bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expression and Application Research of Novel Endolysin Ply6A3 and Holin Hol6A3 in Bacteriophage PD6A3 from Acinetobacter baumannii
Authors: Wu Minle , Yang Yang , Wang Hanqing , Wang Beili , Pan Baishen , Xie Youhua , Guo Wei 
Published: October 2024

Abstract

Background
Currently, the excessive use of antibiotics makes the treatment of drug-resistant bacterial infections difficult. Phages have recently emerged as potential alternatives to antibiotics. However, their high specificity and constrained host range limit their clinical application.
Methods
The entire genome of bacteriophage PD6A3 was sequenced. Bioinformatic tools were used to predict genes and delineate the protein structures. A prokaryotic expression system for Ply6A3 and Hol6A3 was established. The antibacterial efficacy, thermal and pH stability, and cytotoxicity of Ply6A3 and Hol6A3 were investigated thoroughly. Additionally, bacterial resistance to these recombinant proteins was explored.
Results
This study achieved high-purity expression of Hol6A3 holin and Ply6A3 endolysin from the A. baumannii phage PD-6A3. Biochemical properties revealed Ply6A3 and Hol6A3 retained stable activity under different conditions.. These proteins exhibit broad-spectrum and potent bactericidal effects against various pathogens, indicating their potential clinical applications.
Conclusion
These enzymes represent a novel category with potent bactericidal effects and are effective against clinically resistant bacteria. These enzymes have a lot of antibacterial potential; they break down a wide range of bacteria, do not produce endotoxins, maintain their antibacterial functions, and do not easily develop drug resistance. Additionally, they exhibit synergistic effects in combating bacterial infections.
Adverse effects of Dichlofluanid on neotropical marine organisms
Authors: Cruz Ana Carolina Feitosa , Pauly Guacira de Figueiredo Eufrasio , Campos Bruno Galvão , Castro Ítalo Braga , Abessa Denis Moledo de Souza , Kamikawachi Renan Canute 
Published: October 2024

Abstract

This study aimed at evaluating the chronic and acute toxicity of dichlofluanid, an antifouling biocide, on marine invertebrates. Chronic toxicity tests with waterborne dichlofluanid were conducted with embryos of the sea-urchin Echinometra lucunter and ovigerous females of the copepod Nitocra sp. Chronic and acute toxicity tests with sediments spiked with dichlofluanid were performed with Nitocra sp. and the amphipod Tiburonella viscana, respectively, considering sediments with low and high quantities of organic matter. Toxicity was above the environmental concentrations reported in the literature for water. Toxicity to embryos of E. lucunter occurred from 1 µg/L, with effective concentrations to 50% organisms (EC50-40h) estimated as 198.5 (84.6-466.1) µg/L. For the copepod, toxicity started at 100 µg/L, and EC50-7d was 566.4 (304.0-738.4) µg/L. No sediment toxicity was observed to Nitocra sp., while significant effects on the amphipods occurred from 1000 ng/g. Sediments with high organic matter were more toxic. Dichlofluanid may be toxic to marine invertebrates; however, in sediments, its toxicity may be influenced by the amount of OM, since organically enriched sediments exhibited higher toxicity.
ZIF-L coated cotton fabric for antibacterial and self-cleaning applications
Authors: Qiu Qiaohua , Lan Liying 
Published: October 2024

