bluuebunny/crossref_metadata_2025 huggingface dataset:
Anti-CCL2 antibody combined with etoposide prolongs survival in a minimal residual disease mouse model of neuroblastoma
Authors: Lascano Danny , Zobel Michael J. , Lee William G. , Chen Stephanie Y. , Zamora Abigail , Asuelime Grace E. , Choi So Yung , Chronopoulos Antonios , Asgharzadeh Shahab , Marachelian Araz , Park Jinseok , Sheard Michael A. , Kim Eugene S.
Published: November 2023

C–C motif chemokine ligand 2 (CCL2) is a monocyte chemoattractant that promotes metastatic disease and portends a poor prognosis in many cancers. To determine the potential of anti-CCL2 inhibition as a therapy for recurrent metastatic disease in neuroblastoma, a mouse model of minimal residual disease was utilized in which residual disease was treated with anti-CCL2 monoclonal antibody with etoposide. The effect of anti-CCL2 antibody on neuroblastoma cells was determined in vitro with cell proliferation, transwell migration, and 2-dimensional chemotaxis migration assays. The in vivo efficacy of anti-CCL2 antibody and etoposide against neuroblastoma was assessed following resection of primary tumors formed by two cell lines or a patient-derived xenograft (PDX) in immunodeficient NOD-scid gamma mice. In vitro, anti-CCL2 antibody did not affect cell proliferation but significantly inhibited neuroblastoma cell and monocyte migration towards an increasing CCL2 concentration gradient. Treatment of mice with anti-CCL2 antibody combined with etoposide significantly increased survival of mice after resection of primary tumors, compared to untreated mice.
State preparation in a Jaynes-Cummings lattice with quantum optimal control
Authors: Parajuli Prabin , Govindarajan Anuvetha , Tian Lin
Published: November 2023

High-fidelity preparation of quantum states in an interacting many-body system is often hindered by the lack of knowledge of such states and by limited decoherence times. Here, we study a quantum optimal control (QOC) approach for fast generation of quantum ground states in a finite-sized Jaynes-Cummings lattice with unit filling. Our result shows that the QOC approach can generate quantum many-body states with high fidelity when the evolution time is above a threshold time, and it can significantly outperform the adiabatic approach. We study the dependence of the threshold time on the parameter constraints and the connection of the threshold time with the quantum speed limit. We also show that the QOC approach can be robust against control errors. Our result can lead to advances in the application of the QOC to many-body state preparation.
Dendrometers challenge the ‘moon wood concept’ by elucidating the absence of lunar cycles in tree stem radius oscillation
Authors: Tumajer Jan , Braun Sabine , Burger Andreas , Scharnweber Tobias , Smiljanic Marko , Walthert Lorenz , Zweifel Roman , Wilmking Martin
Published: November 2023

Wood is a sustainable natural resource and an important global commodity. According to the ‘moon wood theory’, the properties of wood, including its growth and water content, are believed to oscillate with the lunar cycle. Despite contradicting our current understanding of plant functioning, this theory is commonly exploited for marketing wooden products. To examine the moon wood theory, we applied a wavelet power transformation to series of 2,000,000 hourly stem radius records from dendrometers. We separated the influence of 74 consecutive lunar cycles and meteorological conditions on the stem variation of 62 trees and six species. We show that the dynamics of stem radius consist of overlapping oscillations with periods of 1 day, 6 months, and 1 year. These oscillations in stem dimensions were tightly coupled to oscillations in the series of air temperature and vapour pressure deficit. By contrast, we revealed no imprint of the lunar cycle on the stem radius variation of any species. We call for scepticism towards the moon wood theory, at least as far as the stem water content and radial growth are concerned. We foresee that similar studies employing robust scientific approaches will be increasingly needed in the future to cope with misleading concepts.
A novel directional-oriented method for predicting shear wave velocity through empirical rock physics relationship using geostatistics analysis
Authors: Makarian Esmael , Mirhashemi Maryam , Elyasi Ayub , Mansourian Danial , Falahat Reza , Radwan Ahmed E. , El-Aal Ahmed , Fan Cunhui , Li Hu
Published: November 2023

This study attempts to design a novel direction–oriented approach for estimating shear wave velocity (VS) through geostatistical methods (GM) using density employing geophysical log data. The research area involves three hydrocarbon wells drilled in carbonate reservoirs that are comprised of oil and water. Firstly, VSwas estimated using the four selected empirical rock physics relationships (ERR) in well A (target well), and then all results were evaluated by ten statistical benchmarks. All results show that the best ERR is Greenberg and Castagna, with R2 = 0.8104 and Correlation = 0.90, while Gardner's equation obtained the poorest results with R2 = 0.6766 and correlation = 0.82. Next, Gardner's method was improved through GM by employing Ordinary Kriging (OKr) in two directions in well A, and then Cross-Validation and Jack-knife methods (JKm and CVm, respectively) were used to assess OKr's performance and efficiency. Initially, CVm and JKm were employed to estimate Vs using the available density and its relationship with shear wave velocity, where the performance of CVm was better with R2 = 0.8865 and correlation = 0.94. In this step, some points from the original VSwere used to train the data. Finally, Vs was estimated through JKm and using the relationship between the shear wave velocity of two wells near the target well, including wells B and C; however, in this step, the original shear wave velocity of the target well was completely ignored. Reading the results, JKm could show excellent performance with R2 = 0.8503 and Corr = 0.922. In contrast to previous studies that used only Correlation and R-squared (R2), this study further provides accurate results by employing a wide range of statistical benchmarks to investigate all results. In contrast to traditional empirical rock physics relationships, the developed direction-oriented technique demonstrated improved predicted accuracy and robustness in the investigated carbonate field. This work demonstrates that GM can effectively estimate Vs and has a significant potential to enhance VSestimation using density.
Image denoising and segmentation model construction based on IWOA-PCNN
Authors: Zhang Xiaojun
Published: November 2023

