bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intra‐Aortic Balloon Pump: Overall and Temporal Trends of Comparative Effectiveness in a National Registry
Authors: Cohen Ben , Kalmanovich Eran , Perl Leor , Greenberg Gabi , Beigel Roy , Ovdat Tal , Kornowski Ran , Orvin Katia 
Published: December 2024

ABSTRACTBackgroundAlthough the latest studies failed to prove the benefit of routine intra‐aortic balloon pump (IABP) use in patients with acute myocardial infarction (MI) presenting with cardiogenic shock, the benefit of IABP utilization in selected cases in “real world” practice is unknown.AimsWe sought to follow temporal trends in IABP use in a real‐world cohort of acute coronary syndrome (ACS).MethodsWe evaluated IABP utilization and patient outcomes from the Acute Coronary Syndrome in Israel Survey (ACSIS) between the years 2000 and 2021. Temporal trends and outcomes with IABP at two time periods were set: early (before 2012) and late (after 2012).ResultsOut of 18,662 ACS patients, 3.7% received IABP. The rate of IABP use was 4.5% in the early period and decreased to ~2.5% in the late period (p < 0.001). Patients treated with IABP in the early period had more frequently reduced ejection fraction (64.5% vs. 53.2%, p < 0.01) and presented mostly with ST‐elevation MI (71.0% vs. 62.4%, p = 0.04). Cardiogenic shock on admission and in‐hospital occurred equally in both periods (14.6% vs. 17.1%, p = 0.66; 42.8% vs. 41.9%, p = 0.90, respectively). Thirty‐day mortality and MACE were comparable between time periods (28% vs. 30.7%, p = 0.547; 43.6% vs. 44.1%, p = 0.978, respectively) however bleeding complications were significantly higher in the later period (4.8% vs. 11.2%, p = 0.04).ConclusionsOur real‐world ACS data demonstrated a 50% reduction in the utilization of IABP among acute MI patients in the last decade. A comparable poor prognosis with IABP across time periods, suggest sustainable worse outcome in routine albeit selective clinical practice.
Transcatheter Aortic Valve Implantation in Small and Very Small Aortic Valve Annuli: A Propensity‐Matched Analysis Between Self‐Expanding Versus Balloon‐Expandable Valves
Authors: Itach Tamar , Loewenstein Itamar , Zahler David , Finkelstein Ariel , Barbash Israel , Greener Gabby Elbaz , Assa‐Vaknin Hana , Kornowski Ran , Turyan Anna , Steinvil Arie 
Published: December 2024

ABSTRACTBackgroundThe management of Transcatheter Aortic Valve Implantation (TAVI) patients with a small aortic annulus (SAA) postures a substantial challenge, increasing the risk of patient‐ prosthesis mismatch (PPM) and overall mortality.AimsThis study aimed to compare the hemodynamic and clinical outcomes of transcatheter balloon‐expandable valve (BEV) versus transcatheter self‐expandable valve (SEV) in SAA.MethodsWe conducted propensity score matching (PSM) of severe AS patients with SAA who underwent trans‐femoral TAVR and enrolled to the Israeli TAVR registry between the years 2008 and 2023. SAA was defined as an aortic‐valve annulus area ≤ 430 mm2. Since the BEV used have a smaller size cut‐off, an additional analysis on very small aortic annulus (vSAA) as defined as aortic‐valve annulus area ≤ 345 mm2 was performed.ResultsThe study included 1364 consecutive patients with SAA of (BEV n = 485; SEV n = 879) at a mean age of 82 ± 7 years, of whom the vast majority were female (83%). Propensity‐matched groups comprised of 329 and 122 paired for the SAA and vSAA patients, respectively. As compared to BEV in the SAA and vSAA analyses, SEV showed lower rates of postprocedural of LBBB (32% vs. 22% and 41% vs. 22%; both p < 0.01, respectively), however, higher rates of major vascular complications (2% vs. 7% and 2% vs. 12%; both p < 0.01, respectively) and major or life‐threatening bleeding but only in vSAA group (17% vs. 9.1%, p = 0.009). One‐month mortality was higher in the SEV versus BEV in both SAA and vSAA comparisons (2% vs. 0.6%, p = 0.048 and 3% vs. 0%, p = 0.018; respectively). A nonsignificant trend of higher 5‐year mortality was observed in univariate models, noted mainly in vSAA patients (22% vs. 19%, p = 0.385; 24% vs. 15%, p = 0.073).ConclusionsThe present analysis observed higher rates of major vascular complications and 1‐month mortality in SAA and vSAA treated with SEV. A similar nonsignificant trend toward long‐term mortality for the vSAA group was observed and should be evaluated in larger cohorts.
Development of a Self‐Pressurized Polymer Electrolyte Membrane Electrolyzer for Hydrogen Production at High Pressures
Authors: Liao Longfei , Li Mingyu , Yin Yongli , Du Ruixing , Tan Xing , Zhong Qitong , Zeng Feng 
Published: December 2024

