bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reconfigurable Binary and Ternary Logic Devices Enabling Logic State Modulation
Authors: Cho Jeong Ho , Kwon Yonghyun , Park Su Bin , Yoo Youngjae , Lee Seung Woo 
Published: November 2024

Abstract

This paper reports a reconfigurable binary–ternary transistor with a controllable voltage range and current level for the intermediate logic state. The proposed functions were demonstrated using an indium–gallium–zinc-oxide channel with a dual-gate structure incorporating two types of dielectrics (with high and low capacitances). This asymmetric dual-gate structure exhibits two key characteristics. First, the threshold voltage can be adjusted by applying a voltage to the control gate opposing the input. Second, partial depletion occurs when the input gate’s capacitance is insufficient, making the off current dependent on the control gate voltage. Two dual-gated channels were connected in series, with inputs applied to the low-capacitance gate of one channel and the high-capacitance gate of the other and the remaining gates served as control gates. This device configuration outputs three current regions: fully depleted (low), partially depleted (intermediate), and accumulated (high) channel currents, which were utilized as logic states for the ternary device. Moreover, the threshold voltage for each channel and the current from the partially depleted channel could be precisely controlled by biasing each control gate. This enables an adjustable voltage range and current level for the intermediate logic state, as well as reconfigurability between binary and ternary operations.
Introducing Metal-Sulfur Active Sites in Metal-Organic Frameworks via Post-Synthetic Modification for Hydrogenation Catalysis
Authors: Farha Omar , Xie Haomiao , Khoshooei Milad , Mandal Mukunda , Vornholt Simon , Hofmann Jan , Tufaro Luke , Kirlikovali Kent , Grimes Dawson , Lee Seryeong , Su Shengyi , Reischauer Susanne , Sengupta Debabrata , Fahy Kira , Ma KaiKai , Wang Xiaoliang , Sha Fanrui , Gong Wei , Chen Yongwei , Vitillo Jenny , Anderson John , Notestein Justin , Chapman Karena , Gagliardi Laura 
Published: November 2024

Abstract

Metal sulfide binary compounds, renowned for their exceptional electronic properties, are advantageous in applications such as hydrogenation, dehydrogenation, and photocatalysis. Typically, the majority of active sites in these compounds reside on the surfaces and edges of catalyst particles, leaving the bulk catalyst underutilized. This study introduces a strategy to embed metal-sulfur active sites into metal-organic frameworks (MOFs) via post-synthetic modification, exploiting the MOFs’ accessible internal surfaces. Two MOF systems, including M2Cl2(BBTA) (H2BBTA = 1H,5H-benzo(1,2-d:4,5-d')bistriazole, M = Co, Ni), which features one-dimensional M–Cl chains and hexagonal channels, and M-MFU-4l-Cl (M = Co, Ni), which contains discrete ZnM4 metal nodes, were selected as starting materials. The conversion processes, from M2Cl2(BBTA) to M2(SH)2(BBTA) and from M-MFU-4l-Cl to M-MFU-4l-SH, were executed through a two-step post-synthetic modification protocol and confirmed by single-crystal XRD, PXRD, PDF, SEM, XPS, and N2 sorption techniques. Catalytic performance was assessed using the reduction of 4-nitrophenol to 4-aminophenol with molecular hydrogen as a model reaction, and significant improvement in performance was observed upon introduction of the SH groups. Density functional theory calculations suggest that the flexibility of the sulfur moiety is crucial in the M–X bond cleavage pathway, enhancing hydrogen activation. This study underscores the efficacy of post-synthetic modification in developing advanced MOF-based catalysts with superior performance for selective hydrogenation reactions, highlighting the strategic advantage of incorporating polarizable sulfur components within MOFs.
Allosteric activation of a cell-type specific GPR120 rescues cognition and extends lifespan of Alzheimer’s disease
Authors: Lu Youming , He Aodi , Wang Yue , Shen Yuhang , Dong Zhiqiang , Luo Lingli , Ge Xiangyu , Liu Xinlu , Mao Yue , Zhang Tongmei , Li Xinyan , Li Hao , Jing Wei , Zhu Ling-Qiang , Zhang Qifa 
Published: November 2024