The research suggests a method to improve the present pulse coupled neural network (PCNN), which has a complex structure and unsatisfactory performance in image denoising and image segmentation. Then, a multi strategy collaborative improvement whale optimization algorithm (WOA) is proposed, and an improved whale optimization algorithm (IWOA) is constructed. IWOA is used to find the optimal parameter values of PCNN to optimize PCNN. By combining the aforementioned components, the IWOA-PCNN model had the best image denoising performance, and the produced images were crisper and preserve more information. IWOA-PCNN processed pictures have an average PSNR of 35.87 and an average MSE of 0.24. The average processing time for photos with noise is typically 24.80 s, which is 7.30 s and 7.76 s faster than the WTGAN and IGA-NLM models, respectively. Additionally, the average NU value measures 0.947, and the average D value exceeds 1000. The aforementioned findings demonstrate that the suggested method can successfully enhance the PCNN, improving its capability for image denoising and image segmentation. This can, in part, encourage the use and advancement of the PCNN.
Synthesis, molecular docking, and in vivo antidiabetic evaluation of new benzylidene-2,4-thiazolidinediones as partial PPAR-γ agonists
Authors: Najmi Asim , Alam Md Shamsher , Thangavel Neelaveni , Taha Manal M. E. , Meraya Abdulkarim M. , Albratty Mohammed , Alhazmi Hassan A. , Ahsan Waquar , Haque Anzarul , Azam Faizul
Published: November 2023

Peroxisome proliferator-activated receptor-γ (PPAR-γ) partial agonists or antagonists, also termed as selective PPAR-γ modulators, are more beneficial than full agonists because they can avoid the adverse effects associated with PPAR-γ full agonists, such as weight gain and congestive heart disorders, while retaining the antidiabetic efficiency. In this study, we designed and synthesized new benzylidene-thiazolidine-2,4-diones while keeping the acidic thiazolidinedione (TZD) ring at the center, which is in contrast with the typical pharmacophore of PPAR-γ agonists. Five compounds (5a–e) were designed and synthesized in moderate to good yields and were characterized using spectral techniques. The in vivo antidiabetic efficacy of the synthesized compounds was assessed on streptozotocin-induced diabetic mice using standard protocols, and their effect on weight gain was also studied. Molecular docking and molecular dynamics (MD) simulation studies were performed to investigate the binding interactions of the title compounds with the PPAR-γ receptor and to establish their binding mechanism. Antidiabetic activity results revealed that compounds 5d and 5e possess promising antidiabetic activity comparable with the standard drug rosiglitazone. No compound showed considerable effect on the body weight of animals after 21 days of administration, and the findings showed statistical difference (p < 0.05 to p < 0.0001) among the diabetic control and standard drug rosiglitazone groups. In molecular docking study, compounds 5c and 5d exhibited higher binding energies (− 10.1 and − 10.0 kcal/mol, respectively) than the native ligand, non-thiazolidinedione PPAR-γ partial agonist (nTZDpa) (− 9.8 kcal/mol). MD simulation further authenticated the stability of compound 5c-PPAR-γ complex over the 150 ns duration. The RMSD, RMSF, rGyr, SASA, and binding interactions of compound 5c-PPAR-γ complex were comparable to those of native ligand nTZDpa-PPAR-γ complex, suggesting that the title compounds have the potential to be developed as partial PPAR-γ agonists.
Plasticity-led evolution as an intrinsic property of developmental gene regulatory networks
Authors: Ng Eden Tian Hwa , Kinjo Akira R.
Published: November 2023

The modern evolutionary synthesis seemingly fails to explain how a population can survive a large environmental change: the pre-existence of heritable variants adapted to the novel environment is too opportunistic, whereas the search for new adaptive mutations after the environmental change is so slow that the population may go extinct. Plasticity-led evolution, the initial environmental induction of a novel adaptive phenotype followed by genetic accommodation, has been proposed to solve this problem. However, the mechanism enabling plasticity-led evolution remains unclear. Here, we present computational models that exhibit behaviors compatible with plasticity-led evolution by extending the Wagner model of gene regulatory networks. The models show adaptive plastic response and the uncovering of cryptic mutations under large environmental changes, followed by genetic accommodation. Moreover, these behaviors are consistently observed over distinct novel environments. We further show that environmental cues, developmental processes, and hierarchical regulation cooperatively amplify the above behaviors and accelerate evolution. These observations suggest plasticity-led evolution is a universal property of complex developmental systems independent of particular mutations.
Synergistic effect of perovskites and nitrogen-doped carbon hybrid materials for improving oxygen reduction reaction
Authors: Rohib R. , Rehman Saeed Ur , Lee Eunjik , Kim Changki , Lee Hyunjoon , Lee Seung-Bok , Park Gu-Gon
Published: November 2023

A fundamental understanding of the electrochemical behavior of hybrid perovskite and nitrogen-doped (N-doped) carbon is essential for the development of perovskite-based electrocatalysts in various sustainable energy device applications. In particular, the selection and modification of suitable carbon support are important for enhancing the oxygen reduction reaction (ORR) of non-platinum group metal electrocatalysts in fuel cells. Herein, we address hybrid materials composed of three representative N-doped carbon supports (BP-2000, Vulcan XC-72 and P-CNF) with valid surface areas and different series of single, double and triple perovskites: Ba0.5Sr0.5Co0.8Fe0.2O3−δ, (Pr0.5Ba0.5)CoO3−δ, and Nd1.5Ba1.5CoFeMnO9−δ (NBCFM), respectively. The combination of NBCFM and N-doped BP-2000 produces a half-wave potential of 0.74 V and a current density of 5.42 mA cm−2 at 0.5 V versus reversible hydrogen electrode, comparable to those of the commercial Pt/C electrocatalyst (0.76 V, 5.21 mA cm−2). Based on physicochemical and electrochemical analyses, we have confirmed a significant improvement in the catalytic performance of low-conductivity perovskite catalyst in the ORR when nitrogen-doped carbon with enhanced electrical conductivity is introduced. Furthermore, it has been observed that nitrogen dopants play active sites, contributing to additional performance enhancement when hybridized with perovskite.
A comprehensive assessment of oral health, swallowing difficulty, and nutritional status in older nursing home residents
Authors: Chou Kuei-Ru , Huang Mao-Suan , Chiu Wan-Chun , Chen Yi-Hsiu , Chen Yu-Yoh , Xiao Qian , Yang Suh-Ching
Published: November 2023