AbstractThis study involves the development of a self‐pressurized water electrolyzer for H2 production, highlighting the effects of electrolyzer configuration, operation temperature, flow rate, and pressure on the electrolyzer's performance. The compression of H2 takes up a large proportion of the cost for H2 production through water electrolysis in a polymer electrolyte membrane (PEM) electrolyzer. However, creating a high‐pressure PEM electrolyzer comes with challenges, such as managing diffusion and ohmic losses that impact cell voltage and efficiency. To address these issues, a novel cell configuration was designed. This configuration aims to minimize the gap among various components, including electrodes, gas diffusion layers, and current collectors. The configuration also leads to reduced cost as well as the difficulty of processing and assembling. Additionally, the gas diffusion layers and current collectors were coated with Pt to enhance their conductivity, effectively reducing the ohmic losses within the cell. Further optimization efforts focused on investigating the effects of temperature, pressure, and water flow on concentration voltage to achieve peak performance. As a result, a cell voltage of 1.868 V was achieved at 1 A/cm2 under 10 MPa operating conditions.
Cu2O@Cu@NiAl‐LDH with Cu0/Cu+ Valence Synergy and Core‐Shell Structure for Highly Selective Generation of C2H6
Authors: Guo Sheng‐hui , Guo Rui‐tang , Zhang Zhen‐rui , Yu Ling‐qi , Yan Ji‐song , Liu Hao , Pan Wei‐Guo 
Published: December 2024

AbstractPhotocatalytic CO2 reduction to produce C2 products remains a challenge. Herein, Cu2O@Cu@NiAl‐LDH composites with three‐dimensional ordered core‐shell structures were successfully prepared, and the effects of Cu2O with different exposed surfaces on CO2 photoreduction were investigated. The synergistic effect of zero‐valent Cu and Cu+ as intermediate electron mediators retains more photogenerated electrons and the Z‐scheme heterojunction formed between Cu2O and NiAl‐LDH leads to the enhancement of C2 selectivity. The best sample, Cu2O@Cu@NiAl‐LDH‐2, achieved a C2H6 yield of 22.17 μmol g−1 h−1 with 63.89 % electron selectivity. The evolution pathways and photocatalytic mechanisms of CO2 were investigated by in‐situ DRIFTS and theoretical calculations. This study provides references and suggestions for the further development of experimental and theoretical calculations of Cu2O‐based photocatalysts for the reduction of CO2 to C2 products.
Engineering the Morphology and Electronic Structure of NiCo2O4 to Boost the Electrocatalytic Oxidation of 5‐Hydroxymethylfurfural
Authors: Li Kewang , Lu Huiying , Shi Huijie 
Published: December 2024

AbstractElectrocatalytic biomass conversion using green electricity is regarded as an important strategy to meet the requirement of sustainable development. NiCo2O4 electrodes with different morphologies and electronic structures were fabricated by changing the precipitants used in the solvothermal process, and applied in the electrocatalytic 5‐hydroxymethylfurfural oxidation (HMFOR). The experimental and theoretical calculation results showed NiCo2O4 nanosheets (NCO‐Ns) with low Co/Ni ratio exhibited larger adsorption energy towards HMF and superior intrinsic catalytic activity in HMFOR, while NiCo2O4 nanoneedles (NCO‐Nn) with larger electrochemical active surface areas presented faster electron transfer kinetics and enhanced catalytic performance for 50 mM HMF with a higher conversion rate (99.9 %), 2,5‐furanodicarboxylic acid (FDCA) selectivity (98.6 %) and faraday efficiency (98.6 %). It indicated that compared with NCO‐Ns, NCO‐Nn providing more active sites was kinetically favorable for improving HMFOR efficiency. In‐situ electrochemical Raman investigation revealed that in strong alkaline media, NiOOH formed by the electrochemical reconstruction of NiCo2O4 surface served as the main active species in HMFOR, and an indirect oxidation mechanism was elucidated. This work established the relationship between the electrocatalytic performance of a catalyst and the surface morphology and electronic structure in HMFOR, provided a new idea for improving the electrocatalytic activity of a catalyst, and supported it experimentally.
Seabird nutrient subsidy alters size and resource use of functionally important mangrove macroinvertebrates
Authors: Appoo Jennifer , Graham Nicholas A. J. , Jones Christopher W. , Jaquemet Sébastien , Bunbury Nancy 
Published: December 2024

