bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of genetic diversity and population structure of Eucalyptus urophylla in Indonesia Islands using SNP Data
Authors: Silva Dandara Yasmim Bonfim Oliveira , Rosa João R. B.F. , Souza Izabel Christina Gava , Nunes Maria Paula Barion Alves , Benatti Thiago Romanos , Fernandes Aline Cristina Miranda , Matos Jose Wilacildo , Oda Shinitiro , Beerli Peter , Tambarussi Evandro Vagner 
Published: November 2024

Abstract

Eucalyptus urophylla is one of the most economically important species in the world due to its wood quality and tolerance to water stress. Understanding the genetic composition at the population level of this species is essential for the sustainable and efficient management and utilization of its genetic resources. This study describes the genetic diversity and population structure of E. urophylla from progenies collected on four islands in Indonesia (Wetar, Timor, Lembata, and Adonara) and conserved ex situ in Brazil. A total of 692 open-pollinated adult individuals from 17 populations were genotyped using 5,374 SNP markers. Analyses of diversity (observed heterozygosity, \(\:{H}_{o}\), and expected heterozygosity, \(\:{H}_{e}\)), population hierarchical levels (\(\:{F}_{ST},\:{F}_{IT},\:\text{a}\text{n}\text{d}\:{F}_{IS}\)), effective population size (\(\:{N}_{e}\)), ancestry, PCA, and dendrogram Neighbor-Joining were conducted. The populations showed greater genetic differentiation at the island level (\(\:{F}_{ST}\) ≤0.055). The estimates of genetic diversity were moderate, with \(\:{H}_{o}\) ranging from 0.39 to 0.47, being higher than \(\:{H}_{e}\), which ranged from 0.30 to 0.36. The sublevels \(\:{F}_{IS}\) and \(\:\:{F}_{IT}\) showed negative estimates, indicating a high proportion of heterozygous individuals in the populations and a negative intraclass correlation, showing that alleles were more related among populations than within them. The populations exhibited low genetic differentiation among themselves (\(\:{F}_{ST}\)=0.05). The analyses showed a clear and significant separation of two genetic clusters. The observed genetic diversity and structure ensure that ex situ conservation can be effectively carried out, preserving and exploring the genetic variability found in natural populations.
Novel Cu-II Complexes of 2-Hydroxy 4-Methoxy Benzylidene 2-Hydroxy Benzhydrazide: Synthesis, Spectral Characterization, Thermal, Antimicrobial, Antioxidant and Catalytic activity Study
Authors: Korane Sangeeta , Bhosale Babasaheb , Jadhav Amol Maruti 
Published: November 2024

Abstract

The novel hydrazone ligand 2-hydroxy 4-methoxy benzylidene 2-hydroxy benzhydrazide [HL] was prepared by condensing 2-hydroxy benzhydrazide and 2-hydroxy 4-methoxy benzaldehyde in methanol solvent. The Cu-II complexes [Cu(HL)(NO3)].1/3H2O (1a), [{Cu (HL)}2 (μ-SO4)].12/3H2O(2a), [Cu(HL)(H2O) Cl](3a) were synthesized by refluxing Cu-II salts CuNO3.3H2O CuSO4.5H2O and CuCl2.2H2O with methanol solution of [HL] and characterized by spectral techniques (FT-IR,1H-NMR,13C–NMR,UV-Visible, PXRD study).The complexes are further characterized by thermo gravimetric(TG)analysis, molar conductivity, elemental analysis and magnetic susceptibility measurement study. FT-IR spectra provides valuable information about different coordination sites. UV-Visible spectroscopy reflect LMCT bands from 242718- 261780 cm-1 and d-d bands in the range of 143884-156250 cm-1 in addition to n-π*and π -π*transition in all complexes. Square planar to square pyramidal geometry was proposed for all complexes as illustrated in magnetic, electronic and spectroscopic data. X-ray powder diffraction analysis reveals crystalline nature for all complexes. The experimental results of TGA analysis are in good agreement with spectroscopic data of complexes. A comparison of spectroscopic and physicochemical data are very useful in creating correct assignments and understanding of structure of complex. The ligand act as tribasic tridentate chelating through the phenolate oxygen, azomethine nitrogen and oxygen of enolate donar functionality with copper-II ion. The antibacterial potential of synthesized complex catalysts was evaluated against human pathogenic bacteria such as Bacillus subtilties, Bacillus cereus, Escherichia coli, Pseudomonas velgaris,and Staphylococcus aureus etc. Also, the Cu (II) complexes demonstrate significant antioxidant activity. The catalytic performance in alcohol oxidation using hydrogen peroxide as a green oxidant is also investigated.
Contrastive Learning-optimized recommendation data to Construct a Language Model Recommendation
Authors: Ka Zuming , Zhao Peng , Zhang Bo 
Published: November 2024

