bluuebunny/crossref_metadata_2025_split huggingface dataset:
The fractions skill score for ensemble forecast verification
Authors: Necker Tobias , Wolfgruber Ludwig , Kugler Lukas , Weissmann Martin , Dorninger Manfred , Serafin Stefano 
Published: August 2024

AbstractThe fractions skill score (FSS) is a neighbourhood verification method originally designed to verify deterministic forecasts of binary events. Previous studies employed different approaches for computing an ensemble‐based FSS for probabilistic forecast verification. We show that the formulation of an ensemble‐based FSS substantially affects verification results. Comparing four possible approaches, we determine how different ensemble‐based FSS variants depend on ensemble size, neighbourhood size, and forecast event frequency of occurrence. We demonstrate that only one ensemble‐based FSS, which we call the probabilistic FSS (pFSS), is well behaved and reasonably dependent on ensemble size. Furthermore, we derive a relationship to describe how the pFSS behaves with ensemble size. The proposed relationship is similar to a known result for the Brier skill score. Our study uses high‐resolution 1000‐member ensemble precipitation forecasts from a high‐impact weather period. The large ensemble enables us to study the influence of ensemble and neighbourhood size on forecast skill by deriving probabilistic skilful spatial scales.
Strong consensus of convex second‐order multi‐agent systems with time‐varying topologies
Authors: Jin Yongfang , Liu Xingwen , Cao Mengtao , Tashi Nyima 
Published: August 2024

SummaryThis paper addresses the strong consensus problem of convex second‐order discrete‐time multi‐agent systems (MASs) with time‐varying topologies. The convex second‐order discrete‐time MAS model is derived from the Langevin equation and therefore has a certain physical significance. The strong consensus here means that all the first‐ and second‐order states converge to an identical value. Some fully distributed control protocols are designed with time‐varying weights randomly chosen from an arbitrary finite set. These protocols are applicable to several cases where changing topologies may be directed or undirected, and connected or disconnected. As a special case, the condition for convex second‐order MASs with fixed topologies to achieve the strong consensus is presented. Finally, two simulation examples illustrate the proposed results.
Terrain‐aware path planning via semantic segmentation and uncertainty rejection filter with adversarial noise for mobile robots
Authors: Lee Kangneoung , Lee Kiju 
Published: August 2024

AbstractIn ground mobile robots, effective path planning relies on their ability to assess the types and conditions of the surrounding terrains. Neural network‐based methods, which primarily use visual images for terrain classification, are commonly employed for this purpose. However, the reliability of these models can vary due to inherent discrepancies between the training images and the actual environment, leading to erroneous classifications and operational failures. Retraining models with additional images from the actual operating environment may enhance performance, but obtaining these images is often impractical or impossible. Moreover, retraining requires substantial offline processing, which cannot be performed online by the robot within an embedded processor. To address this issue, this paper proposes a neural network‐based terrain classification model, trained using an existing data set, with a novel uncertainty rejection filter (URF) for terrain‐aware path planning of mobile robots operating in unknown environments. A robot, equipped with a pretrained model, initially collects a small number of images (10 in this work) from its current environment to set the target uncertainty ratio of the URF. The URF then dynamically adjusts its sensitivity parameters to identify uncertain regions and assign associated traversal costs. This process occurs entirely online, without the need for offline procedures. The presented method was evaluated through simulations and physical experiments, comparing the point‐to‐point trajectories of a mobile robot equipped with (1) the neural network‐based terrain classification model combined with the presented adaptive URF, (2) the classification model without the URF, and (3) the classification model combined with a nonadaptive version of the URF. Path planning performance measured the Hausdorff distances between the desired and actual trajectories and revealed that the adaptive URF significantly improved performance in both simulations and physical experiments (conducted 10 times for each setting). Statistical analysis via t‐tests confirmed the significance of these results.
Ionic Polymers with Phenolic Hydroxyl Groups as Hydrogen Bond Donors Toward Enhanced Catalytic Performance for CO2 Conversion
Authors: Zhu Lihua , Huang Ziying , Ge Tianhao , Jiang Chaoqi , Zhong Wei , Kannan Palanisamy 
Published: August 2024