Abstract

Black rice diets are enriched with unsaturated fatty acids that are thought to be beneficial for neurodegenerative disorders in ageing. Here, we find that black rice enriched alpha-linolenic acid (ALA) and 11,14-eicosadienoic acid (EDA) inhibit amyloid pathology, rescue cognition and extends lifespan in mouse preclinical models of Alzheimer’s disease via allosteric activation of GPR120 in brain resident macrophages and activated microglia. We generate the structures of GPR120 bound to ALA and EDA. We demonstrate that ALA and EDA allosterically modulate and synergistically activate GPR120 for macrophagic phagocytosis and clearance of β-amyloid aggregates in Alzheimer’s disease mice. A cell-type specific deletion of GPR120, or Gαi1 completely abrogates the therapeutic effects of ALA and EDA. This deletion can be rescued by a constitutive active Gαi1Q204L. These findings show a cell-type specific function of GPR120 in the brain and provide an enriched allosteric mechanism of GPR120 activation for the treatment of Alzheimer’s disease.
Ecological niche imprints the structure and network of microbial communities in Lonicera japonica Thunb
Authors: Zhang Zhaoyu , Dong Yingda , Chen Xiao , Zhang Guozhuang , Liang Conglian , Zhou Yuxin , Huang Ziying , Shi Liping , Chen Shilin , Dong Linlin , Wei Guangfei 
Published: November 2024

Abstract

Background and aims
Plant-associated microbiomes play pivotal roles in promoting plant health, productivity, and resistance to diseases. However, the differential adaptability of microorganisms to different microenvironments in Lonicera japonica remains unclear, which hinders their application in agriculture.
Methods
Here, the structure and network of bacterial and fungal communities in six compartment niches (bulk soil, rhizosphere soil, root, stem, leaf, and flower) of L. japonica were explored using three host ecotypes.
Results
Results demonstrated that the structure and assembly of microbiomes along the soil–plant continuum were primarily governed by compartment niches rather than host ecotypes. Bacterial diversity and network complexity incrementally decreased from the soil to the root and flower; however, fungal diversity and network complexity gradually decreased from the soil to the stem but increased from the stem to the leaf and flower. The bacterial keystone taxa Proteobacteria, Pseudomonas, Pantoea, Kluyvera, and Enterobacter were dominated in endosphere samples. Meanwhile, the core fungal keystone taxa Cryptococcus, Alternaria, and Erysiphe were dominated by endosphere samples. However, Mortierella and Fusarium were dominated by rhizosphere soil.
Conclusion
Microbiota was mainly derived from bulk soil and then filtered in each compartment niches. This finding provides empirical evidence for host selection and soil–plant–microbiome interaction along the soil–plant continuum.
Perinatal psychiatric symptoms and the continuum of breastfeeding in a University Hospital population of minoritized women
Authors: Jain Swati , Abijo Tomilowo , Powell Edwin W. , Dlamini Sindile , Kellogg Ethan , Reeves Inez 
Published: November 2024

Abstract

Background and Objectives: Reduced rates for breastfeeding remain an important health disparity in minoritized communities. This study examines the influence of perinatal psychiatric symptoms in an urban population of minoritized women on plans, initiation, and continuation of breastfeeding.
Methods: Minoritized pregnant women ≥ 18 years old completed the “My Mood Monitor (M-3)” psychiatric screening tool and breastfeeding questionnaires in three phases: (I) the second trimester of pregnancy (plans to breastfeed), (II) post-delivery (initiation of breastfeeding) and (III) post-partum (continuationof breastfeeding). Data was analyzed to establish the relationship of breastfeeding to any positive M-3 screen) with maternal demographics and at these three corresponding time points.
Results: The only maternal demographic that showed a significant association (*p0.02) with any positive M3 was early entry into prenatal care (≤12 weeks). Although 86.3% of the cohort intended to breastfeed in phase I, 76.1 % initiatedbreastfeeding at phase II and only 43.4 % of the retained cohort continuedbreastfeeding in phase III. In phase I, there was no statistical difference between mothers who screened negative versus those with ANY POSITIVE M-3 screenings (p = 0.684). At phase II, there was an apparent association (p = 0.065) between mothers with ANY POSITIVE M-3 screening. Positive screening for psychiatric symptoms was associated with lower rates of breastfeeding continuation (p = 0.014) in phase III. Anxiety was significantly associated with discontinuation of breastfeeding (p = 0.019).
Conclusion: Further research is needed for screening and early diagnoses of perinatal anxiety, especially following delivery in urban minoritized women.
Synthesis, Characterization, and Adsorption Performance of Magnetic Hydrogels from Apocynum Leaf Cellulose and Chitosan
Authors: JIA Shunpeng , XU HaiYang , Gong wenze , RunPing Yu , Bian yang , JIA lingyun , YANG qinqin , Pan YingNi , JIA Benzhi 
Published: November 2024

