bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disturbance regimes favor alternative plant communities in the natural grasslands of the Pampa Austral (Argentina)
Authors: de Villalobos Ana Elena , Charles-Dominique Tristan 
Published: March 2024

Abstract

The Austral Pampa hosts extensive and diverse grasslands, which, over the last century, have been exposed to climate change and unprecedented disturbance regimes, including domestic herbivory and a novel fire regime. Predicting community responses to these changing conditions and designing appropriate conservation plans requires dissociating the individual contribution of each factor to community filtering. We ask whether fire, herbivory, temperature and drought, favor distinct communities in Pampean grassy ecosystems and which plant traits. Field surveys were conducted in three areas of the Ventania Mountain System in Pampa Austral (Argentina) exposed to varied fire, herbivory, and drought regimes. A total of 140 plant species were examined across 8 sampling areas, selected as representing different disturbance regimes. We measured 17 functional traits related to plant height, reproduction, and leaf area. The relationships between these traits and environmental variables were analyzed using RLQ and fourth-corner methods. RLQ analysis revealed that temperature, rainfall, and herbivory influenced plant communities, while fire frequency had less impact. We identified five distinct plant functional groups (PFGs) that differed in perenniality, type of pollination, resprouting capacity, spinescence, leaf hairiness and leaf area. Separating the effects of herbivory, fire, and drought reveals that multiple stresses could influence communities, resulting in higher resprouting and shorter life cycles. Analyzing how functional traits respond to environmental factors and disturbances provides insights into the conservation challenges posed by these changing disturbance dynamics in the Pampa biome.
Preparation of nanocrystalline stacked spherical SnO2 with higher specific surface area and its gas-sensing performance
Authors: ZHENG Xian-Jun , Liu Songtao , Wang Junbo , Si Fang , Hou Haiyun , Jiang Fengyang , Sun Zhongming , Liu Jianjiang , Fang Chenyu 
Published: March 2024

Abstract
In order to improve the sensitivity of SnO2 to ethanol gas, the spherical SnO2 with a particle size of 0.25μm and uniform particle distribution was prepared by hydrothermal method without adding surfactants. The characterizations were conducted，and the results showed that the spherical SnO2 particles were stacked by fine grains with a grain size of 4nm, with a higher specific surface area of 232.2043m2/g than existing research results. The gas-sensing performance test results show that the spherical SnO2 has the best gas-sensing selectivity to ethanol, with an optimal working temperature of 300℃. When the ethanol concentration is 100ppm, the gas sensitivity of spherical SnO2 to ethanol is 48.28, with a response time of 4s and a recovery time of 15s. Even to low concentration ethanol of 2ppm, the sensitivity of the spherical SnO2 can reach 4.6, indicating excellent gas-sensing performance of the spherical SnO2. This study provides data reference for the research and development of high-performance gas sensors.
Low Current Non-Thermal Plasma Assisted Hydrocarbon Reforming Hydrogen Rich Gas
Authors: P Rajkumar , B Prem Anand 
Published: March 2024

Abstract
Current trends in the automotive industry include the use of hydrogen, GDI engines, and PEM fuel cell systems. low-current non-thermal plasma-assisted hydrocarbon reforming hydrogen-rich gas ways to produce it on board automobiles. In this study, we introduce the plasma fuel reformer (PFR), a non-thermal device that uses the partial oxidation process as its primary mechanism. Plasma is created by PFR using air at higher pressures than the atmosphere. Plasma is generated by an electrode gap discharge and continuous air and fuel infusions. Exothermicity from partial oxidation generates the most heat. The unique Plasma Fuel Reformer (PFR) has three sections in a stack: fuel injection, plasma production fuel reaction, and heat exchanger. The low-current non-thermal plasma is designed to convert gasoline into hydrogen-rich gas under non-thermal circumstances. The first section briefly describes hydrocarbon reforming chemistry. The second section is low-current non-thermal plasma fuel reformer (PFR) technology and design. This novel plasma reformer is still in its early stages of development, but there are a number of technical tweaks that might significantly enhance its chemical efficiency.
Biomechanical Analysis for Ameliorated Escape-resistant Intervertebral Fusion Devices
Authors: Tang Shaolong , Pan Dan , Chen Siyuan , Li Hengyuan , Ye Zhaoming 
Published: March 2024