Abstract

Textiles that possess antibacterial and self-cleaning properties play a crucial role in preventing the growth and spread of microbes. Zeolitic imidazolate framework-L (ZIF-L) nanostructures have gained significant attention in research due to their ability to sustainably release Zn2+ ions, coupled with the physical destruction of bacteria by their blade tips. Integrating natural fabrics with ZIF-L represents an effective approach to enhancing the value-added features of textiles with unique functionalities. In this study, we reported a facile technology for the in-situ growth of ZIF-L on cotton fabrics. A uniform and dense coating of leaf-shaped nanostructures by doping Cu2+ ions on ZIF-L was formed on the cotton fiber surface (Cu@ZIF-L@Cotton), followed by treatment with methyltrimethoxysilane (MTMS) to obtain water-repellent MTMS/Cu@ZIF-L@Cotton fabric. The resulting fabrics exhibited excellent antibacterial activities against both Gram-negative and Gram-positive bacteria, effectively killing 5 log CFU (>99.999%) of E. coli and S. aureus. Furthermore, the prepared cotton fabric not only showed hydrophobicity with a water contact angle of 132° ± 0.58 but also displayed good self-cleaning properties. Additionally, these fabricated fabrics showed good functional stability after washing. It is therefore believed these valuable functions could significantly enhance the practical feasibility of the fabric in various application scenarios.
Analysis of genetic parameters, heritability, and path analysis in chickpeas under irrigated and rainfed conditions
Authors: Kakaei Mehdi , Farshadfar Mohsen 
Published: October 2024

Abstract

Chickpea is a crop containing high protein and has a vital role in the diet of food security in the world, especially in developing countries. An experiment was conducted to evaluate the genetic diversity, heritability, and path analysis in chickpea cultivars, based on the Randomized Complete Block Design with three replications in 2023. The geographical coordinates are north latitude 34°58′ longitude 18°48′ and altitude was 1607. Calculation of genetic correlation in both environmental conditions showed that traits of plant height, number of seeds per plant, number of pods per plant, single plant biomass, seed yield of single plant without pods, the total number of main branches of the plant, grain yield of single plant with pods, grain yield (m2), biomass (m2), the stubble weight and harvest index, had high genetic correlation with each other. The highest percentage of heritability in irrigated conditions was related to biomass (m2) (0.96), number of pods per plant, and SPAD chlorophyll index at the fruiting stage (0.98). The highest percentage of heritability of grain yield (m2) under irrigated was (0.97), biomass, and SPAD chlorophyll index (0.99). The grain yield, biomass, and SPAD chlorophyll index at the fruiting time had the highest amount of heritability under rainfed conditions and also had the highest level of genetic gain. In normal conditions, traits the total number of main branches of the plant (0.06) and grain yield (0.09), had the lowest heritability and genetic gain. Under drought stress, trait the total number of main branches of the plant (0.16) had the lowest heritability and also had the lowest genetic gain (1.07). These results can be used in breeding programs to select for drought tolerance. The first four principal components accounted for 90.966% of the variance under irrigated and 95.362% of variance under rainfed conditions.
Multi-Locus Genome Wide Association Study Uncovers Genetics of Fresh Seed Dormancy in Groundnut
Authors: Bomireddy Deekshitha , Sharma Vinay , Gangurde Sunil S. , D. Khaja Mohinuddin , Kumar Rakesh , Senthil Ramachandran , Singh Kuldeep , Reddisekhar Mangala , Bera Sandip K. , Pandey Manish K. 
Published: October 2024

Abstract

Pre-harvest sprouting in groundnut leads to substantial yield losses and reduced seed quality, resulting in reduced market value of groundnuts. Breeding cultivars with 14–21 days of fresh seed dormancy (FSD) holds promise for precisely mitigating the yield and quality deterioration. In view of this, six multi-locus genome-wide association study (ML-GWAS) models alongside a single-locus GWAS (SL-GWAS) model were employed on a groundnut mini-core collection using multi season phenotyping and 58K “Axiom_Arachis” array genotyping data. A total of 9 significant SNP-trait associations (STAs) for FSD were detected on A01, A04, A08, A09, B02, B04, B05, B07 and B09 chromosomes using six ML-GWAS models. Additionally, the SL-GWAS model identified 38 MTAs across 14 chromosomes of groundnut. Remarkably, a single STA on chromosome B02 (qFSD-B02-1) was consistently identified in both ML-GWAS and SL-GWAS models. Furthermore, candidate gene mining identified nine high confidence genes viz., Cytochrome P450 705A, Dormancy/auxin associated family protein, WRKY family transcription factor, Protein kinase superfamily protein, serine/threonine protein phosphatase, myb transcription factor, transcriptional regulator STERILE APETALA-like, ethylene-responsive transcription factor 7-like and F-box protein interaction domain protein as prime regulators involved in Abscisic acid/Gibberellic acid signaling pathways regulating dormancy/germination. In addition, three of the allele-specific markers developed from the identified STAs were validated across a diverse panel. These markers hold potential for enhancing dormancy in groundnut through marker-assisted selection. Thus, this research offers insights into genetic and molecular mechanisms underlying groundnut seed dormancy in addition to providing markers and donors for breeding future varieties with 2–3 weeks of FSD.
Natural resource rents and sustainable development in MENA Economies: An empirical study
Authors: Abdulraqeb Omar Ahmed , Erbao Cao , Aloqab Abdullah 
Published: October 2024