AbstractIn this study, imidazolium‐based multifunctional ionic polymer (IP 1–IP 3) series, co‐incorporated with phenolic hydroxyl groups as hydrogen bond donors (HBDs) and Cl− as nucleophiles, are synthesized by a facile quaternization method. The physicochemical characterizations of these IPs are systematically examined by using FTIR, XPS, BET, TGA, CO2‐TPD, SEM with elemental mapping and TEM methods. Their catalytic activities are evaluated toward the conversion of carbon dioxide (CO2) and epoxides into cyclic carbonates under solvent‐ and additive‐free environments. Apart from the synergy effect between HBDs and Cl−, it is found that the types of the spacer linking the two imidazole units in the diimidazole precursors (L1–L3) also play an important role in the catalytic activity. And IP 2, with a pyridine spacer as a Lewis base site, exhibits the best catalytic performance under solvent‐free mild conditions i. e., atmospheric pressure CO2, 80 °C, and 5 h. Notably, the catalyst demonstrates a good substrate applicability. Furthermore, IP 2 exhibited good reusability, stability, and it can be recycled for ten successive runs with stable and potential catalytic activity. This study provides an alternative route to construct IPs with efficient activity for CO2 catalytic conversion and fixation under mild‐conditions.
Selective Amphiphile‐Probed Liquid Crystal‐Based Sensing Platform for Monitoring Heavy Metal Ions in Drinking Water
Authors: Rashid Madeeha , Pandey Satyabratt , Singh Vishal , Singh Garima , Singh Sachin Kumar 
Published: August 2024

AbstractThis study presents a new method for detecting and monitoring heavy metal ions in water samples. The method uses liquid crystal‐based optical sensors and a molecular probe called dodecyl‐N‐iminodiacetic acid (DIDAA). The probe's hydrophilic polar diacetate head group acts as a chelator for heavy metal ions, while its hydrophobic non‐polar tail aligns the liquid crystal molecules. When heavy metal ion‐contaminated water samples are introduced, the LC alignment is rapidly disrupted, resulting in bright optical signals. The sensor has a detection limit of 0.1, 0.3, 1.0, and 5.0 μM for for Mercury (Hg2+), Copper (Cu2+), Cadmium (Cd2+), and Lead (Pb2+) respectively. The diacetate probe remains effective even after multiple uses and was not affected by changes in pH. Its activity could persist for over 5 days. Furthermore, this sensor could be reversed and reused to detect HMIs in the presence of EDTA, making it a potential candidate for developing logic gates at the molecular level.
Economic nationalism and the home court advantage
Authors: Choudhury Arnab , Jandhyala Srividya , Nandkumar Anand 
Published: August 2024

AbstractResearch SummaryPolitical and regulatory actors routinely adopt or enforce policies to protect domestic firms at the expense of foreign firms. However, since courts are expected to be neutral and act independently, a question arises whether (and why) they discriminate against foreign firms. We argue that the courts are nationalistic, which emanates from judges differentiating between in‐group (domestic) and out‐group (foreign) members. In a sample of 58,754 patent disputes adjudicated by US federal district courts between 1983 and 2016, we find domestic patent holders and challengers are more successful than their foreign counterparts. Rulings involving foreign firms are more likely to exhibit nationalistic rhetoric. Judicial ideology moderates the differential odds of success between domestic and foreign firms. Thus, the legal system is another source of economic nationalism.Managerial SummaryMultinational firms might face a disadvantage relative to domestic firms because politicians and regulators are nationalistic; they routinely adopt policies that favor domestic firms. If courts are neutral, this disadvantage should not exist in litigation between multinational and domestic firms. On the contrary, if courts are also nationalistic, domestic firms should enjoy an advantage and greater success than multinational firms in judicial verdicts. Using data on patent disputes in the United States observed over a 33‐year period, we find domestic patent holders and challengers are more successful than their foreign counterparts suggesting that the legal system is another source of economic nationalism. Rulings involving multinationals are more likely to exhibit nationalistic rhetoric. Judicial ideology moderates the differential odds of success between domestic and multinational firms.
CO2 Uptake and Stability Enhancement in Vinyltrimethoxysilane‐Treated SBA‐15 Solid Amine‐Based Sorbents
Authors: Vallace Anthony , Campbell Zachary S. , Moon Hyun June , Koros William J. , Jones Christopher W. , Lively Ryan P. 
Published: August 2024