AbstractInvertebrates have a central role in food webs and ecosystem functioning. By boosting productivity, allochthonous nutrient inputs influence the food webs of recipient communities. Understanding how allochthonous nutrient subsidies affect invertebrates is crucial, particularly in highly productive coastal areas. Here, we examine how mangrove macroinvertebrates are impacted by nutrient‐rich guano delivered by nesting seabird populations at Aldabra Atoll in the Indian Ocean. We compare nitrogen and carbon stable isotope ratios and nitrogen composition of basal resources and macroinvertebrate consumers in mangroves with and without nesting seabirds. Seabird‐derived nutrient enrichment increased the nitrogen content of basal food sources and herbivorous littorinid gastropods and sesarmid crabs. In mangroves with breeding seabirds, mean carapace widths of sesarmid and omnivorous portunid crabs were 6% and 11% larger, respectively. Isotopic niches of littorinid gastropods and sesarmid crabs were larger and had higher overlap at seabird compared to non‐seabird sites. Epiphytic macroalgae and guano comprised >50% of resource contributions to littorinid gastropods and sesarmid crabs at seabird sites. This differed markedly from non‐seabird sites where the main resource contributions were 77% mangrove leaves for littorinid gastropods, 36% sediment organic matter, and 41% mangrove leaves for sesarmid crabs. The increased sizes of mangrove crabs suggest that seabird nutrient enrichment can promote mangrove crab fisheries productivity and benefit the provisioning of mangrove ecosystem services. By shifting resource use of functionally important macroinvertebrates, we discuss how seabirds modify trophic interactions, with potential consequences for mangrove ecosystem processes and resilience.
Experimental Evidence of Rapidly Decaying Environmental DNA Highlights Infection Risk from Two Major Amphibian Pathogens
Authors: Trafford Joseph D. , Garner Trenton W. J. , Murrell David J. , Day Julia J. 
Published: December 2024

ABSTRACTInfectious diseases spread through international wildlife trade networks, presenting major conservation and welfare challenges. The diseases amphibian chytridiomycosis (caused predominantly by chytrid fungus Batrachochytrium dendrobatidis, Bd) and ranavirosis (caused by iridoviruses in the genus Ranavirus, Rv) are the result of infection by globally distributed pathogens. These pathogens spread internationally through live‐animal trade networks and have driven population declines, mass mortalities, and community collapse for a broad range of amphibian species. Environmental (e)DNA methods may provide highly sensitive and non‐invasive pathogen surveillance for traded or wild amphibians. To investigate the relationship between eDNA detection and environmental pathogen persistence, eDNA degradation rates were quantified across a range of temperatures (15°C–25°C) for both Bd and Ranavirus. Estimated decay rates suggest that overall pathogen eDNA concentration degrades by 99% between 18.9–52.4 h. Low levels of pathogen eDNA remained detectable for the duration of the experiment (> 28 days). Time was found to have a significant negative effect on eDNA concentration for both pathogens (p < 0.001). The negative effect of temperature on eDNA concentration was significant for both pathogens (20°C for Rv, p < 0.05; 25°C for Bd/Rv p < 0.001). We argue that high concentrations of eDNA represent viable pathogen in the environment, demonstrating the usefulness of eDNA for the monitoring of disease status of consignments of traded amphibians.
An Innovative Nanoparticle Modified Carbon Paste Microsensor for Ultrasensitive and Selective Detection of Danofloxacin in Environmental and Urinary Samples
Authors: Amra Siham , Bourouina‐Bacha Saliha , Bourouina Mustapha , Hauchard Didier 
Published: December 2024