Abstract

This study explores the synthesis and characterization of novel hydrogels derived from cellulose extracted from Apocynum venetum leaves, combined with chitosan, and further modified into magnetic hydrogels with varying magnetic strengths. The hydrogels—cellulose-based (CH), chitosan-based (QH), and magnetic variants (MC, MQ)—were characterized using SEM, FTIR, XRD, and VSM techniques. Adsorption tests were conducted to evaluate their efficiency in removing contaminants, specifically CR dye and Cu ions. Results indicated that CH hydrogels exhibited a remarkable CR adsorption capacity due to their porous structure, while QH hydrogels demonstrated superior Cu removal, attributed to strong chelation with amine groups. Magnetic hydrogels, particularly MQ, showed enhanced adsorption capabilities, benefiting from increased surface roughness and additional active sites. These findings suggest that the synthesized hydrogels, especially the magnetic variants, offer significant advantages over traditional adsorbents, highlighting their potential for practical applications in wastewater treatment. This research contributes to the development of efficient, sustainable solutions for environmental remediation.
Low-Rank Optimization for Efficient Compression of CNN Models
Authors: Liu Hao , Jiang Zheng , Liu Bin , Li Liang , Zhang Xiaokang 
Published: November 2024

Abstract

Tensor decomposition is an important method for compressing convolutional neural network (CNN) models. However, in the decomposition process, it is necessary to configure appropriate rank parameters for each convolutional kernel tensor. To address the difficulty in setting ranks, we propose a low-rank optimization algorithm based on information entropy. By solving the optimization problems, this algorithm can automatically learn the low-rank structure and rank parameters of convolutional kernel tensors, achieving global automatic configuration while ensuring model accuracy. Moreover, we design a weight generator for the network after tensor decomposition, which dynamically assesses the importance of filters of low-dimensional convolutional kernel tensors on a global scale. Indeed, pruning in the low-dimensional space can further enhance compression effects with minimal loss in accuracy. By testing various CNN models on different datasets, the results show that the proposed low-rank optimization algorithm can obtain all rank parameters in a single training process, and the average accuracy loss of the decomposed model does not exceed 1%. Meanwhile, the pruning method in low-dimensional space can achieve a compression ratio of over 4.7× with an accuracy loss of less than 1.3%.
Tailoring mesoporous ferrocene-modified activated carbon derived for phenol removal in wastewater
Authors: Mqehe-Nedzivhe Khathutshelo C. , Ojo Babatope Oluwole , Mabuba Nonhlangabezo 
Published: November 2024

Abstract

This present study investigates the adsorption capacity of synthesized activated carbon/ferrocene composite (AC-H3PO4/Fe7S8) for phenol removal in wastewater. The structural, porosity, and morphology of the synthesized activated carbon/ferrocene composite were determined using FTIR, BET, XRD, and SEM. Parameters varied at different concentrations during the adsorption process include adsorbent dosage, contact time and pH. The AC-H3PO4/Fe7S8 composite achieved 98% removal efficiency of phenol at optimal operational conditions of adsorbent dosage of 0.3g, contact time of 120 min, pH of 4, and concentration of (10-50 mg/L). Batch adsorptions were conducted to study the adsorption isotherm and kinetics. The Freundlich isotherm offered the most suitable representation of the adsorption data, with R² values of 0.99650 and 0.9955 for AC-H3PO4 and AC-H3PO4/Fe7S8 respectively. Furthermore, the adsorption kinetics conformed to a pseudo-second-order model for both adsorbents. The findings suggest that the synthesized AC-H3PO4/Fe7S8 composite represents a promising adsorbent for phenol removal in wastewater treatment.
Single- and multi-locus genome-wide association study reveals genomic regions of thirteen yield-related traits in common wheat
Authors: Lv Yuxia , Dong Liansheng , Wang Xiatong , Shen Linhong , Lu Wenbo , Si Fan , Zhao Yaoyao , Zhu Guanju , Ding Yiting , CAO Shujun , Cao Jiajia , Lu Jie , Ma Chuanxi , Chang Cheng , Zhang Haiping 
Published: November 2024