Abstract

Large Language Models (LLMs) have demonstrated remarkable performance across diverse domains, thereby prompting researchers to explore their potential for use in recommendation systems. Initial at-tempts have leveraged the exceptional capabilities of LLMs, such as rich knowledge and strong gener-alization through In-context Learning, which involves phrasing the recommendation task as prompts.Nevertheless, Given the significant disparity between the training tasks of LLMs and recom-mendation tasks, along with the data sparsity issue arising from insufficient recommendation data during pre-training, the performance of LLMs in recommendation tasks remains unsatisfactory. To bridge this gap, we propose fine-tuning LLMs with Contrastive Learning-optimized recommendation data to Construct a Language Model Recommendation. namely CLCLMRec. The CLCLMRec frame-work aims to achieve an effective and efficient integration of Large Language Models with recommen-dation systems in settings with low GPU memory consumption. The framework encompasses two cru-cial tuning phases: firstly, instruction tuning, a universal LLM training process designed to enhance the generalization capabilities of LLMs; and secondly, recommendation tuning, which focuses on fine-tuning the model specifically for recommendation tasks. In Rec-tuning, we employ the self-attention mechanism to process embedded data and emphasize sequential recommendation methods to capture users' dynamic interests. However, addressing the challenge of data sparsity, we innovatively intro-duce contrastive learning, extracting self-supervised signals from user behavior sequences to train large models more effectively and uncover meaningful user patterns. Ultimately, we fuse "recommen-dation instructions" with "recommendation inputs" to construct "instruction inputs" and utilize "rec-ommendation outputs" as "instruction outputs" for training, thereby building a Large Recommendation Language Model (LRLM). Experimental results demonstrate that even with extremely limited data (fewer than 100 samples), the CLCLMRec framework can significantly boost the recommendation ca-pabilities of LLMs in domains such as movies and books.
Cross-modal Attention and Bidirectional LSTM for Audio- Visual Generalized Zero-shot Learning
Authors: Liu Peng , Huang Hua 
Published: November 2024

Abstract

The goal of audio-visual zero-shot learning (ZSL) is to classify videos from unseen categories using only the images and audio of videos from seen categories as training data. However, existing audio-visual zero-shot learning methods have not effectively captured accurate temporal information. To address this, we propose a novel approach that leverages the natural alignment between audio and visual modalities in video data by combining cross-modal attention and bidirectional LSTM (Bi-LSTM) to enhance audio-visual generalized zero-shot learning (GZSL). By integrating Bi-LSTM in parallel with the cross-attention block, we capture the temporal dependencies in both audio and visual streams. Specifically, during cross-modal processing, we add a bidirectional LSTM channel in parallel for data processing and fuse the data obtained from the two channels. This approach helps capture temporal dependencies in audio and video more effectively, enhances model robustness, and reduces information loss. Compared to various state-of-the-art methods, our proposed CAB-LSTM outperforms most existing approaches on three popular audio-visual zero-shot learning datasets.
Gliding between continents: A review of the North American record of the giant flying squirrel Miopetaurista (Rodentia, Sciuridae) with the description of new material from the Gray Fossil Site (Tennessee)
Authors: Grau-Camats Montserrat , Casanovas-Vilar Isaac , Crowe Cheyenne J. , Samuels Joshua X. 
Published: November 2024