Abstract

Climate change and its effects around the globe are demanding sustainable development, which encompasses socio-economic development along with taking into account the environmental aspect. The Middle East and North African economies (MENA) possess substantial reserves of natural resources. These natural resources played an important role in the development of this region, and studies are scarce in this regard for this region. Therefore, this study investigates the impact of natural resource rents on sustainable development in MENA. This study used the Sustainable Development Index, which incorporates socio-economic and environmental aspects. Thus, this study is different from other studies in this regard in the MENA region. Additionally, this study also considered other vital factors of sustainable development highlighted in the literature. These factors are renewable energy (REC), non-renewable energy (NREC), and trade openness (TRADE). This is a panel study; thus, a cross-sectional dependence test is carried out, which indicates that second-generation unit root tests have to be used for unit root problems. Likewise, the Westerlund cointegration test is used for examining panel cointegration between variables. Panel autoregressive distributed lagged (PARDL) technique is carried out for long- and short-run effects of explanatory variables on sustainable development. The results indicate that natural resource rents (TNR) have a negative impact on sustainable development, while REC, NREC, and TRADE positively influence sustainable development in the long run.
Analysis of Reattachment Streaks in Hypersonic Shockwave-Boundary Layer Interactions with Upstream Roughness
Authors: Webber Nicholas , Gragston Mark , Ibanez Oscar , Bowersox Rodney D.W. 
Published: October 2024

Abstract

A blunt-nosed ogive-cylinder-flare model was tested in Mach 6 flow at Texas A&M University’s ACE blowdown tunnel with swept Reynolds number and angle-of-attack (AoA). IR thermography and schlieren imaging on the windward side were taken concurrently to determine surface heating distribution and flow structure around the shear layer reattachment onto the flare. The resulting schlieren imaging data showed flow structure having a predominately linear dependence on Re/x for 0◦ AoA and 2◦ AoA and being independent of Re/x for 4◦ AoAand 6◦ AoA. The spanwise periodicity of surface heating streaks associated with surface vortices ranged between 10◦ and 30◦. Bifurcation of the spanwise streaks was observed for nonzero AoA and the coalescing of the bifurcated streaks was observed downstream. At 0◦ and 2◦ AoA, the length and movement of the span-wise streaks are more strongly affected by the changing freestream Re/x than at 4◦ AoA and 6◦ AoA. Additionally, spanwise peak-to-trough surface streak St values varied significantly, with maximum ∆St of 3.3 × 10-3, 6.9 × 10-3,8.7×10-3, and 8.2×10-3 for the 0◦ through 6◦ AoA case respectively, neglecting tunnel startup. Convergence of peak St values is seen beyond Re/x = 5 × 106m-1. A novel correlation is proposed relating freestream and flow conditions with surface heating distribution.
GANFIS: The Ensemble model for Affective Classification
Authors: Kumar Dheeraj , Pandey Subhash Chandra 
Published: October 2024