Abstract

Genetic dissection of yield-related traits can be used to improve wheat yield through molecular design breeding. In this study, we genotyped 245 wheat varieties and measured 13 yield-related plant height-, grain- and spike-related traits, in seven environments, and identified 778 loci for these traits by genome-wide association study (GWAS) using single- and multi-locus models. Among them, nine were major loci, of which seven were novel, including Qph/lph.ahau-7A for plant height (PH) and leaf pillow height (LPH), Qngps/sps.ahau-1A for number of grains per spike (NGPS) and spikelet number per spike (SPS), Qsd.ahau-2B.1 and Qsd.ahau-5A.2 for spikelet density (SD), Qlph.ahau-7B.2 for LPH, Qgl.ahau-7B.3 for grain length (GL), and Qsl.ahau-3A.3 for spike length (SL). Through marker development, re-GWAS, gene annotation and cloning, and sequence variation, haplotype, and expression analyses, we confirmed two novel major loci and identified potential candidate genes, TraesCS7A02G118000 (named TaF-box-7A) and TraesCS1A02G190200 (named TaBSK2-1A) underlying Qph/lph.ahau-7A for PH-related traits and Qngps/sps.ahau-1A for spike-related traits, respectively. Furthermore, we reported two favorable haplotypes, including TaF-box-Hap1 associated with low PH and LPH and TaBSK2-Hap3 associated with high NGPS and SPS. In summary, these findings are valuable for improving wheat yield and enriching our understanding of the complex genetic mechanisms of yield-related traits.
Performance of a Multibody Point Absorber With a Damper Plate in Irregular Waves
Authors: Kumar Suman , Vijayasankar Vishnu , Samad Abdus 
Published: November 2024

Abstract

Wave energy converters (WECs) behave differently when operating in irregular waves than regular ones. Although numerous studies describe WEC dynamics in regular waves, the ocean experiences irregular waves, making it essential to evaluate performance under such conditions. A multibody WEC has mixed motion, adding complexity to the system dynamics. In this study, a multibody floating-point absorber WEC equipped with a damper plate was designed and tested for irregular wave conditions in the wave basin at IIT Madras. The wave conditions varied, with significant wave heights ranging from 0.15 to 0.23 m and peak periods from 1 to 2.5 s. Hydrodynamic coefficients, such as the Response Amplitude Operator (RAO), excitation force, radiation damping, and added mass, were computed using the panel method. Additionally, a multibody dynamics solver was used to calculate power absorption. The point absorber, with a damper plate, achieved a maximum power output of 14.05 W at \(\:{H}_{s}\)= 0.23 m and \(\:{T}_{P}\:\)= 2.5 s. The highest absorption efficiency was 48.2% at \(\:{H}_{s}\)=0.20 m and \(\:{T}_{P}\)=2.5 s.
AMIRLe: attribute-enhanced multi-interaction representation learning fore-commerce heterogeneous information networks
Authors: Ding Lianhong , Li Mengxiao , Wang Yi , Shi Peng , Zhang Fangfeng 
Published: November 2024

Abstract

Heterogeneous graph representation learning has attracted considerable interest for its effectiveness in capturing the structural information of nodes within complex and diverse networks. However, existing heterogeneous graph representation learning models primarily focus on structural embeddings, overlooking the importance of node attributes and temporal information in understanding complex interaction networks, particularly in e-commerce heterogeneous networks. To address this issue, this paper proposes an Attribute-enhanced Multi-Interaction Representation Learning method in e-commerce heterogeneous information networks, namely AMIRLe. Specifically, AMIRLe first processes high-dimensional data and identifies hidden patterns via tensor decomposition techniques to construct multi-interaction heterogeneous networks. Then, a novel time-aware attribute embedding method is proposed, which employs an attention mechanism to enhance key node aggregation after integrating interaction time information as auxiliary attributes with node attributes. Finally, a graph neural network (GNN) method is designed to integrate meta-path-based structure embeddings with attribute embeddings to produce the final embeddings. Link prediction experiments on three real-world e-commerce datasets demonstrate that performance of AMIRLe superior to state-of-the-art methods.
Cluster-Based Cell-Free Massive MIMO Systems: A Novel Framework to Enhance Spectral Efficiency with Low Complexity
Authors: Roshanghias Reza , Saadat Reza 
Published: November 2024