Abstract

Flying squirrels (Rodentia, Sciuridae, Sciurinae, Pteromyini) have a long and complex history in North America. First recorded during the Late Eocene, they vanished during the early Late Miocene (at about 9 Ma) only to re-appear in the Pliocene and Pleistocene. The first flying squirrels to be recorded after this Late Miocene gap are surprisingly attributed to the Eurasian genus of giant flying squirrel Miopetaurista. These are just two specimens from Florida that purportedly belong to Miopetaurista webbi, an endemic species. In this work we review these occurrences and further describe a new specimen from the Early Pliocene (latest Hemphillian or early Blancan) Gray Fossil Site in Tennessee, which may represent the oldest record of the genus in North America. We validate their attribution to Miopetaurista webbi and found this species to be probably closely related to Miopetaurista thaleri, the only known Pliocene Eurasian species. The occurrence of Miopetaurista in eastern North America is puzzling, as it is set far away from the known geographical range of the genus and of that of its sister taxon, the extant Petaurista. We hypothesize that Miopetaurista, which was linked to warm forested environments, dispersed into North America via the Bering Land Bridge during the warm phases of the Early Pliocene in the frame of a major faunal dispersal involving many other taxa. Later climatic cooling isolated these squirrels in warmer refuges, such as Florida, until they finally became extinct during the Pleistocene.
WITHDRAWN: A novel silica aerogel-based modified adsorbent for the efficient removal of toluene from aqueous media: characterization, central composite design optimization, isotherms, kinetics studies
Authors: Abedi Vida , Taghavi Lobat , Frahani Hadi , Panahi Homayon Ahmad , Larijani Kambiz 
Published: November 2024

Abstract

This study presents the preparation and evaluation of a novel adsorbent designed for removing organic solvents from wastewater, focusing on toluene, a common toxic solvent. The adsorbent, a unique blend of silica aerogel, recycled polyethylene terephthalate (rPET) short fibers, FeCl3, and chitosan, was rigorously tested and characterized using a range of methods. The adsorption performance of the adsorbent was tested for various organic solvents, with detailed attention to toluene. The adsorption parameters, including adsorbent dosage, initial toluene concentration (100-1000 ppm), contact time (15-40 minutes), pH (2-10), and temperature (18-40 °C), were investigated using response surface methodology (RSM) based on central composite design (CCD). The maximum toluene removal efficiency was 99.52%, achieved under optimal conditions. The adjusted coefficient of the determination of the model was 0.968, which indicates that the model was entirely appropriate and accurate. Kinetic studies suggested that the adsorption followed pseudo-second-order kinetic, while equilibrium data were well-fitted to Langmuir and Freundlich isotherms. The stability of the adsorbent across four regeneration cycles demonstrates its potential for long-term application in sustainable water treatment. These results, along with the potential for long-term application, suggest that the developed adsorbent is a promising solution for effectively remedying toluene and some organic matters like crude oil-contaminated wastewater, contributing to environmental protection and plastic waste management.
Ramification of Relaxed Thermoregulation Under Climate Change
Authors: Lefcort Hugh , Brockman Sean M. , Hopkins Jaxon W. , Salter Sierra M. 
Published: November 2024