Declines in oral consumption and swallowing function are common reasons which may elevate the risk of malnutrition in the older adults. This study aimed to provide valuable information and contribute to the existing body of knowledge in this field as well as highlight the importance of a comprehensive assessment of oral health, swallowing function, and nutritional status in long-term care residents. This was a cross-sectional study. Thirty-nine participants were recruited from a nursing home. The comprehensive assessment was evaluated in participants, including oral health (Oral Health Assessment Tool (OHAT)), swallowing function (Functional Oral Intake Scale (FOIS) and Eating Assessment Tool (EAT)-10), and nutritional status (Mini Nutritional Assessment-Short Form (MNA-SF). The average age of participants was 80.4 ± 11.7 years, and 46% of these older adults were found to be at the risk of malnutrition. There was a negative correlation between the OHAT and MNA-SF scores. In addition, subjects with poor oral health (OHAT score = 5~8), oral consumption of a modified diet (FOIS score = 4~6), and reduced swallowing function (EAT-10 score ≥ 3) were more likely to be at risk of malnutrition. A comprehensive evaluation of oral health and swallowing function was closely connected with the nutritional status of older nursing home dwellers.
Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection
Authors: Leon Raquel , Fabelo Himar , Ortega Samuel , Cruz-Guerrero Ines A. , Campos-Delgado Daniel Ulises , Szolna Adam , Piñeiro Juan F. , Espino Carlos , O’Shanahan Aruma J. , Hernandez Maria , Carrera David , Bisshopp Sara , Sosa Coralia , Balea-Fernandez Francisco J. , Morera Jesus , Clavo Bernardino , Callico Gustavo M.
Published: November 2023

Brain surgery is one of the most common and effective treatments for brain tumour. However, neurosurgeons face the challenge of determining the boundaries of the tumour to achieve maximum resection, while avoiding damage to normal tissue that may cause neurological sequelae to patients. Hyperspectral (HS) imaging (HSI) has shown remarkable results as a diagnostic tool for tumour detection in different medical applications. In this work, we demonstrate, with a robust k-fold cross-validation approach, that HSI combined with the proposed processing framework is a promising intraoperative tool for in-vivo identification and delineation of brain tumours, including both primary (high-grade and low-grade) and secondary tumours. Analysis of the in-vivo brain database, consisting of 61 HS images from 34 different patients, achieve a highest median macro F1-Score result of 70.2 ± 7.9% on the test set using both spectral and spatial information. Here, we provide a benchmark based on machine learning for further developments in the field of in-vivo brain tumour detection and delineation using hyperspectral imaging to be used as a real-time decision support tool during neurosurgical workflows.
On the functional brain networks involved in tool-related action understanding
Authors: Federico Giovanni , Osiurak François , Ciccarelli Giuseppina , Ilardi Ciro Rosario , Cavaliere Carlo , Tramontano Liberatore , Alfano Vincenzo , Migliaccio Miriana , Di Cecca Angelica , Salvatore Marco , Brandimonte Maria Antonella
Published: November 2023

Tool-use skills represent a significant cognitive leap in human evolution, playing a crucial role in the emergence of complex technologies. Yet, the neural mechanisms underlying such capabilities are still debated. Here we explore with fMRI the functional brain networks involved in tool-related action understanding. Participants viewed images depicting action-consistent (e.g., nail-hammer) and action-inconsistent (e.g., scarf-hammer) object-tool pairs, under three conditions: semantic (recognizing the tools previously seen in the pairs), mechanical (assessing the usability of the pairs), and control (looking at the pairs without explicit tasks). During the observation of the pairs, task-based left-brain functional connectivity differed within conditions. Compared to the control, both the semantic and mechanical conditions exhibited co-activations in dorsal (precuneus) and ventro-dorsal (inferior frontal gyrus) regions. However, the semantic condition recruited medial and posterior temporal areas, whereas the mechanical condition engaged inferior parietal and posterior temporal regions. Also, when distinguishing action-consistent from action-inconsistent pairs, an extensive frontotemporal neural circuit was activated. These findings support recent accounts that view tool-related action understanding as the combined product of semantic and mechanical knowledge. Furthermore, they emphasize how the left inferior parietal and anterior temporal lobes might be considered as hubs for the cross-modal integration of physical and conceptual knowledge, respectively.
The formation of KV2.1 macro-clusters is required for sex-specific differences in L-type CaV1.2 clustering and function in arterial myocytes
Authors: Matsumoto Collin , O’Dwyer Samantha C. , Manning Declan , Hernandez-Hernandez Gonzalo , Rhana Paula , Fong Zhihui , Sato Daisuke , Clancy Colleen E. , Vierra Nicholas C. , Trimmer James S. , Fernando Santana L.
Published: November 2023

