bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategic Decision-Making in Higher Education Learning Management System Adoption using hybrid intuitionistic fuzzy Method
Authors: Meng Jiao , Zheng Xiaohan , Zhang Zeheng , Zhang Longji
Published: November 2024

In the context of higher education institutions, the adoption of learning management systems (LMS) represents a critical strategic decision, influenced by complex factors and evolving pedagogical practices. As the digitalization of education accelerates, administrators face the challenge of selecting the most suitable LMS solution amidst a plethora of options. This paper proposes a novel approach to address this challenge, leveraging the intuitionistic fuzzy (IF) criteria importance through intercriteria correlation (CRITIC)This work suggests a novel ranking order strategy that combines the IF criteria importance through intercriteria correlation (CRITIC) -alternative ranking order method accounting for two-step normalization (AROMAN) Method. This technique aims to overcome this hurdle. Method. Drawing upon insights from multi-criteria decision-making (MCDM), this methodology offers a systematic framework for evaluating LMS alternatives while accounting for the inherent uncertainties and subjectivities in the decision-making process.The AROMAN technique—which conducts two-step normalization in an IFenvironment is coupled with the CRITIC paradigm, which examines intercriteria correlations, to improve complicated and uncertain decision-making. The advantages of the suggested approach are shown via an LMS case study. This case study shows how the suggested approach advances open decision-making, consistency, and strategic alignment. The study offers a strong basis for decision-making addressing problems with the use of LMS in higher education. This gift facilitates the digitization of learning surroundings.
Bearing Capacity and Safety Zoning Method for Near Slope Strip Footings Considering Slope Stability
Authors: Yuan Hao , Xiao Qinghua , Qiu Zemin , Han Xiangyu , Li Congming , Xiao Yihuan , Dang Longxin , Liu Jinqiao
Published: November 2024

Ensuring the safety of foundation bearings in slope engineering poses a significant challenge. This study uses numerical simulations and slip line field theory to construct a mathematical model for strip footing near a slope. It employs the limit equilibrium block analysis to propose an estimation formula for the ultimate bearing capacity and a safety zoning method for strip footing near a slope, considering multiple factors such as slope shape, foundation, and load. The results indicated that (1) when the slope fails due to the foundation load, it exhibits a failure mode of initial constant velocity shear followed by a dominant slip to the free side. (2) This research proposes a multi-factor evaluation formula for the ultimate bearing capacity of strip footing near a slope, which can be calculated directly and is convenient for engineering applications. (3) As slope characteristic parameters remain constant, the ultimate bearing capacity decreases with an increase in slope angle and foundation width, and it increases with an increase in distance from footing to the top of the slope, cohesion, and internal friction angle. In addition, the spatial safety zoning evaluation method of strip footing near a slope is established, providing a reference and theoretical basis for engineering practice.
Comprehensive development and screening of novel black pepper hybrids (Piper nigrum L.) for enhanced resistance to Phytophthora capsici
Authors: Arif Tamanna , Narayanpur Vijaykumar B , kulkarni Sudheesh , V Devappa. , Shet Ratnakar , C Vishwanath Y , P Pushpa
Published: November 2024

Black pepper (*Piper nigrum* L.), often referred to as the "King of Spices" and "Black Gold," holds a unique and dominant position as the most important and widely used spice globally. It has been a highly valued agricultural commodity for centuries. Despite its immense commercial significance, black pepper faces considerable challenges, particularly from the destructive Phytophthora foot rot disease, which poses a serious threat to its cultivation. Addressing this challenge through the development of genetic variability via hybridization is crucial. This study investigates the impact of various parental combinations on black pepper seeds to generate novel hybrids. Inter-varietal hybridization was executed with multiple cross combinations, including Panniyur-1 x BPL Gold, Panniyur-1 x Salkani (RMH), Panniyur-1 x SV 7, Panniyur-1 x SV 11, Panniyur-1 x SV 17, and Panniyur-1 x V1. Among these combinations, the Panniyur-1 x Salkani (RMH) hybrid exhibited the highest percentage of spike setting, germination rate, seedling height, number of leaves, internodal length and number of branches. Detailed analysis of leaf characteristics such as base shape, lamina shape, veination and leaf margin revealed noticeable variations between the hybrids and their parent plants. The newly developed hybrids underwent rigorous screening for resistance to Phytophthora foot rot through artificial inoculation with Phytophthora capsici. Notably, the Panniyur-1 x Salkani (RMH) hybrid demonstrated exceptional tolerance, showing minimal lesion development. This study not only expands the genetic diversity of black pepper but also establishes a foundation for cultivating robust hybrids with enhanced resistance to Phytophthora foot rot. Such advancements are pivotal for ensuring a resilient and profitable agricultural future.
Development and Validation of a Sustainable Densitometric RP-HPTLC Method for Analyzing Irbesartan and Amlodipine Besylate in Pharmaceutical Products Using Eco- Friendly Solvents
Authors: Chaure Vinod A. , Shirkhedkar Atul A
Published: November 2024