Abstract

Emotions are a crucial aspect of daily life and play vital roles in human interactions as well as in different other domains such as entertainment, healthcare etc. Perhaps, the use of physiological signals can increase the clarity, objectivity, and reliability of communicating emotions. Therefore, because of these reasons researchers have substantially implemented the idea of using physiological signals to recognize the emotions in recent past. Further, electroencephalography (EEG) is the most popular means of recording brain activity and owing to its diversified applications in variety of domains EEG signals have been widely used to recognize the emotions nowadays. Moreover, EEG signals based emotion recognition techniques are non-invasive in nature and also provides high temporal resolution. However, several crucial attempts have been made by the researchers to recognize the emotions using EEG signals. But, there is still a need for an accurate and effective technique for emotion classification based on EEG signals and undoubtedly, developing a pragmatic and effective algorithm in the pursuit of emotion recognition is a challenging task. This paper proposes an innovative Generative Adversarial Network (GAN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) based hybrid model i.e., 'GANFIS' for EEG signals based emotion recognition. The proposed hybrid model renders a layered structure. The first layer of the model consists of \(\:N\) GANs systems in parallel and further the second layer consists of \(\:N\) ANFIS in parallel where \(\:N\) is equal to the types of emotions to be recognized. The objective of designing of this hybrid model is to enhance the recognition accuracy of the emotions consisting of three and four classes. Perhaps, this is an arduous task for the existing state-of-art techniques. In this proposed hybrid model, the most appropriate distribution for classification are inputted to the first layer i.e., to the GAN structures and subsequently the first layer outputs the extracted features. These extracted features possess the succinct characteristics to recognize the emotions. Further, these extracted features are given as input to the second layer i.e., ANFIS for training. Further, the outputs of the second layer are integrated and thus create the feature vector. These feature vectors are given as input to the third layer that is the adaptive layer. Each layer is properly trained. Furthermore, the third layer outputs the classes of emotions. In addition, the performance of proposed hybrid model is tested and validated on two benchmark datasets. These are: the Feeling Emotion dataset and DEAP dataset. The recognition accuracies obtained from the proposed hybrid model for these datasets are 74.69% and 96.63% respectively. The obtained emotions recognition accuracies superior to accuracies obtained from other state-of-art techniques.
A comparative investigation of changes in the refractive status of children pre- and post-Covid-19 outbreak
Authors: Li Jingjie , Zhang Xiaorui , Chen Ziyi , Xu Chaoyu , Ruan Zengliang , Li Ying 
Published: October 2024

Abstract

Background
Amidst the COVID-19 pandemic, heightened reliance on electronic devices and reduced engagement in outdoor activities among students have contributed to a surge in both the frequency and intensity of myopia. This study aimed to examine changes in students’ refraction status pre- and post-COVID-19 at a school located in Xuzhou, China.
Methods
A prospective cohort study was conducted to evaluate changes in spherical equivalent (SE), astigmatism, and myopia incidence among adolescents aged 5 to 17 years from a school in Tongshan District, Xuzhou City. Vision screenings were carried out for three consecutive years before the COVID-19 outbreak (December 2018 and 2019) and after the outbreak (December 2020). T-tests and analysis of variance were employed to assess alterations in SE and astigmatism pre- versus post-outbreak. Furthermore, comparisons were made between gender and the prevalence of myopia, as well as incidence rates before versus after the epidemic.
Results
The study unveiled an elevation in spherical equivalent (SE) values among children aged 5 to 8 years and those aged 13 to 17 years subsequent to the onset of the COVID-19 pandemic, while SE remained constant among children aged 9 to 12 years. There was a marked increase in astigmatism severity during the pandemic period compared with pre-pandemic levels. Furthermore, there was a substantial surge in myopia incidence rates during COVID-19 within two age brackets (5–8 years old; 13–17 years old) when contrasted with pre-outbreak rates. The development and progression of myopia were determined to be independent of gender.
Conclusions
In the wake of the COVID-19 pandemic, the combination of home isolation measures and online classes has led to an accelerated increase in myopia and astigmatism among adolescents and children, particularly evident within the 5 to 8 age group. This issue demands attention and calls for the implementation of measures to protect visual health among young children.
Single Image Highlight Removal via Innovative Pseudo Image Bases Fusion with a Dual-Network
Authors: PANG Xufang , CHEN Xiansheng , YANG Chao , ZHENG Zhenliang , LIU Shengbo , ZHOU Hongjun , XIA Xuan , JIANG Bo , DING Ning , ZHONG Xiaoping 
Published: October 2024