Abstract
Background
This study aims to compare the sinking and shifting of an enhanced escape-proof intervertebral fusion device with a traditional TLIF intervertebral fusion device.
Methods
Five specimens each of the improved escape-resistant intervertebral cage and the traditional TLIF cage were selected. Four types of mechanical tests were conducted on each cage, Furthermore, a blade-cutting torque test was performed on the escape-resistant cage, with the recording of load-displacement curves and mechanical values.
Results
In static axial compression performance testing and static subsidence testing and dynamic subsidence testing, the improved escape-resistant cage were similar to those of the traditional TLIF ccage. In static escape performance testing, the maximum escape force when the blade rotated out for the improved escape-resistant cage (534.02 ± 21.24N) was higher than the maximum escape force when the blade did not rotate out (476.97 ± 24.45N) (P = 6.81E-04). The maximum escape force when the blade rotated out for the improved escape-resistant cage (534.02 ± 21.24N) was significantly higher than that of the traditional TLIF cage (444.01 ± 12.42N) (P = 9.82E-05).
Conclusions
The improved escape-resistant cage product effectively enhances the device's escape prevention and anti-subsidence performance, it demonstrates biomechanical advantages.
The effects of two biofertilizers on the physiology of replanted Zanthoxylum bungeanum and soil phenolic acids
Authors: Zhang Shuheng , Chen Wei , Wang Bin , Ding Dedong , He Jing 
Published: March 2024

Abstract

To solve the issues of low survival rate and poor vigor of Zanthoxylum bungeanum seedlings caused by long-term continuous cropping, a study was conducted using bio-organic fertilizer and microbial bacterial fertilizer as repair agents. The aim was to investigate their effects on the physiological metabolism of Zanthoxylum bungeanum seedlings and soil phenolic acids, with a focus on understanding the growth-promoting mechanism of replanted Zanthoxylum bungeanum. The results revealed that fertilization significantly increased the activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), nitrate reductase (NR), as well as the levels of soluble sugar (SS) and soluble protein (SP) in Zanthoxylum bungeanum seedlings. Conversely, the content of malondialdehyde (MDA) and four soil phenolic acids (gallic acid (FA), ferulic acid (GA), caffeic acid (CA), and p-hydroxybenzoic acid (PHBA) were significantly reduced. The mixed application of microbial fertilizer and bio-organic fertilizer showed better growth-promoting effects compared to single application. Specifically, when the volume ratio of microbial fertilizer and bio-organic fertilizer was 2:1, the activity of defense enzymes was most significantly promoted. Under this treatment, the activities of SOD, CAT, POD, and NR in seedlings were 1.8, 3, 3.8, and 5.3 times higher than the control (no fertilization treatment), respectively. The levels of SS and SP were 2.4 and 2.5 times higher than the control, respectively. The MDA content was 27% of the control, and the total content of the four phenolic acids was 60% of the control. Principal component analysis results showed that the scores of fertilization treatments were higher than the control, with the order being T6 > T7 > T2 > T5 > T4 > T3 > T1 > T0. Therefore, the combined application of microbial fertilizer and bio-organic fertilizer effectively promotes the physiological metabolism of seedlings, reduces the content of soil phenolic acids, and has a positive effect on alleviating the obstacles to continuous cropping of Zanthoxylum bungeanum.
Training transfer validity of virtual reality simulator assessment
Authors: Hjellvik Simen , Mallam Steven 
Published: March 2024