A review of the literature found that there is no suitable "reversed phase-high performance thin layer chromatography (RP-HPTLC)" method for examining amlodipine besylate (AMD) and irbesartan (IRB) in tablet formulations. For the quantification of commercial tablets manufactured by AMD and IRB, a new RP-HPTLC method that is quick, simple to use, economical, and eco-friendly has been created. RP-HPTLC analysis was performed on IRB and AMD using "RP-18 silica gel 60 F254S HPTLC plates." A binary mixture of green solvents, consisting of methanol and water (60: 40:1.0, v/v), used as the mobile phase. This chromatographic technique yielded compact bands with good resolution, with retardation factors (Rf) of 0.22 ± 0.002 for AMD and 0.53 ± 0.001 for IRB. AMD and IRB measurements were made at 236 nm. For IRB in the 500–3000 ng per band range (R2 = 0.9992) and for AMD in the 25-1500 ng per band range (R2 = 0.999), it was shown that the recommended RP-HPTLC method was linear. The "precision, accuracy, robustness, and sensitivity" of the proposed RP-HPTLC approach were all validated. For AMD, the accuracy varied from 99.33 to 100.20%, while for IRB, it ranged from 99.41 to 100.61%. For moderate accuracy and repeatability, the % RSD was found to be less than 2. IRB had quantification limits of 31.63 ng per band and AMD had detection limits of 10.44 ng per band and AMD had detection limits of 3.35 ng per band. The percentages of IRB and AMD in commercially available tablets were determined to be 99.78 to 101.96 for IRB and 98.25 to 100.42% for AMD, respectively. The proposed RP-HPTLC method may be successfully applied to the pharmaceutical assay of IRB and AMD, which are sold as tablets, using green solvents.
OsPIP2;4 aquaporin mediates non-selective Na+ and K+ conductance, potentially contributing to the absorption and distribution of cations in rice
Authors: Tran Sen Thi Huong , Katsuhara Maki , Mito Yunosuke , Onishi Aya , Higa Ayaka , Ono Shuntaro , Paul Newton Chandra , Horie Rie , Harada Yoshihiko , Horie Tomoaki
Published: November 2024

Aquaporin (AQP)-dependent water transport across membranes is indispensable in plants. Recent evidence shows that several AQPs, including plasma membrane intrinsic proteins (PIPs), facilitate the electrogenic transport of ions as well as water transport and are referred to as ion-conducting aquaporins (icAQPs). The present study attempted to identify icAQPs that exhibit cation transport activity among PIPs from rice. Electrophysiological experiments on 11 OsPIPs using Xenopus laevis oocytes revealed that OsPIP2;4 mediated the electrogenic transport of alkali monovalent cations with the selectivity sequence of Na+ ≈ K+ > Rb+ > Cs+ > Li+, suggesting non-selective cation conductance for Na+ and K+. Transcripts of OsPIP2;4 were abundant in the elongation and mature zones of roots with similar expression levels between the root stelar and remaining outer parts in the cultivar Nipponbare. Immunostaining using sections of the crown roots of Nipponbare plants revealed the expression of OsPIP2;4 in the exodermis and sclerenchyma of the surface region and in the endodermis and pericycle of the stelar region. The present results provide novel insights into OsPIP2;4-dependent non-selective Na+ and K+ transport and its physiological roles in rice.
PAM-flexible adenine base editing rescues hearing loss in a humanized MPZL2 mouse model harboring an East Asian founder mutation
Authors: Shu Yilai , Hu Shao Wei , Jeong Sohyang , Jiang Luoying , Koo Hansol , Wang Zijing , Choi Won Hoon , Zhu Biyun , Seok Heeyoung , Zhou Yi , Kim Min Gu , Mu Dan , Guo Huixia , Zhou Ziyi , Jung Sung Ho , Zhang Yingting , Chae Ho Byung , Chen Liheng , Lee Sung-Yeon , Guo Luo , Suh Myung-Whan , Xiao Yang , Park Moo Kyun , Tang Honghai , Song Jae-Jin , Chen Xi , Chen Ai , Lee Jun Ho , Bae Sangsu , Lee Sang-Yeon
Published: November 2024