AbstractSilica‐supported amine absorbents, including materials produced by tethering aminosilanes or infusion of poly(ethyleneimine), represent a promising class of materials for CO2 capture applications, including direct air and point source capture. Various silica surface treatments and functionalization strategies are explored to enhance stability and CO2 uptake in amine‐based solid sorbent systems. Here, the synthesis and characterization of novel vinyltrimethoxysilane‐treated Santa Barbara Amorphous‐15 (SBA‐15) supports and the corresponding enhancement in CO2 uptake compared to various SBA‐15‐based control supports are presented. The relationship between CO2 diffusion and amine efficiency in these systems is explored using a previously reported kinetic model. The synthesized materials are characterized with CO2 and H2O isotherms, diffuse reflectance infrared Fourier transform spectroscopy, 1H T1–T2 relaxation correlation NMR, and rapid thermal cycling experiments. The novel support materials are shown to enable high amine efficiencies, approaching a fourfold improvement over standard SBA‐15‐supported amines, while simultaneously exhibiting excellent stability when cycled rapidly under humid conditions. As the poly(ethyleneimine) loadings are held constant across the various samples, enhancements in CO2 uptake are attributed to differences in the way the poly(ethyleneimine) interacts with the support surface.
Amino‐Functionalized Metal–Organic Frameworks Featuring Ultra‐Strong Ethane Nano‐Traps for Efficient C2H6/C2H4 Separation
Authors: Zhang Li‐Ping , Guan Guo‐Wei , Li Yi‐Tao , Liu Hao‐Ran , Zheng Su‐Tao , Jiang Yu , Bai Rui , Yang Qing‐Yuan 
Published: August 2024

AbstractDeveloping high‐performance porous materials to separate ethane from ethylene is an important but challenging task in the chemical industry, given their similar sizes and physicochemical properties. Herein, a new type of ultra‐strong C2H6 nano‐trap, CuIn(3‐ain)4 is presented, which utilizes multiple guest‐host interactions to efficiently capture C2H6 molecules and separate mixtures of C2H6 and C2H4. The ultra‐strong C2H6 nano‐trap exhibits the high C2H6 (2.38 mmol g−1) uptake at 6.25 kPa and 298 K and demonstrates a remarkable selectivity of 3.42 for C2H6/C2H4 (10:90). Additionally, equimolar C2H6/C2H4 exhibited a superior high separation potential ∆Q (2286 mmol L−1) at 298 K. Kinetic adsorption tests demonstrated that CuIn(3‐ain)4 has a high adsorption rate for C2H6, establishing it as a new benchmark material for the capture of C2H6 and the separation of C2H6/C2H4. Notably, this exceptional performance is maintained even at a higher temperature of 333 K, a phenomenon not observed before. Theoretical simulations and single‐crystal X‐ray diffraction provide critical insights into how selective adsorption properties can be tuned by manipulating pore dimensions and geometry. The excellent separation performance of CuIn(3‐ain)4 has been confirmed through breakthrough experiments for C2H6/C2H4 gas mixtures.
Nb Doping Induced the Formation of Protective Layer to Improve the Stability of Fe‐Ni3S2 for Seawater Electrolysis
Authors: Xing Minghui , Wang Shitao , Yun Jimmy , Cao Dapeng 
Published: August 2024

AbstractThe seawater electrolysis to produce hydrogen is a significant topic on alleviating the energy crisis. Here, the Fe, Nb‐Ni3S2 catalyst is prepared by metal‐doping strategy, and it shows high oxygen evolution reaction (OER) activity in alkaline medium, and only needs 1.491 V to deliver a current density of 100 mA cm−2 in simulated seawater. Using Fe, Nb‐Ni3S2 as a bifunctional catalyst, the two‐electrode electrolyzer only requires a voltage of 1.751 V (without impedance compensation) to drive the current density of 50 mA cm−2, and can run over 150 h stably in the simulated seawater. Importantly, In situ Raman test demonstrates that the outstanding performance of Fe, Nb‐Ni3S2 in simulated seawater is ascribed to the in situ formed sulfate protective layer induced by Nb doping, which can effectively inhibit the corrosion of chloride ion, while the protective layer is absent for Fe‐Ni3S2. The stable operation of simulated seawater electrolysis under industrial current density further confirms the stability improvement mechanism of forming protective layer. In short, this study provides a new strategy of using Nb dopants inducing the formation of protective layer to enhance the stability of seawater electrolysis.
Ternary Passivation for Enhanced Carrier Transport and Recombination Suppression in Highly Efficient Sn‐Based Perovskite Solar Cells
Authors: Wang Liang , Miao Qingqing , Wang Dandan , Zhang Zheng , Chen Mengmeng , Bi Huan , Liu Jiaqi , Baranwal Ajay Kumar , Kapil Gaurav , Sanehira Yoshitaka , Kitamura Takeshi , Shen Qing , Ma Tingli , Hayase Shuzi 
Published: August 2024