An ultrasensitive and selective voltammetric microsensor (multiwalled carbon nanotube [MWCNT]/carbon black nanoparticle [nCB])‐modified carbon paste microelectrode (mCPµE) with ultra‐trace level detection limit is designed for the determination of danofloxacin (DAN) in real samples. The (MWCNT/nCB)‐mCPµE consists of a carbon paste cavity microelectrode (MEC) modified with nCBs and MWCNTs. The nanostructure of the different MEC materials are characterized by scanning electron microscopy and electrochemical impedance spectroscopy. Under optimal conditions, a wide linear range (2.5 × 10−9–2.5 × 10−7 mol L−1) is obtained. The detection and quantification limits are estimated at 4.3 × 10−10 and 1.43 × 10−9 mol L−1, respectively. For the measurement of DAN in the presence of many possible interfering chemical molecules, the suggested microsensor demonstrates remarkable selectivity. Analysis of the real samples confirms that the (MWCNT/nCB)‐mCPµE is a suitable electrochemical sensor for the determination of DAN in wastewater and urine samples with satisfactory recoveries of 103.5%–104.6% and relative standard deviations less than 4.93%. Finally, in terms of sustainability (availability of materials used), analytical efficiency (precision and very low limit of quantification), and economic considerations (use of a very small quantity of materials), the proposed method outperforms previously reported methods.
Joint Power and Delay Optimization‐Based Resource Allocation in Mu‐MIMO‐OFDM System: Deep Convolutional Red Piranha Pyramid‐Dilated Neural Network
Authors: Vijaipriya K. , Nesasudha M. , Michael Prawin Angel 
Published: December 2024

ABSTRACTIn general, Multi‐User Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MU‐MIMO‐OFDM) enables multiple users to simultaneously communicate with a single base station using multiple antennas and OFDM modulation. Nevertheless, resource allocation challenges such as power management and delay optimization arise within MU‐MIMO‐OFDM systems, requiring sophisticated solutions to ensure efficient use of resources and optimal system performance. Thus, joint power and delay optimization‐based resource allocation using a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN) with Red piranha optimization and Optimal Delay Scheduling conflict graphs Algorithm (DCPDNN‐RPO‐ODSCGA) in MU‐MIMO‐OFDM system is proposed in this presented research. The proposed mechanism is performed in two stages: power allocation and delay optimization. In the first stage, through a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN), which aims to maximize throughput, the network resources are distributed to user equipment (UEs) based on power and transmission rate. To reduce the loss function, Red Piranha Optimization (RPO) is proposed to optimize the layers of DCPDNN. In the second stage, the Optimal Delay Scheduling conflict graphs Algorithm (ODSCGA) is proposed for the optimizing delay in the MU‐MIMO‐OFDM system. The multiracial envelope procedure and service curve for traffic flows in the uplink transmission are used in the ODSCGA approach to estimate the delay‐bound value. Ideas like the maximal weight independent set and optimal conflict graph are also utilized. The simulations of DCPDNN‐RPO‐ODSCGA were conducted using MATLAB software. Thus, the proposed approach has attained higher spectral capacity, higher fairness index, and increased cumulative distribution function (CDF), 29.74%, 32.98%, and 16.46% lower loss rate, 28.05%, 24.09%, and 17.45% improved energy efficiency, 15.09%, 13.78%, and 12.05% lower processing time than other conventional approaches like MPQM‐SCA, Hyb‐BF‐DSA, and SIA‐FDBD methods, respectively.
HACDRAN: A Novel Hybrid Atrous Convolution Model With Densenet and Residual Attenuation Network for Multi‐Plant Leaf Disease Classification
Authors: Sahu Kalicharan , Singh Manoj Kumar , Niranjan Maheshwari , Joshi Pratibha 
Published: December 2024

ABSTRACTThe beneficiation of the plant is majorly crucial for both the environment and human life. The crops do trouble from disorders like other species. Various plant leaf disorders happen and trouble the general growth of the crop. These crop leaf disorders are troubles the entire plant consisting flower, root, stem, and leaf. The plant leaf disorders are mostly not taken care of by the farmers so that the crop dies or can create the cause of fruits, flowers and leave a drop. Significant detection of these disorders is essential for detecting and takes preventive measures of plant leaf disorders. The research of plant leaf disorders, procedures, and their causes for handling and managing is known as plant pathology. However, the conventional model encloses the involvement of humans in the identification and categorization of crop leaf disorders. This approach is expensive and consumes more time. It is highly essential to design a new multi‐plant leaf disorder categorization model to tackle the above‐mentioned complexities. At first, the multi‐plant leaf pictures are obtained from online sources and they are offered to the abnormality segmentation phase. Here, the abnormality presented in the multi‐plant leaf image is segmented by adaptive TransUNet, where the parameters are optimized by the developed Mean Position of Sheep Flock and Cuckoo Search (MPSFCS). Further, the abnormality segmented images are offered to the multi‐plant leaf disease classification phase. In this phase, the multi‐plant leaf disorders are categorized by utilizing Hybrid Atrous Convolution based Networks of DenseNet and Residual Attenuation Network (HACDRAN), and their parameters are optimized by the developed MPSFCS to offer effective multi‐plant leaf disease classified outcome. Thus, the developed multi‐plant leaf disease classification model provides a better functionality rate than the conventional methods with multiple analyses.
Combinatorial discovery of small molecule‐doped afterglow polymer composites for anti‐counterfeiting
Authors: Lu Yeqing , Chen Xue , Suh Yung Doug , Liu Xiaowang 
Published: December 2024