Hearing loss is one of the most prevalent sensory disorders, but no commercial biological treatments are currently available. Here, we identified an East Asia-specific founder mutation, the homozygous c.220C>T mutation in MPZL2, that contributes to a significant proportion of hereditary deafness cases in our cohort study. We found that the disease-causing mutation could be targetable by adenine base editors (ABEs) that enable A·T-to-G·C base corrections without DNA double-strand breaks. To demonstrate this, we developed a humanized mouse model (hMPZL2Q74X/Q74X) that recapitulates human MPZL2 deafness and leads to progressive hearing loss. A PAM-flexible ABE variant with reduced bystander and off-target effects (ABE8eWQ-SpRY:sgRNA3) was packaged in dual adeno-associated viruses (AAVs) and injected into the inner ear of hMPZL2Q74X/Q74X mice and effectively corrected the mutation. This treatment significantly restored hearing function, improved inner ear structural integrity, and reversed altered gene expression. Base editing may hold therapeutic potential for hereditary deafness, including most cases of MPZL2 deafness.
Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health
Authors: Temesgen Lema , Tufa Takele Beyene , Abunna Fufa
Published: November 2024

Background
Salmonella is a significant foodborne pathogen, with milk and milk products commonly implicated in its transmission. However, limited information is available regarding the direct link between antimicrobial use (AMU), dairy hygiene practices, and antimicrobial resistance (AMR) in Salmonella strains isolated from dairy products in Bishoftu town.
Methods
Cross-sectional research was done from October 2023 to April 2024 to assess dairy farmers' antimicrobial usage (AMU) and hygiene practices and the occurrence of antimicrobial resistance (AMR) profiles of Salmonella isolated from raw cow milk and its products. Two hundred samples were collected from dairy farms, milk vendors, and restaurants and analyzed using standard microbiological methods. Using the OmniLog system, Salmonella enterica was successfully identified. Then, the antimicrobial susceptibility was evaluated using the Kirby-Bauer disc diffusion technique. Data were analyzed using STATA version 14.2.
Results
Overall, 2% (n = 4) of the samples tested positive for S. enterica. Of the 4 isolates, 3 were identified in dairy farm samples, whereas 1 were isolated from milk vendors. However, no Salmonella was identified in cheese or yogurt samples obtained from the restaurants. Regarding the AMR profile, S. enterica isolates were resistant to amoxicillin (75%), streptomycin (75%), and tetracycline (50%). Resistant to two or more antimicrobials were identified in 75% of the isolates.
Conclusion
This study indicated contamination of cow milk and its products with S. enterica. Therefore, appropriate control measures, including awareness creation among personnel and improving hygienic practices at the milk value chains is recommended to mitigate cross-contamination.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Divestment From Fossil Fuels: Evidence From Ownership Data
Authors: Naef Alain , Trouvé Benjamin
Published: November 2024

Fossil divestment, or the sale of fossil fuel financial assets, aims to redirect capital towards sustainable energy sources. Historical precedents, such as divestment during South African Apartheid, successfully pressured governments to drive change. But is there any substantial evidence of fossil fuel divestment today? Here we show that large-scale divestment remains limited, with only certain religious organizations, universities, and public institutions actively reducing fossil fuel holdings. Using a new database of 30 million investor positions across 312 major fossil fuel companies, we reveal distinct short- and long-term divestment drivers: while short-term divestment is primarily triggered by declining oil prices, long-term divestment is influenced by anticipated environmental and climate policy risks. Yet, only a minority of investors consider these long-term risks in their fossil fuel investment strategies, indicating a hesitant shift towards divestment as a response to climate concerns.
Radio Frequency Interference Detection by Classification Models based on Signal Fingerprints of Earth Stations
Authors: Azevedo Josinaldo , Vidal Paulo , Goldschmidt Ronaldo , Salles Ronaldo
Published: November 2024