In arterial myocytes, the canonical function of voltage-gated CaV1.2 and KV2.1 channels is to induce myocyte contraction and relaxation through their responses to membrane depolarization, respectively. Paradoxically, KV2.1 also plays a sex-specific role by promoting the clustering and activity of CaV1.2 channels. However, the impact of KV2.1 protein organization on CaV1.2 function remains poorly understood. We discovered that KV2.1 forms micro-clusters, which can transform into large macro-clusters when a critical clustering site (S590) in the channel is phosphorylated in arterial myocytes. Notably, female myocytes exhibit greater phosphorylation of S590, and macro-cluster formation compared to males. Contrary to current models, the activity of KV2.1 channels seems unrelated to density or macro-clustering in arterial myocytes. Disrupting the KV2.1 clustering site (KV2.1S590A) eliminated KV2.1 macro-clustering and sex-specific differences in CaV1.2 cluster size and activity. We propose that the degree of KV2.1 clustering tunes CaV1.2 channel function in a sex-specific manner in arterial myocytes.
An atomically tailored chiral magnet with small skyrmions at room temperature
Authors: Liu Tao , Selcu Camelia M. , Wang Binbin , Bagués Núria , Wu Po-Kuan , Hartnett Timothy Q. , Cheng Shuyu , Pelekhov Denis , Bennett Roland A. , Corbett Joseph Perry , Repicky Jacob R. , McCullian Brendan , Chris Hammel P. , Gupta Jay A. , Randeria Mohit , Balachandran Prasanna V. , McComb David W. , Kawakami Roland K.
Published: November 2023

Creating materials that do not exist in nature can lead to breakthroughs in science and technology. Magnetic skyrmions are topological excitations that have attracted great attention recently for their potential applications in low power, ultrahigh density memory. A major challenge has been to find materials that meet the dual requirement of small skyrmions stable at room temperature. Here we meet both these goals by developing epitaxial FeGe films with excess Fe using atomic layer molecular beam epitaxy (MBE) far from thermal equilibrium. Our atomic layer design permits the incorporation of 20% excess Fe while maintaining a non-centrosymmetric crystal structure supported by theoretical calculations and necessary for stabilizing skyrmions. We show that the Curie temperature is well above room temperature, and that the skyrmions have sizes down to 15 nm as imaged by Lorentz transmission electron microscopy (LTEM) and magnetic force microscopy (MFM). The presence of skyrmions coincides with a topological Hall effect-like resistivity. These atomically tailored materials hold promise for future ultrahigh density magnetic memory applications.
Identification and engineering of potent cyclic peptides with selective or promiscuous binding through biochemical profiling and bioinformatic data analysis
Authors: Smith Thomas P. , Bhushan Bhaskar , Granata Daniele , Kaas Christian S. , Andersen Birgitte , Decoene Klaas W. , Ren Qiansheng , Liu Haimo , Qu Xinping , Yang Yang , Pan Jia , Chen Quijia , Münzel Martin , Kawamura Akane
Published: November 2023

In this work different methods stemming from mRNA display were investigated toward developing potent binding cyclic peptides with distinct selectivity profiles against targets of a related protein family.
A designed DNA/amino acid amphiphile-based supramolecular oxidase-mimetic catalyst for colorimetric DNA detection
Authors: Jiang Minquan , Xu Shichao , Liu Yuanxi , Wang Zhen-Gang
Published: November 2023

The self-assembled DNA/Fmoc-amino acids/Cu2+ material exhibits remarkable catechol oxidase-mimetic activity towards catalyzing colorimetric oxidative reaction, which are employed for selective and sensitive detection of DNA hybridization.
CO2 switchable adhesion of ionic polydimethylsiloxane elastomers
Authors: Miwa Yohei , Tsunoda Masatoshi , Shimozaki Shoei , Sawada Rina , Kutsumizu Shoichi
Published: November 2023

Ionic polydimethylsiloxane elastomers have been developed that increase their adhesion rapidly and reversibly upon exposure to CO2 gas.
Cobalt-based tripodal complexes as molecular catalysts for photocatalytic CO2 reduction
Authors: Liu Dong-Cheng , Luo Zhi-Mei , Aramburu-Trošelj Bruno M. , Ma Fan , Wang Jia-Wei
Published: November 2023

The progress in cobalt tripodal complexes as molecular catalysts for CO2 photoreduction is summarized.
Ratiometric analysis of reversible thia-Michael reactions using nitrile-tagged molecules by Raman microscopy
Authors: Yamakoshi Hiroyuki , Shibata Daiki , Bando Kazuki , Kajimoto Shinji , Kohyama Aki , Egoshi Syusuke , Dodo Kosuke , Iwabuchi Yoshiharu , Sodeoka Mikiko , Fujita Katsumasa , Nakabayashi Takakazu
Published: November 2023

Ratiometric Raman analysis of reversible thia-Michael reactions was achieved using α-cyanoacrylic acid (αCNA) derivatives.
Controlled assembly of photosensitizers through directional interactions for effective photooxidation
Authors: Yang Yuntian , He Jirong , Mou Qi , Quan Bo , Jin Mingshi , Cui Chunzhi , Jin Long Yi , Huang Zhegang
Published: November 2023

We report a rational strategy for the generation of a reactive 1O2 system based on the control of hierarchical assemblies of PS-based amphiphiles with fundamental function and morphologically different architectures.
Doping-mediated electronic and magnetic properties of graphene-like ionic NaX (X = F and Cl) monolayers
Authors: Nguyen Thi Bich Ngoc , Ha Chu Viet , Thi Ha Lien Nghiem , Guerrero-Sanchez J. , Hoat D. M.
Published: November 2023

Ionic (a) NaF and (b) NaCl monolayers are predicted. Further effects of doping with IIA- and VIA-group atoms are also analyzed.
Li intercalation in 2D iron phosphate synthesized from the partial dehydration and deprotonation of vivianite
Authors: Yamane Ryo , Li Hongyi , Ichitsubo Tetsu , Sugiyama Kazumasa
Published: November 2023