Abstract

How animals respond to climate changes may be limited by their niche dimensions. Animals able to select microhabitats will be less affected than those that physically or behaviorally are unable to change their exposure. Hence the outcome of tick responses to climate change - which may affect transmission of diseases to humans - may not be obvious first-order effects. Tick species that actively move throughout their habitat searching for hosts may be able to utilize microhabitats that avoid the full effect of rising temperatures. Other tick species are more static since they wait for hosts to come to them. So even if a tick has a low preferred temperature, the need to be present in questing sites optimal for encountering hosts may force exposure to near lethal elevated temperatures. To further explore the questing behavior of Dermacentor variabilis and D. andersoni, and to test if regional variation is exhibited by adult D. variabilis, we reproduced a study that found that this species is an active hunter that orients and moves towards infrared radiation (IR) by use of Haller’s organs. We also tested if D. andersoni would move towards an exposed human hand, i.e. a host emitting a combination of IR, CO2, and odors. This tested if the tick species exhibits sit-and-wait or active hunting. We found strong sit-and-wait behaviors by D. andersoni and D. variabilis. The ticks did not move toward the stationary exposed hand of an observer, and they were not attracted to infrared radiation. Tick may prioritize optimal locations to encounter potential hosts, over enzymatically optimal temperatures. Rather than evolving to detect hosts at a distance, Haller’s organs may have evolved to differentiate warm attachment sites from cooler fur. Our results suggest that Dermacentor questing behavior (remaining on station irregardless of preferred temperature) may make them particularly vulnerable to future rises in temperature.
Integrated test case generation and prioritization based on multiple coverage criteria
Authors: Guo Zhonghao , Geng Chenge , Xu Xinyue , Chen Xiangxian 
Published: November 2024

Abstract

Purpose: Software testing is crucial for ensuring software quality, but it often consumes significant time and resources. Test case generation tools can generate test cases which cover the elements of tested program. However, some types of test case generation algorithms, such as those based on symbolic execution, can also gather coverage information during the test case generation process, which is undoubtedly valuable for other testing tasks. Test case prioritization (TCP) helps detect software faults earlier, achieving better testing outcomes under limited resources. Our goal is to enhance TCP without increasing costs, making it applicable across all white-box testing while improving its effect.
Methods: We developed MCTCG, a symbolic execution-based test case generation tool that produces test case sets meeting various coverage criteria. During generation, MCTCG analyzes program coverage for elements like statements and branches to guide the next step. We also proposed TCPall−first , a prioritization method that uses the coverage information of MCTCG to prioritize test cases based on the principle of 'maximizing coverage step by step.' It selects test cases that cover the most uncovered elements until full coverage is achieved. Since TCPall−first directly uses the coverage data of MCTCG, there is no need to re-execute the test cases to determine priority, allowing test case generation and prioritization to occur in the same process, saving significant testing resources.
Results and conclusion: We evaluated our approach using multiple open-source programs. The results show that MCTCG successfully generates high-coverage test case sets according to various coverage criterias, with higher bug detection rates. TCPall-first uses the coverage information obtained during the generation process to determine test case prioritization. Compared with the best performing among other TCP methods, TCPall−first improved the APFD value by 4.11% and reduced the first-fail metric by 8.7%. Moreover, TCPall−first required the fewest test cases to detect the same number of bugs compared to all other methods. Therefore, we believe that MCTCG effectively enhances test case set coverage while gathering coverage information, and TCPall−first extends the applicability of TCP and improves coverage-based TCP techniques.
A Reconstructed Priority Assignment Method for Computationally Intensive Task Offloading in Mobile Communication Networks
Authors: Zou Qun , Ambati Loknath Sai , Reddy Thippa 
Published: November 2024

Abstract

Computationally intensive tasks often require substantial energy support, and mobile devices may experience slow task execution, response delays, and device overheating due to insufficient processing capabilities. By offloading computationally intensive tasks, the energy consumption of mobile devices can be reduced, and the resource utilization and network balance of mobile communication networks can be improved. Therefore, this paper designs a refactored priority division method for offloading computationally intensive tasks in mobile communication networks. This method first calculates the execution delay and energy consumption of mobile communication network system devices, mobile edge computing servers, and cloud servers, and uses these as factors for the refactored priority division of computationally intensive tasks. Then, it employs the Analytic Hierarchy Process (AHP) to refactor the priority division of computationally intensive tasks in mobile communication networks. In addition, deep reinforcement learning is used to comprehensively consider multiple factors such as delay and energy consumption to find the optimal offloading decision. Experimental results show that this method can effectively offload computationally intensive tasks from mobile devices and mobile edge computing servers and improve the balance of mobile communication networks.
Electro-osmotically Modulated Viscoelastic SWCNT-Blood flow in Symmetric/Nonsymmetric Stenosed Arteries with heat generation using a Fractional Second Grade Model
Authors: Channakote Mahadev M , Bég O. Anwar , Kuharat S. , Shekar M. , Siddabasappa C. 
Published: November 2024