Satellite networks are essential around the world and, sometimes, are the only means of connection in regions that are difficult to access. Such networks use wireless communication and are affected by interfering signals, which makes it important to identify the origin of these signals. The main technique for identifying the origin of interfering signals is geolocation. However, geolocation may return an area that is in fact occupied by several ground stations, making it difficult to identify the real source of interference. This work proposes a method that can reduce the number of stations listed by the geolocation technique, by applying classification models to radio frequency fingerprint characteristics extracted from the signals. The proposed method achieved an accuracy greater than 98\% in experiments with real data involving 64,800 signal instances and 6 ground stations.
Techno-Economical Assessment of Kappaphycus alvarezii Carrageenan Extraction Plant
Authors: Subakti Felix , Noguchi Ryozo , Diharmi Andarini , Miyasaka Juro , Ohdoi Katsuaki , Ito Ayana
Published: November 2024

Kappaphycus alvarezii carrageenan extraction was optimized using a software-based process simulation. The study focused on the Indonesian seaweed industry, utilizing the advanced modeling capabilities of “SuperPro™”. The simulation involved comprehensive analysis of the extraction process, from dried seaweed transport to final carrageenan production. Furthermore, an economic sensitivity analysis was conducted, incorporating the seaweed production cost as a critical parameter. This analysis provides valuable insights into the financial viability of Kappaphycus alvarezii carrageenan extraction by considering the variations in the input costs, market prices, and other economic factors. The data show that a factory producing Kappaphycus alvarezii carrageenan is both technically and economically feasible within a 10-year lifespan. The plant processes 11.5 MT of raw Kappaphycus seaweed per batch, amounting to an annual input of 44.045 MT raw materials, and an annual output of 3.14 MTs of carrageenan, totaling the processing of 13,074 MTs of Kappaphycus alvarezii carrageenan annually with a payback period of around 8 year and a return on investment of 11.33%. The results provide information for stakeholders, including seaweed farmers, processors, and policymakers, about the potential financial benefits and challenges associated with scaling-up Kappaphycus alvarezii carrageenan extraction in Indonesia.
The coupled PLUS-InVEST-XGBoost model explores the response of climate to ecosystem services in SSP scenarios
Authors: Zhai Duanqiang , Zhuo Jian , Wang Rongyao
Published: November 2024

Climate change stands as one of the most significant challenges globally, affecting regional ecosystems with broad and unpredictable consequences. Incorporating climate change into ecosystem monitoring is essential for sustainability. However, the relationship between climate variables and ecosystem services remains underexplored, and the specific impacts of these variables are not well understood. This study introduces a comprehensive framework to investigate the effects of climate variables on regional ecology. Using CMIP6 climate data, alongside the PLUS and InVEST models, this research predicts the spatial distribution of ecosystem services (ESs). Additionally, Spearman correlation analysis assess the trade-offs and synergies among four ecological indicators, and the eXtreme Gradient Boosting (XGBoost) model is utilized to analyze the response of these indicators to climate variables. The results showed that the ecological land type was protected and restored under the SSP126 scenario. The SSP245 scenario recommends moderate land development; The SSP585 scenario is characterized by rapid economic growth and urban expansion eroding ecological land. In the future, ESs index changes dramatically, SSP126 shows an increase, and the other two scenarios are reduced. The four ecosystem service functions show synergistic effect. Among the climate variables, there are significant changes from year to year. SSP126 scenario is considered to be the best path for regional ESs under climate change. We suggest that managers continue to control regional carbon emissions. Precipitation is always a positive factor to promote the development of regional ecosystem, and future development can reduce the uncertainty of future development by taking advantage of climate.
A Pontomesencephalic-Mesolimbic Circuit Underlying Activity-Based Anorexia
Authors: Liu Shuai , Peng Beibei , Chen Yan , Gao Xu , Xin Yushi , Zhang Yuxiao , Lu Mingli , Li Wenyan , Yang Deqi , Bao Chaofei
Published: November 2024