Li+ can be intercalated into a 2D hydrous iron(ii) phosphate via dehydration and deprotonation.
Discovery of potential RIPK1 inhibitors by machine learning and molecular dynamics simulations
Authors: Liu Ji-xiang , Na Ri-song , Yang Lian-juan , Huang Xu-ri , Zhao Xi
Published: November 2023

Six small molecules from virtual screening hits may treat neurodegenerative diseases and SARS-CoV-2 by inhibiting RIPK1.
Prediction of superconductivity in metallic boron–carbon compounds from 0 to 100 GPa by high-throughput screening
Authors: Zheng Feng , Sun Yang , Wang Renhai , Fang Yimei , Zhang Feng , Wu Shunqing , Lin Qiubao , Wang Cai-Zhuang , Antropov Vladimir , Ho Kai-Ming
Published: November 2023

Boron–carbon compounds have been shown to have feasible superconductivity.
Charge doping and electric field tunable ferromagnetism and Curie temperature of the MnS2 monolayer
Authors: Xie Jing , Wu Dongni , Liao Yangfang , Cao Xiaolong , Zhou Shiyou
Published: November 2023

Two-dimensional ferromagnets with a long-range ferromagnetic ordering at finite temperature present a bright prospect for their potential applications in nanoscale spintronic devices.
Coexistence of superconductivity and charge density wave instability in A15-Nb3Sn
Authors: Wu Li-Na , Yang Si-Tong , Shen Jin-Ke , Zhang Jian-Sheng , Liu Fei-Hu
Published: November 2023

A15-type compound Nb3Sn has attracted much attention due to its relatively high critical temperature and critical field of superconductivity, making it a leading material for superconducting applications.
External electric field, a potential catalyst for C–N cross-coupling reaction
Authors: Yadav Priyanka , Kumar Pradeep
Published: November 2023

The present work investigates the role of the external electric field in boosting the C–N cross-coupling reaction between 2-chlorobenzoic acid and propylamine, by computing the reaction rates and energy barrier.
Assembly of dysprosium(iii) cubanes in a metal–organic framework with an ecu topology and slow magnetic relaxation
Authors: Shao Dong , Wan Yi , Yang Jiong , Ruan Zhijun , Zhu Junlun , Shi Le
Published: November 2023

A rare dysprosium(iii) metal–organic framework constructed using dysprosium(iii) cubanes as secondary building units has been reported to exhibit field-supported single-molecule magnet (SMM) behavior and an unprecedented ecu topology.
Partitioning of secondary organic aerosol onto nanoplastics leading to hygroscopic partially-engulfed particles
Authors: Raincrow Katrina L. , Al-Mashala Habeeb H. , Schnitzler Elijah G.
Published: November 2023

Partitioning of secondary organic aerosol from α-pinene onto hydrophobic polystyrene nanoplastics leads to partially-engulfed particles that undergo hygroscopic growth.
Electrochemical degradation of a C6-perfluoroalkyl substance (PFAS) using a simple activated carbon cathode
Authors: Ackerman Grunfeld Diana , Jones Adele M. , Sun Jun , Le Song Thao , Pickford Russell , Huang Qingguo , Manefield Michael , Kumar Naresh , Lee Matthew J. , O'Carroll Denis M.
Published: November 2023

This scoping study investigates the ability of an inexpensive, commercially available granular activated carbon (GAC) to sorb and conduct electrical charge to achieve reductive defluorination of PFAS.
Single-crystalline oligomer-based conductors modeling the doped poly(3,4-ethylenedioxythiophene) family
Authors: Fujino Tomoko , Kameyama Ryohei , Onozuka Kota , Matsuo Kazuki , Dekura Shun , Yoshimi Kazuyoshi , Mori Hatsumi
Published: November 2023

Oligomer-based charge-transfer complexes display a diversified carrier-to-carrier Coulomb repulsion (Ueff) and intermolecular interactions (W), enabling flexible tuning of electrical conductivities.
A comparative study of palladium-gold and palladium-tin catalysts in the direct synthesis of H2O2
Authors: Kovačič Dávid , Lewis Richard J. , Crombie Caitlin M. , Morgan David J. , Davies Thomas E. , López-Martín Ángeles , Qin Tian , Allen Christopher S. , Edwards Jennifer. K. , Chen Liwei , Skjøth-Rasmussen Martin Skov , Liu Xi , Hutchings Graham J.
Published: November 2023

Supported PdSn catalysts are highly effective for the direct synthesis of hydrogen peroxide showing significantly higher selectivity to comparable PdAu catalysts.
Enriching 2D transition metal borides via MB XMenes (M = Fe, Co, Ir): Strong correlation and magnetism
Authors: Tang Jiawei , Li Shaohan , Wang Duo , Zheng Qi , Zhang Jing , Lu Tao , Yu Jin , Sun Litao , Sa Baisheng , Sumpter Bobby G. , Huang Jingsong , Sun Weiwei
Published: November 2023

We explore a series of new 2D magnetic FeSe-like XMene (anti-MXene) borides, among which FeB exhibits a stable ferromagnetic state with notable MAE and a high Curie temperature, indicating its potential for spintronic applications.
Synthesis, antimicrobial activity and molecular simulation of thiourea derivatives containing 6-carboalkoxybenzo[d]thiazole andd-glucose moieties
Authors: Dinh Thanh Nguyen , Son Hai Do , Thi Kim Giang Nguyen , Ngoc Toan Vu , Thi Kim Van Hoang , Minh Tri Nguyen , Ngoc Toan Duong
Published: November 2023