Abstract

The current study aims to analyse the electro-osmotically driven non-Newtonian blood flow containing single-walled carbon nanotubes (SWCNTs) in symmetric and non-symmetric stenosed arteries. This nanoscale formulation considers the impact of SWCNTs on flow characteristics, with a key focus on the thermal and electrical properties of blood. The fractional viscoelastic second grade Reiner-Rivlin differential model is deployed for rheological effects and employs Caputo's definition. Heat generation and thermal buoyancy (natural convection) are also considered. The Debye-Hückel linearization approximation is used to analyse the electro-osmotic dynamics. The system of partial differential equations relevant to the problem is simplified to an ordinary differential equation system by virtue of suitable scaling transformations. Analytical solutions are derived for the non-dimensional boundary value problem. Axial velocity, temperature, electrical potential, volumetric flow rate, axial pressure gradient, pressure rise, and wall shear stress have been computed and selected characteristics have been visualized with the aid of graphs using Mathematica software. The computations show that there is a depletion in the velocity at the walls whereas there is a strong elevation in the core zone for both symmetric (n=2) and non-symmetric (n=6) shapes of stenosis with increasing positive values of Helmholtz-Smoluchowski velocity (UHS), non-Newtonian fractional viscoelastic parameter (λ), carbon nanotube (CNT) volume fraction (ϕ), electro-osmotic Debye length parameter (m) and stenosis height (ϵ). With increasing heat generation parameter (β>0), axial velocity is enhanced across the arterial section and temperature is enhanced. Temperature and wall shear stress (τ_w ) are both strongly reduced with greater carbon nanotube (CNT) volume fraction (ϕ). An increment in volume flow rate (Q) and stenosis height (ϵ) enhances wall shear stress values. A non-symmetric shape of stenosis (n =6) generally produces higher temperatures than the symmetric shape case (n =2). An assessment of trapping phenomena shows that size and number of trapping boluses are increased with higher volumetric flow rate (Q) for both the non-symmetric and symmetric stenotic cases.
Quantifying Calcium Dynamics in T Cell Populations: An Automated Analysis Framework for Antigen Fluorescence Applying Functional Anova
Authors: Rocha-Clavijo Daniel , Suarez-Gomez Deiver , Miranda Gabriel , Rosas Norma Pérez , Alvear Alibeth E Luna , Braña Santiago Colom , Isaza Clara E. , Cabrera-Rios Mauricio 
Published: November 2024

Abstract

Calcium plays a pivotal role in a wide array of physiological processes, serving as a key indicator of cellular activity. This study underscores the importance of understanding calcium patterns in response to stimuli, highlighting the necessity of automated segmentation in fluorescence movies to analyze large cell populations exposed to diverse stimuli. We present a framework for analyzing videos capturing calcium fluorescence in extensive T cell populations exposed to multiple antigens, including UCHT1, 9V:MHC, OKT3, 4D:MHC, and a negative antigen-free control. We utilized Fiji software for video preprocessing and CaImAn for region of interest segmentation and temporal calcium transient extraction. Subsequently, we conducted statistical analyses using empirical models including linear and polynomial regression, spline regression, and functional additive models. Our findings indicate that the functional ANOVA model was the most appropriate, revealing significant impacts of calcium signaling for the aforementioned antigens and the negative control across distinct time intervals. This study developed an interactive Shiny application called SignalPredict where the functional ANOVA model is available, thus facilitating analysis for scientists without programming expertise. These findings support the concept of unique effects of each antigen on calcium signaling in T cells, enhancing our understanding of cellular activity and its implications in biomedical and immunological research. This methodology provides a valuable tool for further exploration of cellular response in physiological and pathological contexts.