Abstract

Specular highlights in images can damage or completely obliterate the color and texture details of objects, posing significant challenges to various visual tasks. Traditional highlight removal methods often struggle with handling specular highlights on surfaces with complex textures or rely on stringent and complicated shooting conditions. On the other hand, deep learning-based methods excel at highlight removal on single images with intricate surfaces due to their robust encoding capabilities. However, these methods still face issues with texture distortion in highlight regions. In this paper, we propose a novel method for highlight removal inspired by the observation that specular highlights typically result in increased brightness and decreased saturation. Our method relies on generating pseudo-SV (saturation-value) modulated image bases, effectively constructing a discrete color space that closely approximates the brightness, saturation, and hues of highlight-free pixels. We employ a dual-network architecture, jointly training a highlight detection sub-network and a highlight removal sub-network. By leveraging the generated image bases and highlight positional priors from the highlight detection network, our method enables the highlight removal network to learn the nuances of texture alterations across different highlight levels, thereby producing high-quality highlight-free images via a weighted fusion process. Our experiments demonstrate that our approach effectively restores texture and color details in highlighted regions, significantly outperforming existing methods, as evidenced by superior PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index) scores. To encourage future research and collaboration, we have made our source code publicly available at https://github.com/XufangPANG/Highlight-Removal-based-on-Pesudo-image-bases-fusion.
Reduced-order adaptive synchronization in a chaotic neural network with parameter mismatch: A dynamical system vs. machine learning approach
Authors: Kobiolka Jan , Habermann Jens , Yamakou Marius E. 
Published: October 2024

Abstract

In this paper, we address the reduced-order synchronization problem between two chaotic memristive Hindmarsh-Rose (HR) neurons of different orders using two distinct methods. The first method employs the Lyapunov active control technique. Through this technique, we develop appropriate control functions to synchronize a 4D chaotic HR neuron (response system) with the canonical projection of a 5D chaotic HR neuron (drive system). Numerical simulations are provided to demonstrate the effectiveness of this approach. The second method is data-driven and leverages a machine learning-based control technique. Our technique utilizes an \textit{ad hoc} combination of reservoir computing (RC) algorithms, incorporating reservoir observer (RO), online control (OC), and online predictive control (OPC) algorithms. We anticipate our effective heuristic RC adaptive control algorithm to guide the development of more formally structured and systematic, data-driven RC control approaches to chaotic synchronization problems, and to inspire more data-driven neuromorphic methods for controlling and achieving synchronization in chaotic neural networks \textit{in vivo}.
Assessing complex protein-solvent interactions using environment-controlled crack-growth experiments
Authors: Baumberger Tristan , Ronsin Olivier 
Published: October 2024

Abstract

The modulation of protein functionality, i.e. their ability to fold/unfold, by adding low molecular weight substances to the “natural” solvent water is an important issue in biochemistry. Taking advantage of the unique ability of gelatin to self assemble into elastic networks via partial renaturation of the native collagen protein, we propose to recast the issue into a fracture mechanics one. We describe a method to decipher the effect of alcohols as cosolvents on gelatin networks from the shift of fracture energy in response to an environmental shock. After suitable subtraction of the viscous dissipation we are able characterize the solvent/network interaction by the relative shift of the free energy characteristic of the crosslinked→dismanteled transition of the network associated to its fracture. Using two alcohols, methanol and glycerol, we show that our method is able to accounts for their known contrasting effects on proteins. We briefly discuss the nature of the energy of interaction. In addition we unveil an open issue regarding the origin and consequence of the poroelastic solvent flow associated to crack propagation in hydrogels.