Anorexia nervosa (AN) is a psychiatric disorder with a high mortality rate. The compulsivity of the disorder leads to an emerging dopamine (DA)-centered hypothesis. However, the key underlying mechanism of AN remains elusive. In the present study, we identified a critical circuit from the lateral parabrachial nucleus (LPBN) to the ventral tegmental area (VTA), in a well-established animal model of AN (activity-based anorexia, ABA). Using in vivo and in vitro electrophysiology, optogenetics, chemogenetics, and fiber photometry, we found that the LPBN-VTA circuit bidirectionally modulated the food intake and reinforcement behaviors. Furthermore, the excitability of VTA-projecting LPBN neurons was increased in ABA mice, and inhibition of this circuit significantly increased food intake and survival rate in ABA mice. The LPBN glutamatergic neurons targeted medial VTA DA neurons indirectly via inhibitory GABA interneurons, underlying the hypoactivity of the VTA DA neurons in ABA mice. This hypoactivity was also due to decreased function of the high-conductance calcium- and voltage-dependent potassium (BK) channels on the DA neurons. Notably, intra-VTA infusion of a BK channel agonist rescued DA neuronal firing and survival rate in ABA mice. These results have elucidated the critical role of the LPBN-VTA circuit and the potential channel pathology in the disorder, which may serve as a key to the development of drug treatments and intervention strategies for AN.
Space charge drives electromechanical conversion via a piezoelectric-like effect in ion implanted polymers
Authors: Sherrell Peter , Šutka Andris , Fiedler Holger , Linarts Artis , Malnieks Kaspars
Published: November 2024

Ion implantation is a powerful tool to modify materials chemistry and structure. The implantation process was considered to result in a net-neutral material, due to implanted ionic charge being compensated by the host materials lattice. Here, we show ion implantation into polytetrafluoroethylene (PTFE) results in an uncompensated ‘space charge’ region – requiring a reconsideration of ion implantation into polymers. This is demonstrated via electromechanical testing of Cu implanted PTFE as a triboelectric nanogenerator (TENG). Previously, ion implantation into polymers has shown to increase TENG performance, attributed to increasing the prevalence of electron transfer during contact-separation testing. This attribution to electron transfer is incorrect, with significant electromechanical conversion being observed in 1 x 1016 Cu ions cm− 2 implanted polytetrafluoroethylene (PTFE) in both piezoelectric mode testing and in non-contact induction measurements – where electron transfer cannot occur. These results, indicate that the implantation of Cu ions creates a space charge effect in the PTFE matrix, and the subsequent charge asymmetry creates an electric field enhancing TENG performance, analogous to hybrid piezoelectric-TENGs. These results demonstrate that ion implanted polymers possess space charge and can be used directly for sensing, creating a new pathway for electromechanical conversion materials.
Observations reveal changing coastal storms around the United States
Authors: Morim Joao , Wahl Thomas , Rasmussen D.J. , Calafat Francisco , Vitousek Sean , Dangendorf Sönke , Kopp Robert , Oppenheimer Michael
Published: November 2024

Understanding extreme storm surge events that threaten low-lying coastal communities is key to effective coastal flood mitigation and adaptation measures. However, estimates of extremes storm surge events from observations are sparse and highly uncertain along most coastal regions owing to data limitations. There is also lack of observational evidence about their long-term (underlying) trends and how such trends contribute to overall extreme sea-level changes. Here, we analyze the U.S. tide-gauge observational network using a spatio-temporal Bayesian hierarchical framework, which provides robust empirical spatially-continuous estimates of extreme storm surge likelihoods and their underlying long-term trend since 1950 along U.S. coastlines. We find that observational estimates have underestimated likelihoods of storm surge extremes across over 80% of tide gauge locations nationwide. Additionally, and contrary to prevailing beliefs, storm surge extremes show significant trends within widespread regions along the U.S. coastlines, providing new evidence of changing coastal storm intensity during the historical monitoring period. Regional hotspots exist where storm surge trends are comparable to, or even exceed, trends in mean sea-level rise and its major individual components. These findings advance traditional coastal design/planning practices that rely on estimates obtained from discrete observations and assume stationarity in storm surge extremes.