Abstract

The issue of diminished spectral efficiency (SE) of the downlink (DL) transmission in distributed cell-free massive MIMO (CF-mMIMO) systems poses a significant challenge in terms of user equipment (UE) performance when compared to their centralized CF-mMIMO counterparts. The primary root cause of this issue can be attributed to the reduced efficacy of distributed precoders, which are devised using local channel state information (CSI) in distributed systems. This reduced efficacy becomes particularly pronounced in terms of interference mitigation when compared to centralized precoders. To address this issue, this paper proposes a novel architectural framework for CF-mMIMO systems, referred to herein as the "cluster-based structure." Within this innovative structure, a hybrid amalgamation of centralized and distributed configurations is employed, complemented by the introduction of a unique cluster arrangement for the access points (APs) within the network. In this design, the CSI of APs within each cluster is collectively shared within a local processor unit. Consequently, by harnessing this enhanced repository of local channel information, local precoders are formulated, which facilitate more effective interference mitigation with reduced computational complexity compared to the centralized approach. This approach ultimately results in a significantly augmented SE when contrasted with the distributed architecture. In this paper, the DL signal-to-interference-plus-noise ratio (SINR) of the UEs in this new architecture is derived analytically, and two precoders, namely maximum ratio (MR) and minimum mean square error (MMSE), are proposed for the new architecture. Furthermore, an elucidation of the computational complexity associated with the MMSE precoder in the context of the cluster-based framework will be presented, drawing a comparative analysis with both centralized and distributed structural configurations. The simulation results unequivocally demonstrate that within the cluster-based framework, the optimal SE for the network is attained when utilizing four clusters in conjunction with the MMSE precoding technique, leading to a notable reduction in computational complexity exceeding \(85%\). Importantly, this approach surpasses the SE performance of the centralized structure.
Considering landscape heterogeneity improves the inference of inter-individual interactions from movement data
Authors: Fronville Thibault , Blaum Niels , Jeltsch Florian , Kramer-Schadt Stephanie , Radchuk Viktoriia 
Published: November 2024

Abstract

Background: Animal movement is influenced by both the physical environment and social environment. The effects of both environments are not independent from each other and identifying whether the resulting movement trajectories are shaped by interactions between individuals or whether they are the result of their physical environment, is important for understanding animal movement decisions.
Methods: Here, we assessed whether the commonly used methods for inferring interactions between moving individuals could discern the effects of environment and other moving individuals on the movement of the focal individual. We used three statistical methods:Dynamic interaction index, and two methods based on step selection function. We created five scenarios in which the animals' movements were influenced either by their physical environment alone or by inter-individual interactions. The physical environment is constructed such that it leads to a correlation between the movement trajectories of two individuals.
Results: We found that neglecting the effects of physical environmental features when analysing interactions between moving animals leads to biased inference, i.e. inter-individual interactions spuriously inferred as affecting the movement of the focal individual. We suggest that landscape data should always be included when analysing animal interactions from movement data. In the absence of landscape data, the inference of inter-individual interactions is improved by applying 'Spatial +', a recently introduced method that reduces the bias of unmeasured spatial factors.
Conclusions: This study contributes to improved inference of biotic and abiotic effects on individual movement obtained by telemetry data. Step selection functions are flexible tools that offer the possibility to include multiple factors of interest as well as combine it with spatial +.
Multi-source Data Fusion-based Grid-level Load Forecasting
Authors: Ye Hai , Teng Xiaobi , Song Bingbing , Zou Kaiming , Zhu Moyan 
Published: November 2024

Abstract

Grid-level dispatching is generally based on the accumulation of independent load forecasting data from provincial and municipal dispatch centers. However, the differences in economic development levels and the frequency of forecasting result updates among provinces and cities lead to certain limitations in the direct accumulation method, affecting the accuracy of the integrated forecasting results. To address this, this paper proposes a short-term load forecasting method for the power grid based on the i-Transformer model. First, the dataset is constructed through data preprocessing and feature engineering, followed by training and optimizing the model parameters. Further, considering the differences in forecasting results reported by provincial dispatch centers, principal component analysis is used to determine the weights of provinces and cities, thereby effectively integrating the forecasting data from different provinces and cities through weighting. The case study shows that the i-Transformer outperforms traditional statistical and machine learning algorithms on multiple evaluation metrics, and the integration method has considerable potential in handling multi-source heterogeneous data and improving forecasting accuracy. This paper provides a new means of load forecasting result integration for power grid dispatch centers, ensuring the safe, high-quality, and economical operation of the power system.