Substituted benzo[d]thiazole sulfonyl thioureas were synthesized. They exhibited antimicrobial activity, with some inhibitingStaphylococcus aureusDNA gyrase, DNA Topo IV, and dihydrofolate reductase. IFD, MM-GBSA and MD were performed on 6d/2XCS ofS. aureus.
Biocompatible fluorescent europium(iii) magnetic nanoparticles
Authors: Marques Inês J. , Vaz Pedro D. , Girão Ana V. , Nolasco Mariela M. , Nunes Carla D.
Published: November 2023

Silica-coated iron oxide and silica nanoparticles were prepared and derivatized with a Eu(iii) complex to yield magneto-fluorescent and fluorescent nanomaterials that could work as possible biosensors.
Recent progress and perspective for oxygen evolution reaction under acidic environments
Authors: Chen Lianhua , Liu Yuting , Cong Hang , Ge Qingmei , Zhao Wenfeng , Jiang Nan , Zhang Qian
Published: November 2023

Proton exchange membrane (PEM) electrolyzers play a vital role in sustainable energy conversion and storage.
NHC–amine Ru complex catalyzed selective mono-N-methylation of amines with methanol: understanding the effect of amine ligands
Authors: Cai Xiuju , Zhou Xiaoyu , Huang Ming
Published: November 2023

The selective mono-N-methylation of amines with methanol by the bifunctional NHC–NH2 Ru complex is presented.
Nickel-catalyzed dynamic kinetic cross-electrophile coupling of benzylic alcohols and alkenyl triflates
Authors: Peng Xuejing , Huang Jingxian , Han Guan-Yu , Shu Xing-Zhong
Published: November 2023

We report a dynamic kinetic cross-electrophile coupling reaction of benzylic alcohols with alkenyl triflates. The reaction enables replacement of the alcohol group with an alkenyl functionality, yielding versatile benzyl-substituted cyclic alkenes.
Silver-mediated synthesis of 1,4-dihydropyridine sulfones via [4 + 2] cyclization of N-allenylsulfonamides and enaminones with a 1,3-sulfonyl shift
Authors: Zhou Shuguang , Dong Shuang-Feng , Zhang Xin , Zhang Shen-Yuan , Loh Teck-Peng , Tian Jie-Sheng
Published: November 2023

A [4 + 2] cyclization reaction of N-allenylsulfonamides and enaminones towards unsymmetrical 1,4-dihydropyridine sulfones with a 1,3-sulfonyl shift was reported and simple operation for diversification was also achieved.
Bio-based polycarbonates: progress and prospects
Authors: Wang Hao , Xu Fei , Zhang Zhencai , Feng Mi , Jiang Ming , Zhang Suojiang
Published: November 2023

The review covers the advancements in bio-based polycarbonates with regards to their raw materials, polymerization techniques, and modification strategies.
Comment on “Enhancing the output performance of hybrid nanogenerators based on Al-doped BaTiO3 composite films: a self-powered utility system for portable electronics”, by B. Dudem, L. K. Bharat, H. Patnam, A. R. Mule and J. S. Yu, J. Mater. Chem. A, 2018, 6, 16101
Authors: Tkach Alexander , Okhay Olena
Published: November 2023

This Comment discusses a lack of proof for the relationship of the nanogenerator performance reported in J. Mater. Chem. A, 2018, 6, 16101 to the enhanced piezoelectricity and to the Al-doping of BaTiO3 particles used as the nanogenerator core.
One-dimensional amorphous porous iridium–ruthenium oxide for efficient acidic oxygen evolution reaction
Authors: Li Lamei , Cheng Zifang , Su Jiaqi , Song Beibei , Yu Hao , Ji Yujin , Shao Qi , Lu Jianmei
Published: November 2023

One dimensional amorphous porous Ir–Ru oxide nanobelts (NBs) were synthesized by ion exchange method. The Am-Ir1Ru3O8 NBs-250 exhibit an excellent oxygen evolution reaction (OER) activity, outperforming most electrocatalysts reported to date.
Ru nanoparticle decorated Ni(OH)2 nanosheets for highly efficient electrochemical synthesis of 2,5-furandicarboxylic acid: experimental and theoretical studies
Authors: Cheng Zhong , Fu Dingbang , Zhou Wenjing , Deng Wenfang , Tan Yueming , Ma Ming
Published: November 2023

Ru nanoparticle decorated Ni(OH)2 is developed as a high-performance catalyst for the electrochemical synthesis of 5-hydroxymethylfurfural into 2,5-furandicarboxylic acid.
Novel piezoelectric properties of electrospun polyamide-imide nanofiber membranes
Authors: Bai Ruixi , Shao Hao , Chang Haibo , Wang Hongxia , Ding Xiang , Cao Weihua , Cao Yuying , Lin Tong
Published: November 2023

Electrospun polyamide-imide (PAI) nanofiber membranes exhibit excellent piezoelectric properties under both ambient temperature and high-temperature conditions.
Controllable construction of Pt/CNT catalyst layers to improve Pt utilization in PEMFCs
Authors: Pei Yabiao , Zhu Weikang , Yue Runfei , Wang Lianqin , Li Ran , Zhang Junfeng , Yin Yan
Published: November 2023

The cathode catalyst layer, constructed with carbon nanotube-supported nano-Pt, exhibits high fuel cell performance due to enhanced mass transfer efficiency and Pt utilization.
Hierarchical peroxiredoxin assembly through orthogonal pH-response and electrostatic interactions
Authors: Anaya-Plaza Eduardo , Özdemir Zulal , Wimmer Zdenek , Kostiainen Mauri A.
Published: November 2023

Highly ordered anisotropic assemblies of toroidal peroxiredoxin protein cage are reported by the sequential and orthogonal input of pH and chemical stimuli.
Manipulation of cross-linking in PEDOT:PSS hydrogels for biointerfacing
Authors: Goestenkors Anna P. , Liu Tianran , Okafor Somtochukwu S. , Semar Barbara A. , Alvarez Riley M. , Montgomery Sandra K. , Friedman Lianna , Rutz Alexandra L.
Published: November 2023

