bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Flow Method: An improved Hazard and Operability Study methodology
Authors: Smith Craig , Morris Brandon , Memmott James , Azimi Reza , Hanson Joel , Brown Scott S. 
Published: February 2025

AbstractThe traditional Hazard and Operability Study (HAZOP) is a well‐established methodology in the chemical industry for hazard identification and risk analysis, also known as Process Hazard Analysis (PHA). However, its deviation‐based approach can lead to inefficiencies, fragmented reviews, and increased team fatigue. The Process Flow Failure Modes Analysis (PFFM) was introduced as an efficient alternative, evaluating risk based on the natural process flow, and recognizing that each piece of equipment has knowable failure modes. However, PFFM's limitations include the intensive preparation and the qualitative nature of the evaluation, leaving potential for missed risks. Layer of Protection Analysis (LOPA), a more quantitative method, typically relies on HAZOP results, which increases team resource usage. This paper introduces the “Flow Method,” an evolved and optimized blend of HAZOP, PFFM, and LOPA. By integrating additional tools, the Flow Method enhances the overall PHA process, resulting in streamlined, and consistent studies with unparalleled thoroughness. With over 200 studies conducted across 25 production sites and terminals, Nutrien has now adopted the Flow Method for all PHA studies. This paper presents comparative data from multiple studies and locations, demonstrating the Flow Method's effectiveness and its potential to revolutionize process safety analysis in the chemical industry.
IAMPDB: A Knowledgebase of Manually Curated Insects‐Derived Antimicrobial Peptides
Authors: Mondal Rajat Kumar , Tripathi Prabhat , Mondal Rudra Prasad , Sen Debarup , Arya Ankish , Karmakar Debayan , Pal Oshin , Dey Avijit , Samanta Sintu Kumar 
Published: February 2025

ABSTRACTInsects, a majority of animal species, rely on innate immunity and antimicrobial peptides (AMPs), which are a part of their innate immunity, to combat diverse parasites and pathogens. These peptides have applications ranging from agriculture to antimicrobial resistance (AMR). However, there is a lack of a specialized database, prompting the development of the Insect Antimicrobial Peptide Database (IAMPDB) as a pioneering comprehensive Knowledgebase dedicated to insect‐derived antimicrobial peptides (IAMPs), serving as a resource for researchers and industry professionals. Curated from UniProt and associated literature(s), IAMPDB currently houses 438 curated entries of IAMPs from various insect species, spanning 10 taxonomical orders of insects. Each entry is meticulously annotated with details on peptide sequence, source organism, activities, physicochemical properties, and more. IAMPDB offers a user‐friendly interface with diverse search options, interactive visualizations, and links to external databases; advanced tools, including a peptide sequence alignment toolbox and a peptide feature calculation toolbox, facilitating sequence alignment, physicochemical property calculation, and in‐depth analysis. The knowledgebase is accessible online (at URL https://bblserver.org.in/iampdb/).
Assessing forecast benefits of future constellations of microwave sounders on small satellites using an ensemble of data assimilations
Authors: Lean Katie , Bormann Niels , Healy Sean , English Stephen , Schüttemeyer Dirk , Drusch Matthias 
Published: February 2025