Abstract

This study utilises computer-based simulations to explore the transfer effects of competency training in maritime education, addressing the current lack of research on their transferability to real-world scenarios. The research explores the accuracy of procedural knowledge assessment using virtual reality, positing that head-mounted display (HMD) VR offers stronger concurrent validity through training transfer measures than 3D desktop VR. This is evaluated by regression on a training transfer condition. It also investigates motivation's influence on training transfer and the model of this relationship. Fifteen marine engineering students were divided into two experimental groups using 3D desktop VR and HMD VR systems, with eight experts in the control group. The students had previously received traditional lecture-based instruction and were given practical training using a 2D desktop simulator in the same scenario as in the VR treatment and in the training transfer condition. The ANCOVA design experiment involved two levels of technical immersion before the operation of real-life equipment. Neither technical immersion nor expertise level as independent variables were found to have a significant effect in the relationship of the assessment predicting the training transfer. The direct relationship was significant (R 2 adj =.436) and further analysed with the influence of motivation, resulting in a moderation model with a decent effect size (R 2 =.740). We can infer on these findings that both types of VR simulation used for assessment demonstrate concurrent validity in predicting real-life performance, however, we found no support for one over the other.
Analysis and Knowledge Extraction of Newborn Resuscitation Activities from Annotation Files
Authors: Abukmeil Mohanad , Meinich-Bache Øyvind , Eftestøl Trygve , Rettedal Siren , Myklebust Helge , Tysland Thomas Bailey , Ersdal Hege , Md Estomih , Engan Kjersti 
Published: March 2024

Abstract

Deprivation of oxygen in a newbornduring and after birth leads to birth asphyxia, which is considered one of the leading causes of death in the neonatal period. Adequate resuscitation activities are performed immediately after birth to save the majority of newborns. The primary resuscitation activities include ventilation, stimulation, drying, suction, and chest compression. While resuscitation guidelines exist, little research has been conducted on measured resuscitation episodes. Modeling the executed resuscitation activities to generate temporal data and extract knowledge can provide unique insights into dominant resuscitation activities. It also aids in constructing a resuscitation timeline to visually represent and describe the actions performed on a newborn.In this paper, we propose a method for generating and encoding temporal resuscitation data, enabling the description and visualization of the resuscitation timeline. We utilize neighborhood component analysis (NCA) to cluster the generated data based on the presence of ventilation and the outcome of the newborn. Additionally, we employ an autoencoder (AE) model to enhance clustering performance by visualizing its latent space.Our proposed method demonstrates high-quality visual clustering results on two different datasets. It provides insights into the intricate structure of the generated resuscitation data by grouping similar unlabeled resuscitation episodes into coherent clusters.
Assessing long-term landscape dynamics based on automated production of land category layers from Danish late 19th century topographic maps
Authors: Levin Gregor , Groom Geoff , Svenningsen Stig Roar 
Published: March 2024

Abstract

Context
Assessing long-term land use and land cover (LULC) change is critical for understanding of landscapes dynamics. Historical topographic maps contain valuable, spatially explicit information about past LULC. Yet, for analyses of landscape dynamics, it is necessary to "unlock" this information through recognition and extraction via map processing.
Objectives
Our main goal was to test automated extraction of machine-readable LULC categories from historical topographic maps. Furthermore, we explore landscape dynamics and discuss potential biases associated with category changes between historical and contemporary LULC data.
Methods
For two study areas in northern and central Jutland, Denmark we apply object-based image analysis (OBIA), vector GIS, colour segmentation and machine learning processes to produce machine readable LULC layers from topographic maps from the late 19th century. By comparison with contemporary maps, we investigate landscape dynamics over 140 years.
Results
An accuracy assessment applied to the extracted LULC categories indicated an overall obtained accuracy beyond 90 %. A comparison with a contemporary map revealed landscape dynamics, which are characterised by a decrease in heath, wetland and dune sand due to cultivation and afforestation. Dune sand was also characterised by a change to heath and dry grassland.
Conclusions
We conclude that automated production of machine-readable LULC categories from historical maps offers a less time consuming and more resource efficient alternative to manual vectorisation. Our results also underline that an understanding of mapped LULC categories in both historical and contemporary maps is critical to the interpretation of landscape dynamics.
Lasting Legacy: The enduring relationship between racially restrictive housing covenants and health and wellbeing
Authors: West Kristine Lamm , Allen Elizabeth , LaPlante Ava , Durben Anchee Nitschke , Palma Victoria Delgado 
Published: March 2024

