors: Gong Hongli , Tian Shu , Ding Hao , Tao Lei , Wang Li , Wang Jie , Wang Tian , Yuan Xiaohui , Heng Yu , Zhang Ming , Shi Yong , Xu Chengzhi , Wu Chunping , Wang Shengzi , Zhou Liang 
Published: June 2024

AbstractThis phase II trial aimed to determine the efficacy and safety of induction chemoimmunotherapy of camrelizumab plus modified TPF in locally advanced hypopharyngeal squamous cell carcinoma (LA HSCC) (NCT04156698). The primary endpoint was objective response rate (ORR), and secondary endpoints were 3-year overall survival (OS), progression-free survival (PFS), larynx preservation rate (LPR), and metastasis-free survival (MFS). Patients (cT3-4aN0-2M0), regardless of sex, received induction chemoimmunotherapy for three cycles: camrelizumab 200 mg d1, docetaxel 75 mg/m2 d1, cisplatin 25 mg/m2 d1-3, and capecitabine 800 mg/m2 bid d1-14, q21d. Patients were assigned to radioimmunotherapy if they had a complete or partial response, those with stable or progressive disease underwent surgery and adjuvant (chemo)radiotherapy. Camrelizumab was maintained post-radioimmunotherapy. Fifty-one patients were enrolled with a median follow-up duration of 23.7 months. After induction therapy, the ORR was 82.4% (42/51), meeting the prespecified endpoint. Grade 3/4 adverse events occurred in 26 patients, and no treatment-related death occurred. As three-year outcomes were immature, two-year OS, PFS and LPR were reported. As no distant metastatic event had occurred, MFS was not reported here. The two-year OS, PFS, and LPR rates were 83.0%, 77.1%, and 70.0%, respectively. The induction chemoimmunotherapy of camrelizumab plus TPF showed a high ORR rate with an acceptable safety profile in LA HSCC.
A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data
Authors: Chen Minhui , Dahl Andy 
Published: June 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) has been widely used to characterize cell types based on their average gene expression profiles. However, most studies do not consider cell type-specific variation across donors. Modelling this cell type-specific inter-individual variation could help elucidate cell type-specific biology and inform genes and cell types underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 85 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to illuminate cell type-specific biology in scRNA-seq.
Small molecule in situ resin capture provides a compound first approach to natural product discovery
Authors: Bogdanov Alexander , Salib Mariam N. , Chase Alexander B. , Hammerlindl Heinz , Muskat Mitchell N. , Luedtke Stephanie , da Silva Elany Barbosa , O’Donoghue Anthony J. , Wu Lani F. , Altschuler Steven J. , Molinski Tadeusz F. , Jensen Paul R. 
Published: June 2024

AbstractCulture-based microbial natural product discovery strategies fail to realize the extraordinary biosynthetic potential detected across earth’s microbiomes. Here we introduce Small Molecule In situ Resin Capture (SMIRC), a culture-independent method to obtain natural products directly from the environments in which they are produced. We use SMIRC to capture numerous compounds including two new carbon skeletons that were characterized using NMR and contain structural features that are, to the best of our knowledge, unprecedented among natural products. Applications across diverse marine habitats reveal biome-specific metabolomic signatures and levels of chemical diversity in concordance with sequence-based predictions. Expanded deployments, in situ cultivation, and metagenomics facilitate compound discovery, enhance yields, and link compounds to candidate producing organisms, although microbial community complexity creates challenges for the later. This compound-first approach to natural product discovery provides access to poorly explored chemical space and has implications for drug discovery and the detection of chemically mediated biotic interactions.
Nanotransistor-based gas sensing with record-high sensitivity enabled by electron trapping effect in nanoparticles
Authors: Hu Qitao , Solomon Paul , Österlund Lars , Zhang Zhen 
Published: June 2024

AbstractHighly sensitive, low-power, and chip-scale H2 gas sensors are of great interest to both academia and industry. Field-effect transistors (FETs) functionalized with Pd nanoparticles (PdNPs) have recently emerged as promising candidates for such H2 sensors. However, their sensitivity is limited by weak capacitive coupling between PdNPs and the FET channel. Herein we report a nanoscale FET gas sensor, where electrons can tunnel between the channel and PdNPs and thus equilibrate them. Gas reaction with PdNPs perturbs the equilibrium, and therefore triggers electron transfer between the channel and PdNPs via trapping or de-trapping with the PdNPs to form a new balance. This direct communication between the gas reaction and the channel enables the most efficient signal transduction. Record-high responses to 1–1000 ppm H2 at room temperature with detection limit in the low ppb regime and ultra-low power consumption of $$\sim$$
~
300 nW are demonstrated. The same mechanism could potentially be used for ultrasensitive detection of other gases. Our results present a supersensitive FET gas sensor based on electron trapping effect in nanoparticles.