AbstractThe ensemble of data assimilations (EDA) method is employed to evaluate the expected impact of a wide range of potential future constellations of passive microwave (MW) sounders on small satellites for global numerical weather prediction. Such constellations are expected to become an important component of the future observing system, complementing a backbone of larger, high‐performance platforms and allowing unprecedented temporal sampling. Twelve constellations are investigated to probe key aspects of the constellation design: number of satellites (ranging from 8 to 20), types of orbits (sun synchronous, mid‐inclination), and channel complement (183 GHz humidity‐sounding capabilities only versus combining these with temperature‐sounding capability around 50 GHz). The small‐satellite data and accompanying errors are simulated, using an all‐sky framework, and the relative benefits from adding the different constellations to the observing system are measured by the reduction in the spread of the ensemble members, reflecting improvement to the forecast uncertainties. Results suggest continued benefit from adding MW‐sounding observations beyond currently available observations. The EDA spread reduction for different variables (e.g., wind and geopotential height) and different pressure levels is already significant using the smallest constellation considered, adding eight satellites to a four‐satellite baseline of existing MW‐sounding instruments. The EDA spread reduction continues as further observations are added, although the rate of reduction slows significantly, especially where scenarios use only humidity‐sounding channels. Use of temperature‐sounding channels gives significant added benefit over humidity sounding only, generally 2–3 and 1.5–2 times larger in the extratropics and Tropics respectively. Different behaviour in the relative magnitudes and rates of EDA spread reduction is seen between the extratropics and Tropics, which can be attributed to different physical processes and different error growth. This study was unable to provide conclusive results on the choice of polar orbits only, mid‐inclination orbits only, or a mix of orbit types.
The Completion Numbers of Hamiltonicity and Pancyclicity in Random Graphs
Authors: Alon Yahav , Anastos Michael 
Published: February 2025

ABSTRACTLet denote the minimum number of edges whose addition to results in a Hamiltonian graph, and let denote the minimum number of edges whose addition to results in a pancyclic graph. We study the distributions of in the context of binomial random graphs. Letting , we prove that there exists a function of order such that, if with , then with high probability . Let denote the number of degree vertices in . A trivial lower bound on is given by the expression . We show that in the random graph process with high probability there exist times , both of order , such that for every and for every . The time can be characterized as the smallest for which contains less than copies of a certain problematic subgraph. In particular, this implies that the hitting time for the existence of a Hamilton path is equal to the hitting time of with high probability. For the binomial random graph, this implies that if and , then, with high probability, . For completion to pancyclicity, we show that if and , then, with high probability, . Finally, we present a polynomial time algorithm such that, if and , then, with high probability, the algorithm returns a set of edges of size whose addition to results in a pancyclic (and therefore also Hamiltonian) graph.
Sustainable Tourism and SDGs in the South Caucasus
Authors: Martins Flavio , Sitchinava Tatiana , Keryan Tigran , Mitrofanenko Alexander , Stefanelli Nelson , Guigoz Yaniss 
Published: February 2025

ABSTRACTThis study examines sustainable tourism practices in the South Caucasus region (Armenia, Azerbaijan, and Georgia) through the lens of the United Nations Sustainable Development Goals (SDGs). A scoping literature review was conducted, analyzing academic papers from Scopus and Web of Science databases. Content analysis and expert validation were employed to map synergies and trade‐offs between sustainable tourism practices and the 169 SDG targets. The analysis of 94 papers reveals 434 connections, comprising 276 synergies and 158 trade‐offs. Notable synergies were identified with SDG 8 (Decent Work and Economic Growth) and SDG 11 (Sustainable Cities and Communities). The study highlights region‐specific challenges and opportunities, including the need for water resource management in Azerbaijan and the potential of wine tourism in Georgia. Findings underscore the importance of cross‐border cooperation and tailored approaches to SDG implementation, considering each country's distinct characteristics. The research contributes to understanding the complex interactions between sustainable tourism and SDGs in the South Caucasus, offering insights for policymakers and stakeholders.
How does artificial intelligence improve human decision‐making? Evidence from the AI‐powered Go program
Authors: Choi Sukwoong , Kang Hyo , Kim Namil , Kim Junsik 
Published: February 2025