Abstract

Racially restrictive covenants in housing deeds, commonplace for houses built from the 1910s to the 1950s, provided a foundation for the myriad of policies that made it difficult for people of color to obtain housing. Though covenants were ruled illegal in 1968, their legacy continues to shape neighborhoods. The Mapping Prejudice Project (MPP)’s efforts in Hennepin County, Minnesota produced the first systematic documentation of racially restrictive covenants. We use this novel data set to explore the relationship between historic covenants and current health and wellbeing outcomes. Using regression analysis to control for neighborhood level covariates, we compare previously covenanted neighborhoods to neighborhoods without covenants. We find that racially restrictive covenants have a lasting impact. Today covenanted neighborhoods have higher life expectancy and lower rates of obesity, diabetes, coronary heart disease and asthma than neighborhoods without racially restrictive covenants. Additionally, covenanted neighborhoods have less upward mobility for children from poorer households and there are larger gaps in upward mobility between white and black children. These findings contribute to a growing literature that shows racist policies, even decades after they are legally enforceable, have enduring impacts. Using the novel data from the MPP we provide statistical analysis that confirms qualitative and anecdotal evidence on the role of racial covenants in shaping neighborhoods.
High-Fidelity Simulations of Contaminant Dispersion in an Urban Environment with Comparison to Magnetic Resonance Imaging Measurements
Authors: Owkes Mark , Homan Ty , Benson Michael , Banko Andrew 
Published: March 2024

Abstract

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm (CIA) that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets agree very well and identify complex flow features within the urban environment.
Immunohistochemical analysis and distribution of epithelial mast cells in the rat larynx and trachea
Authors: Abdali Sayed Sharif , Yokoyama Takuya , Yamamoto Yoshio , Narita Keishi , Hirakawa Masato , Saino Tomoyuki 
Published: March 2024

Abstract

Mast cells (MCs) in rat airways have been classified into two subtypes: epithelial MCs and connective tissue MCs (CTMCs). However, the immunohistochemical characteristics, cellular morphology, and distribution of epithelial MCs in the upper airways remain unclear. The present study investigated the morphological characteristics and distribution of epithelial MCs using 5-hydroxytryptamine (5-HT) and other immunohistochemical markers in sectioned or whole-mount preparations of the rat larynx and trachea. A double immunofluorescence analysis revealed the co-localization of 5-HT immunoreactivity with c-kit, a stem cell factor receptor commonly used as a MC marker, in both epithelial MCs and CTMCs. Dopa decarboxylase, an enzyme involved in 5-HT synthesis, was detected in both subtypes, suggesting their ability to synthesize and release 5-HT. Tryptase and histidine decarboxylase (a biosynthetic enzyme of histamine), which are well-known mediators of MCs, were exclusive to CTMCs. Epithelial MCs were pleomorphic with long cytoplasmic processes, whereas CTMCs were round and lacked cytoplasmic processes. The density of epithelial MCs was significantly higher in the glottis and cranial part of the trachea than in the epiglottis and other parts of the trachea. The present results showed that the morphology and immunohistochemical characteristics of epithelial MCs were different from those of CTMCs in the rat larynx and trachea, and variform epithelial MCs were predominantly located at the entrance of the upper airways. Epithelial MCs may release 5-HT in the vicinity of epithelial cells that regulate innate immune responses by modulating epithelial cell functions at the entrance gate of the upper airways.
ZRRD-MBNet：Zero-Reference RETINEX Decomposition-Based Multi-Branch Network for Low-Light Image Enhancement
Authors: Liu Xianzhi , Tong Zhengrong , Wang Hao , Li Peng 
Published: March 2024