AbstractThe exploration of nontoxic Sn‐based perovskites as a viable alternative to their toxic Pb‐based counterparts has garnered increased attention. However, the power conversion efficiency of Sn‐based perovskite solar cells lags significantly behind their Pb‐based counterparts. This study presents a ternary passivation strategy aimed at enhancing device performance, employing [6,6]‐phenyl‐C61‐butyric‐acid‐methyl‐ester (PCBM), poly(3‐hexylthiophene) (P3HT), and indene C60 bisadduct (ICBA). These components play crucial roles in managing energy levels and enhancing carrier transportation, respectively. The results reveal that the introduction of the ternary system leads to improvements in carrier collection and transportation, accompanied by a suppression of the recombination process. Ultimately, the champion device achieves a remarkable performance with an efficiency of 14.64%. Notably, the device also exhibits robust operational and long‐term stored stability.
IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts
Authors: Ji Shunhui , Gong Jiahao , Dong Hai , Zhang Pengcheng , Zhu Shaoqing 
Published: August 2024

AbstractWith the widespread application of smart contracts, there is a growing concern over the quality assurance of smart contracts. The data flow testing is an important technology to ensure the correctness of smart contracts. We propose an approach named IABC‐TCG (Improved Artificial Bee Colony‐Test Case Generation) to generate test cases for the data flow testing of smart contracts. With a dominance relations‐based fitness function, an improved artificial bee colony algorithm is used to generate test cases, in which the bee colony search coefficient is adaptively adjusted to improve the effectiveness and efficiency of the search. In addition, an improved test case selection and updation strategy is used to avoid unnecessary test cases. The experimental results show that IABC‐TCG achieves 100% coverage for all the test requirements on a dataset of 30 smart contracts and outperforms the baseline approaches in terms of the number of test cases and the execution time. Performing tests with the generated test cases, IABC‐TCG can find more errors with less test cost.
High Quality Epitaxial Piezoelectric and Ferroelectric Wurtzite Al1‐xScxN Thin Films
Authors: Zeng Yang , Lei Yihan , Wang Yanghe , Cheng Mingqiang , Liao Luocheng , Wang Xuyang , Ge Jinxin , Liu Zhenghao , Ming Wenjie , Li Chao , Xie Shuhong , Li Jiangyu , Li Changjian 
Published: August 2024

AbstractPiezoelectric and ferroelectric wurtzite are promising to reshape modern microelectronics because they can be easily integrated with mainstream semiconductor technology. Sc doped AlN (Al1‐xScxN) has attracted much attention for its enhanced piezoelectric and emerging ferroelectric properties, yet the commonly used sputtering results in polycrystalline Al1‐xScxN films with high leakage current. Here, the pulsed laser deposition of single crystalline epitaxial Al1‐xScxN thin films on sapphire and 4H‐SiC substrates is reported. Pure wurtzite phase is maintained up to x = 0.3 with ≤0.1 at% oxygen contamination. Polarization is estimated to be 140 µC cm−2 via atomic scale microscopy imaging and found to be switchable via a scanning probe. The piezoelectric coefficient is found to be five times of the undoped one when x = 0.3, making it desirable for high‐frequency radiofrequency (RF) filters and 3D nonvolatile memories.
PIoT‐fortifying IoT device identity and data access: A security framework empowered by blockchain
Authors: Janani K. , Ramamoorthy S. 
Published: August 2024