The effect of gelling agent concentration (ionic liquid) on PEDOT:PSS hydrogel fabrication and properties was investigated. Gelation kinetics, stability, swelling, stiffness, conductivity, and support of seeded cells were characterized.
Industrially-friendly rapid printing of stretchable liquid metal circuits for patch-mode wearable healthcare devices
Authors: Jia Yanling , Zhang Ke
Published: November 2023

Sponge-roller assisted liquid metal printing (SALP) technology provides an industrially-friendly method for achieving rapid and economical liquid metal electrode or circuit printing.
Unveiling the electronic properties of metal-free and undoped covalent organic framework as a semiconductor
Authors: Yadav Kushagra , Budakoti Praveen K. , Dhakate S. R.
Published: November 2023

Experimental and theoretical validation of a triazine-based covalent organic framework as a semiconductor with the band gap in the range of 3.2–3.4 eV.
Significantly enhanced energy storage density in lead-free barium strontium titanate-based ceramics through a cooperative optimization strategy
Authors: Ren Jia-Jia , Xu Di-Ming , Li Da , Zhao Wei-Chen , Xu Meng-Kang , Shi Zhong-Qi , Zhou Tao , Lin Hui-Xing , Zhou Di
Published: November 2023

An ultrahigh Wrec of 5.53 J cm−3 (460 kV cm−1) has been achieved in the 0.91BST–0.09BZT ceramic, together with good temperature stability at 200 kV cm−1 and excellent fatigue resistance.
Facile synthesis of Z-scheme Fe-nPPy/BiOI nanocomposites for enhanced visible light driven photocatalytic activity
Authors: Kumar Rajesh , Gogoi Rituporn , Sharma Kajal , Singh Astha , Siril Prem Felix
Published: November 2023

Development of Z-scheme nanocomposites containing bismuth oxyiodide and conducting polymer is reported here as efficient visible light active photocatalysts.
Association Between Social Determinants of Health and Communication Difficulties in Poststroke U.S. Hispanic and Non-Hispanic White Populations
Authors: Marte Manuel Jose , Addesso David , Kiran Swathi
Published: November 2023

Purpose:

The relationship among ethnicity, social determinants of health (SDOH), and disparities in poststroke outcomes is complex, and the impact on communication difficulties is unclear. This study investigated the presence and nature of communication difficulties in poststroke non-Hispanic White (PsnHw) and Hispanic U.S. populations using population-level data.

Method:

We performed a cross-sectional analysis of 2,861 non-Hispanic White and 353 Hispanic poststroke respondents included in the 2014–2018 National Health Interview Survey. Respondents self-reported difficulties communicating in their usual language, in addition to providing information relating to demographics and lifestyle, health care access and utilization, health status, and SDOH. We used univariate statistics, generalized linear models, and an exploratory mediation analysis, to characterize the pattern of differences between these cohorts, examine associations between variables and communication difficulties, and determine the potential intermediate role of cumulative SDOH on the likelihood of reporting communication difficulties.

Results:

Findings indicated a more challenging life context for the poststroke Hispanic population due to SDOH disparities. Poverty and Internet use were associated with greater and lower odds of communication difficulties for PsnHw, respectively. The mediation analysis showed that ethnicity significantly affected communication difficulties, but only when mediated by SDOH. SDOH accounted for approximately two thirds of the total effect on reporting communication difficulties.

Conclusions:

This study underscores the need for uniform measures of SDOH in prospective research and for interventions aimed at mitigating health disparities through addressing disparities in SDOH. Future research should focus on evaluating the effectiveness of such strategies in diverse ethnic and socioeconomic poststroke populations.

Supplemental Material:

https://doi.org/10.23641/asha.24521419
Automatic Signature Verifier Using Gaussian Gated Recurrent Unit Neural Network
Authors: Khan Sameera , Singh Dileep Kumar , Singh Mahesh , Mena Desta Faltaso
Published: November 2023

Handwritten signatures are one of the most extensively utilized biometrics used for authentication, and forgeries of this behavioral biometric are quite widespread. Biometric databases are also difficult to access for training purposes due to privacy issues. The efficiency of automated authentication systems has been severely harmed as a result of this. Verification of static handwritten signatures with high efficiency remains an open research problem to date. This paper proposes an innovative introselect median filter for preprocessing and a novel Gaussian gated recurrent unit neural network (2GRUNN) as a classifier for designing an automatic verifier for handwritten signatures. The proposed classifier has achieved an FPR of 1.82 and an FNR of 3.03. The efficacy of the proposed method has been compared with the various existing neural network‐based verifiers.
Evaluating the Impact of Data Transformation Techniques on the Performance and Interpretability of Software Defect Prediction Models
Authors: Zhao Yu , Huang Zhiqiu , Gong Lina , Zhu Yi , Yu Qiao , Gao Yuxiang
Published: November 2023