AbstractResearch SummaryWe study how humans learn from artificial intelligence (AI), leveraging an introduction of an AI‐powered Go program (APG) that unexpectedly outperformed the best professional player. We compare the move quality of professional players to APG's superior solutions around its public release. Our analysis of 749,190 moves demonstrates significant improvements in players' move quality, especially in the early stages of the game where uncertainty is highest. This improvement was accompanied by a higher alignment with AI's suggestions and a decreased number and magnitude of errors. Young players show greater improvement, suggesting potential inequality in learning from AI. Further, while players of all skill levels benefit, less skilled players gain higher marginal benefits. These findings have implications for managers seeking to adopt and utilize AI in their organizations.Managerial AbstractWe examine how professionals can learn from artificial intelligence (AI) by studying an AI‐powered Go program (APG) that outperformed the best professional player. By analyzing 749,190 moves, we find that players' move quality improved significantly, closely aligning with the AI's recommendations. The number and magnitude of errors also decreased. This learning effect was particularly strong early in the game where decisions are more uncertain. Young players showed greater effect, suggesting that learning from AI may vary by age. While players of all skill levels benefited, those with less skill saw the greatest improvement. These findings highlight the instructional role of AI and offer guidance on how to effectively integrate AI into organizations to enhance worker performance across different age groups and skill levels.
Regulating Rotational Dynamics of Co‐Adsorbed Guest Molecules via Halogen Bonds in Functionalized Pores of Self‐Assembled Molecular Networks at the Liquid‐Solid Interface
Authors: Machida Yoshihito , Katsu Akitoshi , De Feyter Steven , Tahara Kazukuni 
Published: February 2025

AbstractUnderstanding and controlling molecular rotation on surfaces is crucial for the development of molecular‐scale artificial motors that operate at interfaces. Herein, it is reported the successful co‐adsorption of guest molecules within the functionalized 2D pores of self‐assembled molecular networks (SAMNs) through directional halogen bonding, as confirmed by scanning tunneling microscopy. Specifically, the porous SAMN formed by dehydrobenzo[12]annulene derivative DBA‐Py with a pyridyl group at the termini of its three alkoxy chains, hosts an iodinated trigonal guest molecule, tris(4‐iodophenyl)benzene (TIB), through a halogen bond between the nitrogen and iodine atoms. Within the pores, the TIB molecule exhibits rotational motion, preferentially residing at two locations. In contrast, within the pores formed by a mixture of DBA‐Py and DBA‐Ph, where DBA‐Ph features three phenyl groups instead of pyridyl groups, the guest molecule preferentially resides in a single location. This behavior is attributed to the reduced number of energy minima within the pores owing to the decreased number of pyridyl units. Statistical analysis of the guest orientation suggests that the on‐surface arrangement of DBA‐Py and DBA‐Ph is influenced by the guest molecule. This modular approach using functionalized pores in SAMNs provides an effective strategy for controlling molecular rotational behavior.
Over 20% Efficiency in Printable Mesoscopic Perovskite Solar Cells with Enhanced Open‐Circuit Voltage via a Multifunctional Ionic Liquid
Authors: Zhang Yang , Chen Yiwen , Liu Yan , Cai Yongxiang , Liu Yunxiang , Wu Chenshu , Wang Jinjiang , Zhang Zheling , Wang Dongjie , Zhang Jian 
Published: February 2025

AbstractThe large open‐circuit voltage (VOC) losses limit the enhancement of power conversion efficiency (PCE) in printable mesoscopic perovskite solar cells (p‐MPSCs). These losses primarily result from the high defect density at perovskite grain boundaries within the mesoporous scaffold, which promotes non‐radiative recombination. In this study, the crystallization improvement and defect modulation of perovskite is promoted by adopting a multifunctional ionic liquid, 1‐butyl‐2,3‐dimethylimidazolium trifluoromethanesulfonate (BMMIm[OTF]). The imidazolium ions in BMMIm[OTF] form hydrogen bonds with the PbI64− framework and coordinate with under‐coordinated lead ions through S═O bonds. These interactions synergistically improve the crystallinity of perovskite films and optimize energy level alignment at the perovskite/carbon electrode interface. This improved interface facilitates more efficient charge transfer and extraction while reducing non‐radiative recombination. As a result, the champion p‐MPSCs incorporating BMMIm[OTF] achieve a PCE of 20.02% and a VOC of 1.055 V, significantly outperforming control devices with a VOC of 0.965 V. Furthermore, the hydrophobic nature of BMMIm[OTF] enhances device stability. This research provides a practical strategy for developing efficient and durable p‐MPSCs.
Hierarchical Nanoporous Carbons with an Integrated Activation Using 3D Flower‐Like ZnO Microspheres and KOH for Flexible EDL Capacitor with a High Operating Potential
Authors: Balamurugan Ramalingam , Chandra Bose Arumugam , Vinu Ajayan 
Published: February 2025