AbstractThe exploration of afterglow in small molecule‐doped polymer composites, rooted in a nuanced understanding of structure‐properties relationships, holds paramount importance for optoelectronics. However, conventional strategies face challenges in achieving high‐throughput discovery of these polymers. This study introduces a novel combinatorial approach, employing photoinitiated solvent‐free polymerization, to craft afterglow aromatic boronic acid‐doped polymer composites. The afterglow activation results from stabilizing the triplet states of doped small molecules through a synergy of chemical and physical fixation effects. Aromatic boronic acids emerge as crucial dopants, exhibiting versatility in afterglow development across the visible spectrum. Notably, the influence of functional groups and the number of non‐fused benzene rings on afterglow wavelengths is minimal, while significantly impacting afterglow lifetimes. Besides conjugation degrees, the optimal size and doping concentrations of dopants play a pivotal role in extending afterglow lifetimes. This strategy not only facilitates exploration of small molecule‐based afterglow materials but also enables the feasible fabrication of intricate, multicolor afterglow polymeric objects via a step‐polymerization strategy for anti‐counterfeiting.
Explainable Soybean Futures Price Forecasting Based on Multi‐Source Feature Fusion
Authors: Wu Binrong , Yu Sihao , Lv Sheng‐Xiang 
Published: December 2024

ABSTRACTThe prediction and early warning of soybean futures prices have been even more crucial for the formulation of food‐related policies and trade risk management. Amid increasing geopolitical conflicts and uncertainty in trade policies across countries in recent years, there have been significant fluctuations in global soybean futures prices, making it necessary to investigate fluctuations in soybean futures prices, reveal the price determination mechanism, and accurately predict trends in future prices. Therefore, this study proposes a comprehensive and interpretable framework for soybean futures price forecasting. Specifically, this study employs a set of methodologies. Using a snow ablation optimizer (SAO), this study improves the parameters of a time fusion transformer (TFT) model, an advanced interpretable predictive model based on a self‐attention mechanism. Besides, it addresses the factors influencing soybean futures prices and constructs effective fusion features through a feature fusion method. To explore volatility trends, the original soybean futures price series are decomposed using variational mode decomposition (VMD). This study also enhances the accuracy of soybean futures price predictions by introducing global geopolitical risk coefficients and trading volumes as predictors. The empirical findings suggest that the VMD‐SAO‐TFT model enhances prediction accuracy and interpretability, offering implications for decision‐makers to achieve accurate predictions and early warning of agricultural futures prices.
Science and Justice
Authors: Kaebnick Gregory E. 
Published: December 2024

AbstractIn different ways, the November‐December 2024 issue of the Hastings Center Report contests the view that science is a value‐free endeavor to understand the world. The lead article argues that, while most science is commendable, some is inherently “abhorrent,” as it is both harmful and devoid of value. Contemporary “race science”—the work of a “new wave of race researchers” who use “questionable scientific techniques to investigate alarming hypotheses regarding the genomic basis of differences in cognitive abilities between racial and ethnic groups”—is, for the authors, a paradigmatic case of abhorrent science. The intersection of genomics and values is also the subject of a special report, “Toward a More Just Genomics,” published with this issue.
How to Diagnose Abhorrent Science
Authors: Matthews Lucas J. , Tabery James , Turkheimer Eric 
Published: December 2024

AbstractWhat makes certain scientific research controversial? And when does scientific research go beyond being merely controversial to be something far worse? We propose a diagnostic framework for distinguishing between scientific research that is merely controversial and that which is abhorrent. Our framework places research projects along two axes of a value‐harm map. Most research, fortunately, is both valuable and harmless. However, research may be controversial if it is either valuable but harmful or harmless but valueless. The most concerning quadrant of our value‐harm map includes research that is both valueless and harmful, which is abhorrent science. The article's analysis considers a series of case studies, highlighting “new genomic race science” as an exemplar of abhorrent science.