Abstract
To address the challenges of low visibility, poor contrast, and significant noise in images captured under various extreme conditions, such as backlighting and low-light situations, we propose a novel zero-reference Retinex decomposition-based multi-branch network known as ZRRD-MBNet for enhancing low-light images. The ZRRD-MBNet is divided into two main components: decomposition and recovery. The decomposition part can separate the input low-light image into three distinct components: the illuminance map, the reflection map, and the noise map. On the other hand, the recovery part follows a dual-path approach. The first path involves gamma transforming the generated illuminance map to enhance brightness effectively. Simultaneously, the second path divides the input low-light image element-wise by the originally decomposed illuminance map. The result is then subtracted element-wise from the noise map obtained during decomposition, yielding a denoised reflection map. To obtain the final enhanced image, the denoised reflectance map is multiplied with the brightness-enhanced illuminance map. The specific loss functions are critical for updating the weight parameters of ZRRD-MBNet and guiding the network during low-light image decomposition. Extensive qualitative and quantitative experiments are conducted using publicly available datasets. The results demonstrate that our method produces high-quality images with clarity, minimal noise, and absence of artifacts.
Characterisation of a novel “glyco-organochlorine” bioflocculant produced from Pseudomonas aeruginosa strain F29 isolated from pig fecal matter collected from a mixed animal farm in Ibadan, Oyo State, Nigeria
Authors: Okorie I. K. M. , Ogunjobi A. A. 
Published: March 2024

Abstract
Antibiotic resistance has reached global proportions, and the discovery of effective alternatives to the common antibiotics currently in use, could aid in solving this problem. The aim of this study was to characterise a bioflocculant produced from Pseudomonas aeruginosa strain F29, accession number OQ734844, with 69% flocculating activity and which had been observed to possess biocontrol activity against Staphylococcus aureus SO183 at concentrations of 0.090 g/L and 0.150 g/L and against identified Pseudomonas aeruginosa at a concentration of 0.150 g/L. Pseudomonas aeruginosa strain F29, was isolated from pig fecal matter collected from a mixed animal farm in Ibadan, Nigeria via the pour plate method, identified through biochemical tests and confirmed through molecular studies. Fourier transform infrared (FTIR) spectroscopy of the bioflocculant revealed the presence of carboxyl, aromatic alcohol, alkene, halo and polysulfide functional groups. Scanning electron microscopy (SEM) revealed a clumped and flaky bioflocculant surface while energy dispersive X-ray spectroscopy (EDX) revealed the main chemical elements were chlorine (56.00%), carbon (20.50%), sodium (12.50%), oxygen (4.00%), and phosphorus (3.00%). High performance liquid chromatography (HPLC) and mass spectrometry (MS) revealed that the bioflocculant consisted of carbohydrate sugar moieties of glucose, galactose, inositol and mannose, D-ribose, arabinose, rhamnose and xylose; each with varied peaks. The phenolic sulfuric acid method showed that the concentration of these sugars was 0.0059 g/L. The bioflocculant was a polymeric compound composed mainly of carbohydrates and organochlorines, possibly known as a “glyco-organochlorine.” From available documentation, this is the first report of a “glyco-organochlorine” bioflocculant.
Generative Adversarial Network Model to Classify Human Induced Pluripotent Stem Cell-Cardiomyocytes based on Maturation Level
Authors: Wu Ziqian , Park Jiyoon , Steiner Paul R. , Zhu Bo , Zhang John X.J. 
Published: March 2024

Abstract
Objective: Our study develops a generative adversarial network (GAN)-based method that generates faithful synthetic image data of human cardiomyocytes at varying stages in their maturation process, as a tool to significantly enhance the classification accuracy of cells and ultimately assist the throughput of computational analysis of cellular structure and functions.
Methods: Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) were cultured on micropatterned collagen coated hydrogels of varied stiffness on which structural and optical measurements were performed to analyze their structural and functional maturation. Control groups were cultured on collagen coated glass well plates. These image recordings were used as the real data to train the GAN model.
Results: The GAN approach was able to replicate true features from the real data, and inclusion of such synthetic data significantly improved the classification accuracy compared to he exclusive usage of only real experimental data limited in scale and diversity.
Conclusion: The proposed model outperformed four conventional machine learning algorithms by incorporating synthetic data to improve both data generalization and classification.
Significance: This work demonstrates the potential utility of integrating synthetic data to effectively address the challenges imposed by constrained data.