AbstractActivated nanoporous carbons are widely used in various applications, where their efficiency is largely determined by their specific surface area and pore structure. Traditional KOH‐assisted chemical activation methods primarily produce micropores, limiting the performance of these porous carbons in applications requiring a hierarchical arrangement of micro, meso, and macropores. This study introduces a novel integrated activation strategy using 3D flower‐like microsphere (3DFM) ZnO and KOH to synthesize nanoporous carbons from Sesbania Grandiflora side shoots. The porous nanosheet tips and microsphere bulk of 3DFM‐ZnO generate mesopores and macropores, while KOH induces microporosity, resulting in a hierarchical structure with an ultrahigh specific surface area of 4114 m2 g−1. The fabricated activated carbon electrodes with the combination of macro, meso, and micropores exhibit high specific capacitances of 672 F g−1 for the positive electrode and 756 F g−1 for the negative electrode. The performance of electrodes is optimized with the proper selection of electrolytic ions for positive and negative electrodes. A high operating potential window of 2.7 V is achieved in a symmetric device through charge‐balanced mass loading. The fabricated flexible electric double‐layer capacitor demonstrates a maximum specific energy of 128.2 W h kg−1 at a specific power of 1.35 kW kg−1.
An Empirical Study on the Effects of Jayvee, a Domain‐Specific Language for Data Engineering, on Understanding Data Pipeline Architectures
Authors: Heltweg Philip , Schwarz Georg‐Daniel , Riehle Dirk , Quast Felix 
Published: February 2025

ABSTRACTA large part of data science projects is spent on data engineering. Especially in open data contexts, data quality issues are prevalent and are often tackled by non‐professional programmers. We introduce and evaluate Jayvee, a domain‐specific language for data engineering aimed at reducing barriers to building data pipelines. We show that a structured DSL can have positive effects on speed, ease of use, and quality for data engineering by non‐professional developers. For this, we present an empirical quantitative study, in which we compare the performance of students as proxies for non‐professional programmers using Jayvee with Python and Pandas. We search for reasons for the empirical findings using a follow‐up interview study on how using a DSL changes how non‐professional programmers build data pipelines. Participants solve a subset of tasks faster, more easily, and with higher quality when using Jayvee compared to Python. Interviewees describe tradeoffs regarding the DSL's more limited features, stricter code structure, and explicit descriptions. Jayvee is found to be more approachable, which leads to a more guided development flow. New data engineering languages should provide good tooling and documentation, plan how to visualize intermediate data and consider new development workflows involving tools like ChatGPT to find adoption.
Light‐Induced Radix Modulation and Optoelectronic Synaptic Properties in Ternary‐Logic Devices
Authors: Park Chohyeon , Lim Jung Wook 
Published: February 2025

Multivalued logic (MVL) devices overcome the limitations of binary computing. However, their complex structures and complementary metal–oxide semiconductor (CMOS) incompatibility pose considerable challenges. Herein, a streamlined MVL device has been developed using a transistor with an oxide channel and dual‐gate dielectric, eliminating the need for a barrier junction in the channel layer. This new device supports three logic states (OFF, intermediate, and ON) through Fowler–Nordheim tunneling between the gate and source. It exhibits optoelectronic synaptic properties by leveraging the photoresponse of its constituent TiO2 channel and charge trapping at the gate dielectric/channel interface, achieving optical potentiation of 128 multistates with a linearity of 0.94. Additionally, the device can switch between ternary and binary‐logic states within a specific wavelength range. The proposed approach is a practical solution to integrating logic state switching and synaptic functions in a single device, with potential application in advanced semiconductor technologies.
Unveiling the potential of emerging microRNA panels as diagnostic biomarkers for prostate cancer: A review
Authors: Manoj Anveshika , Prasad Gautam , Ahmad Mohammad Kaleem 
Published: February 2025