AbstractThe IoT, which refers to the process in which billions of devices are connected to the Internet, has emerged as an essential component of today's society. Yet, the safety of data exchange and the identification of devices in IoT networks have emerged as significant concerns in recent years. Also, there will be a significant drop in the effectiveness of the conventional consensus process. This study presents a novel consensus technique, Proof of IoT (PIoT), to address the security and authentication‐related issues in the IoT Infrastructure. It uses blockchain‐based smart contracts to securely transfer the data and uniquely identify the device on the IoT‐based network. PIoT uses a reputation assessment technique that involves complex cryptographic NuCypher‐based security computations to authenticate and update the data across IoT devices. This contract assures that only authorized parties can access the information recorded in the blockchain. A reward‐based filtering technique is developed for PIoT to identify malicious nodes with harmful actions, preventing them from contributing to consensus. Compared to specific conventional methods, PIoT performs better in simulations. Compared with LPBFT, DAC4SH Consensus, the Point of Interaction in blockchain‐based PIoT improved by 74.7% and 96.8%, respectively. When compared to DAC4SH, PIoT shows an overall 15% improvement in the security of the blockchain under the IoT. In addition to providing a secure method of communication between IoT devices, the given study also provides security against various IoT attacks.
Biological effects of sodium phenylbutyrate and taurursodiol in Alzheimer's disease
Authors: Arnold Steven E. , Hendrix Suzanne , Nicodemus‐Johnson Jessie , Knowlton Newman , Williams Victoria J. , Burns Jeffrey M. , Crane Monica , McManus Alison J. , Vaishnavi Sanjeev N. , Arvanitakis Zoe , Neugroschl Judith , Bell Karen , Trombetta Bianca A. , Carlyle Becky C. , Kivisäkk Pia , Dodge Hiroko H. , Tanzi Rudolph E. , Yeramian Patrick D. , Leslie Kent 
Published: August 2024

AbstractINTRODUCTIONSodium phenylbutyrate and taurursodiol (PB and TURSO) is hypothesized to mitigate endoplasmic reticulum stress and mitochondrial dysfunction, two of many mechanisms implicated in Alzheimer's disease (AD) pathophysiology.METHODSThe first‐in‐indication phase 2a PEGASUS trial was designed to gain insight into PB and TURSO effects on mechanistic targets of engagement and disease biology in AD. The primary clinical efficacy outcome was a global statistical test combining three endpoints relevant to disease trajectory (cognition [Mild/Moderate Alzheimer's Disease Composite Score], function [Functional Activities Questionnaire], and total hippocampal volume on magnetic resonance imaging). Secondary clinical outcomes included various cognitive, functional, and neuropsychiatric assessments. Cerebrospinal fluid (CSF) biomarkers spanning multiple pathophysiological pathways in AD were evaluated in participants with both baseline and Week 24 samples (exploratory outcome).RESULTSPEGASUS enrolled 95 participants (intent‐to‐treat [ITT] cohort); cognitive assessments indicated significantly greater baseline cognitive impairment in the PB and TURSO (n = 51) versus placebo (n = 44) group. Clinical efficacy outcomes did not significantly differ between treatment groups in the ITT cohort. CSF interleukin‐15 increased from baseline to Week 24 within the placebo group (n = 34). In the PB and TURSO group (n = 33), reductions were observed in core AD biomarkers phosphorylated tau‐181 (p‐tau181) and total tau; synaptic and neuronal degeneration biomarkers neurogranin and fatty acid binding protein‐3 (FABP3); and gliosis biomarker chitinase 3‐like protein 1 (YKL‐40), while the oxidative stress marker 8‐hydroxy‐2‐deoxyguanosine (8‐OHdG) increased. Between‐group differences were observed for the Aβ42/40 ratio, p‐tau181, total tau, neurogranin, FABP3, YKL‐40, interleukin‐15, and 8‐OHdG. Additional neurodegeneration, inflammation, and metabolic biomarkers showed no differences between groups.DISCUSSIONWhile between‐group differences in clinical outcomes were not observed, most likely due to the small sample size and relatively short treatment duration, exploratory biomarker analyses suggested that PB and TURSO engages multiple pathophysiologic pathways in AD.Highlights
Proteostasis and mitochondrial stress play key roles in Alzheimer's disease (AD).
Sodium phenylbutyrate and taurursodiol (PB and TURSO) targets these mechanisms.
The PEGASUS trial was designed to assess PB and TURSO effects on biologic AD targets.
PB and TURSO reduced exploratory biomarkers of AD and neurodegeneration.
Supports further clinical development of PB and TURSO in neurodegenerative diseases.