The performance of software defect prediction (SDP) models determines the priority of test resource allocation. Researchers also use interpretability techniques to gain empirical knowledge about software quality from SDP models. However, SDP methods designed in the past research rarely consider the impact of data transformation methods, simple but commonly used preprocessing techniques, on the performance and interpretability of SDP models. Therefore, in this paper, we investigate the impact of three data transformation methods (Log, Minmax, and Z‐score) on the performance and interpretability of SDP models. Through empirical research on (i) six classification techniques (random forest, decision tree, logistic regression, Naive Bayes, K‐nearest neighbors, and multilayer perceptron), (ii) six performance evaluation indicators (Accuracy, Precision, Recall, F1, MCC, and AUC), (iii) two interpretable methods (permutation and SHAP), (iv) two feature importance measures (Top‐k feature rank overlap and difference), and (v) three datasets (Promise, Relink, and AEEEM), our results show that the data transformation methods can significantly improve the performance of the SDP models and greatly affect the variation of the most important features. Specifically, the impact of data transformation methods on the performance and interpretability of SDP models depends on the classification techniques and evaluation indicators. We observe that log transformation improves NB model performance by 7%–61% on the other five indicators with a 5% drop in Precision. Minmax and Z‐score transformation improves NB model performance by 2%–9% across all indicators. However, all three transformation methods lead to substantial changes in the Top‐5 important feature ranks, with differences exceeding 2 in 40%–80% of cases (detailed results available in the main content). Based on our findings, we recommend that (1) considering the impact of data transformation methods on model performance and interpretability when designing SDP approaches as transformations can improve model accuracy, and potentially obscure important features, which lead to challenges in interpretation, (2) conducting comparative experiments with and without the transformations to validate the effectiveness of proposed methods which are designed to improve the prediction performance, and (3) tracking changes in the most important features before and after applying data transformation methods to ensure precise and traceable interpretability conclusions to gain insights. Our study reminds researchers and practitioners of the need for comprehensive considerations even when using other similar simple data processing methods.
Low‐Complexity BFGS‐Based Soft‐Output MMSE Detector for Massive MIMO Uplink
Authors: Li Lin , Hu Jianhao
Published: November 2023

For the massive multiple‐input multiple‐output (MIMO) uplink, the linear minimum mean square error (MMSE) detector is near‐optimal but involves undesirable matrix inversion. In this paper, we propose a low‐complexity soft‐output detector based on the simplified Broyden–Fletcher–Goldfarb–Shanno method to realize the matrix‐inversion‐free MMSE detection iteratively. To accelerate convergence with minimal computational overhead, an appropriate initial solution is presented leveraging the channel‐hardening property of massive MIMO. Moreover, we employ a low‐complexity approximated approach to calculating the log‐likelihood ratios with negligible performance losses. Simulation results finally verify that the proposed detector can achieve the near‐MMSE performance with a few iterations and outperforms the recently reported linear detectors in terms of lower complexity and faster convergence for the realistic massive MIMO systems.
Energy efficiency optimisation in massive multiple‐input, multiple‐output network for 5G applications using new quantum genetic algorithm
Authors: Sabaawi Abdulbasit M. A. , Almasaoodi Mohammed R. , El Gaily Sara , Imre Sándor
Published: November 2023

Devising efficient optimisation methods has been a subject of great research attention since current evolving trends in communication networks, machine learning, and other cutting‐edge systems that need a fast and accurate optimised computational model. Classical computers became incapable of handling new optimisation problems posed by newly emerging trends. Quantum optimisation algorithms appear as alternative solutions. The existing bottleneck that restricts the use of the newly developed quantum strategies is the limited qubit size of the available quantum computers (the size of the most recent universal quantum computer is 433 qubits). A new quantum genetic algorithm (QGA) is proposed that handles the presented problem. A quantum extreme value searching algorithm and quantum blind computing framework are utilised to extend the search capabilities of the GA. The quantum genetic strategy is exploited to maximise energy efficiency at full spectral efficiency of massive multiple‐input, multiple‐output (M‐MIMO) technology as a toy example for pointing out the efficiency of the presented quantum strategy. The authors run extensive simulations and prove how the presented quantum method outperforms the existing classical genetic algorithm.
Asteroseismic modelling strategies in the PLATO era
Authors: Bétrisey J. , Buldgen G. , Reese D. R. , Meynet G.
Published: November 2023

Context. In the framework of the PLATO mission, to be launched in late 2026, seismic inversion techniques will play a key role in determining the mission precision requirements in terms of stellar mass, radius, and age. It is therefore relevant to discuss the challenges of the automation of seismic inversions, which were originally developed for individual modelling.

Aims. We tested the performance of our newly developed quality assessment procedure of seismic inversions, which was designed for pipeline implementation.

Methods. We applied our assessment procedure to a testing set composed of 26 reference models. We divided our testing set into two categories: calibrator targets whose inversion behaviour is well known from the literature and targets for which we assessed the quality of the inversion manually. We then compared the results of our assessment procedure with our expectations as a human modeller for three types of inversions: the mean density inversion, the acoustic radius inversion, and the central entropy inversion.

Results. We find that our quality assessment procedure performs as well as a human modeller. The mean density inversion and the acoustic radius inversion are suited to large-scale applications, but not the central entropy inversion, at least in its current form.

Conclusions. Our assessment procedure shows promising results for a pipeline implementation. It is based on the by-products of the inversion and therefore requires few numerical resources to quickly assess the quality of an inversion result.
Urban Farming in Pandemic Covid-19 and How the Economic Impact Analysis for Communities Kauman Village, Malang City
Authors: Istiqomah Ni`matul , Wahjoedi  , Asnan Qodri Lutfi , bint Mohd Radzi Norfaridza
Published: November 2023

Urban farming is a sustainable and adaptable farming alternative. Especially during the COVID-19 pandemic, urban farming is an efficient alternative since it does not require high mobility. This study examined the efficacy of implementing urban farming with the Community’s Economic Impact Analysis (EIA). This type of research is qualitative research with deep interview techniques by the 7 participants. The participants are the people of Kauman Village, Malang City, East Java, Indonesia. The results showed that the impact of urban farming in Kauman significantly increased the community’s Economic Impact Analysis (EIA). The public’s perception of the application of urban farming is quite good. Most people perceive the benefits of implementing urban farming, including using green land around their houses. According to Economic Impact Analysis, implementing urban farming can increase well-being in terms of food security. Community participation in implementing urban farming looks quite effective and enthusiastic so that people, individually and in groups, perceive the benefits of implementing this farming system.