AbstractProstate cancer (PCa) is a multifaceted disease that envelops 1.41 million new cases globally. It is the second most common cancer reported in men. Its heterogeneity and indolent growth, coupled with incompetent early screening methods such as serum prostate‐specific antigen level estimations and digital rectal examinations, contribute to its delayed detection, potentially leading to misdiagnosis or overtreatment. Despite the advancement in surgical methods, better management of PCa requires definitive diagnostics, prognostics, and therapeutics. PCa cells express microRNA (miRNA) on their surface as well as release miRNA into the bloodstream, which enables their noninvasive detection in body fluids like serum, plasma, and urine. miRNA acts as sponge for circulating RNA that regulates gene expression of crucial pathways in PCa progression. In recent years, compelling evidence indicates that the use of miRNAs, individually or in combination, in the form of miRNA panels in both tissue and body fluids, together with clinicopathological parameters, might act as a diagnostic biomarker. This will increase the accuracy of risk stratification and early screening of PCa patients under active surveillance. These findings will help differentiate aggressive PCa from indolent and decipher novel therapeutic findings. We have put together a review of studies that have found and confirmed miRNA panels in PCa tissue and PCa liquid biopsies (serum, plasma, and urine exosomes), with a focus on how they might help patients.
Multi-parametric [18F]PI-2620 tau PET/MRI for the phenotyping of different Alzheimer’s disease variants
Authors: Rullmann Michael , Henssen Dylan , Melasch Juliana T. , Scherlach Cordula , Saur Dorothee , Schroeter Matthias L. , Tiepolt Solveig , Koglin Norman , Stephens Andrew W. , Hesse Swen , Strauss Maria , Brendel Matthias , Mishchenko Olena , Schildan Andreas , Classen Joseph , Hoffmann Karl-Titus , Sabri Osama , Barthel Henryk ,   for the German Imaging Initiative for Tauopathies (GII4T)
Published: February 2025

Abstract

Purpose
Heterogeneity in clinical phenotypes has led to the description of different phenotypes of Alzheimer’s disease (AD). Besides the most frequent amnestic variant of AD (aAD), patients presenting with language deficits are diagnosed with logopenic variant primary progressive aphasia (lvPPA), whereas patients presenting with visual deficits are classified as posterior cortical atrophy (PCA).

Methods
This study set out to investigate the value of a multi-parametric [18F]PI-2620 tau PET/MRI protocol to distinguish aAD, lvPPA and PCA to support clinical diagnosis in 32 patients. Phenotype-specific information about tau accumulation, relative perfusion, grey matter density, functional network alterations and white matter microstructural alterations was collected.

Results
The aAD patients showed significantly higher tau accumulation, relative hypoperfusion and grey matter density loss in the temporal lobes compared to PCA and lvPPA patients. PCA patients, on the other hand, showed significantly higher tau accumulation in the occipital lobe as compared to aAD patients. Relative hypoperfusion in the occipital lobe and loss of functional connectivity of the posterior cingulate cortex to supplementary visual cortical regions helped to distinguish PCA from lvPPA. Tau accumulation in the cerebellum and microstructural changes in the cingulum were found to help differentiate lvPPA from aAD.

Conclusion
This study highlights structural and functional differences between patients with different AD phenotypes. Differences in regional tau PET signals suggest that refinements in the Braak staging system are needed for the non-aAD cases. These patterns of tau accumulation align with the cascading network failure hypothesis, though more research is needed to warrant the here presented results in larger patient cohorts.