bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physical and Chemical Degradation of Bacterial Cellulose via Rearranging Fibers
Authors: Şahin Fulya , Kayra Neslihan , Aytekin Ali Özhan 
Published: April 2024

Abstract
Bacterial cellulose (BC) has unique properties such as high tensile strength, high crystallinity, and high purity. Fiber length of BC causes different attributes. Therefore, degradation of BC has been studied deeply. In this study, fibers of BC were rearranged via DMAc-LiCl solvent and BC was degraded in wet state. Two different degradation methods, milling with liquid nitrogen and autoclave treatment, were applied. Degraded BCs were characterized by FTIR, TEM, AFM, TGA, and XRD. The solvent helps to align the fibers, making it more crystalline. Degraded BCs had lower crystalline ratio than BC, because of increasing hydrogen bonding during degradation in wet state. Degradation with autoclave made two different degraded BCs as nanofibrils and spherical nanocrystals with no pretreatment and solvent pretreatment, respectively. The nanofibril lengths were between 312 – 700 nm depending on applied method and spherical nanocrystal size was 56 nm. The rearrangement via solvent causes an important difference in degradation of BC. Nanofibrils and nanocrystals can be obtained, depending on the rearrangement of fibers before degradation process.
How Do Environmental Protection Awareness, Attitudes, Behaviors and Pollution Perceptions Affect the Healthiness of Rural Residents: Evidence from the Mountainous Areas of Sichuan, China
Authors: Shui Yue , Yang Yingjie , Liu Shaoquan 
Published: April 2024

Abstract
Purpose - Environmental pollution and health issues are hot topics for discussion in modern society. However, there is a shortage of research on the influence of environmental pollution on health from the perspective of subjective factors such as environmental protection.
Design/methodology/approach - Firstly, the 396 data were collected through a field study in Sichuan Province’s mountainous rural areas. hen, based on the KAP model, an interactive impact mechanism model on the health of rural residents was established. The relationship between background characteristics and environmental protection of rural residents was tested using chi square test and T-test. The impact mechanism of environmental protection awareness, attitude, behavior, and perception of environmental pollution on the health of rural residents was explored through a multiple linear regression model.
Findings – The findings indicate that: (1) All core observation variables can be classified as strong or weak. Stronger environmental awareness is more likely to be found among younger village official with higher educational levels. (2) The health degree of rural residents is significantly affected by their attitude towards environmental protection in a positive way and by environmental protection behavior in a negative way. (3) Age, gender, marital status, and party member, have a significant impact on the health of rural residents.
Originality - The study’s findings can serve as a scientific foundation for enhancing rural residents’ environmental protection and health degree.
Neddylation-related gene signature predicts the prognosis and is associated with immune infiltration of glioma
Authors: Jiang Zhipeng , Yin Wen , Tang Guihua , Guo Youwei , Huang HaiLong , Wang Zihan , Wang Lei , Liu Weidong , Jiang Xingjun , Ren Caiping 
Published: April 2024

Abstract

Background
Glioma is the most prevalent malignant tumor that originates from central nervous system. Neddylation, a post-translational modification similar to ubiquitination, is involved in tumorigenesis and progression. However, there were limited studies focused on the neddylation in glioma. Therefore, we aimed to explore the potential role of neddylation in glioma.
Methods
In this study, neddylation-related genes (NRGs) were identified and were used to construct a prognostic signature for glioma patients. Based on this prognostic index, we also explored the differences in clinical features, mutational landscape, immune cell infiltration between high-risk and low-risk groups. Next, single-cell RNA sequencing analysis was further performed to verify the expression of these genes in NRG signature. At last, one gene selected from the NRG signature were validated by in vitro experiments.
Results
Seven genes (TOP2A, F2R, UST, HSPA1B, LGALS3BP, UROS, and OSBPL11) were identified to construct the NRG signature, which was able to successfully classify glioma patients into high-risk and low-risk groups. A nomogram based on the NRG signature and other prognostic factors were developed to accurately predict the prognosis of glioma. Significant differences in prognosis, mutational landscape, immune cell infiltration were found between distinct groups. Moreover, in vitro experiments illustrated that knockdown of HSPA1B could inhibit the proliferation, migration, and invasion of glioma cells and also inhibit the polarization of M2 macrophages.
Conclusion
These findings provide new insights into understanding the relationship between NRGs and glioma development and identify novel biomarkers may help to guiding precise treatments to glioma.
Research case study of the Discovery Museum and Tyne &amp; Wear Archives in Newcastle-Upon-Tyne (United Kingdom).
Authors: Hui Yann , Mak Michael 
Published: April 2024

Abstract
The Discovery Museum [(built in 1899, Grade II listed) (Science & Technology Museum category)] underwent a major renovation (2004 completion), with the addition of the Tyne & Wear Archives (2008 completion) situated within the museum’s basement level. The Discovery Museum and the Tyne & Wear Archives project (Atkins, 2023) is re-visited as a research case study, via the conceptual framework lens of International Council of Museum’s (ICOM) & Organisation for Economic Co-operation & Development’s (OECD) “Culture and Local Development: Maximising the Impact (ICOM & OECD, 2019)” guide for local governments, communities and museums and the “Management of Archive & Museum Collections” lecture series (Alici, 2023). The research paper seeks to question the functional and social role of the museum within society and it’s constantly evolving identity and image, for example Cole’s vision of “museums as a schoolroom for everyone” (Hallemann, 2019). A new metaphor for the Discovery Museum’s near future vision [post COVID-19 pandemic era] will be provided within the conclusion of the paper.
Photobacterium mangrovi sp. nov., isolated from mud sediment
Authors: Jiang Wanli , Shan Dapeng , Li Xu , Li Guangyu , Shao Zongze 
Published: April 2024

Abstract
A Gram-stain-negative, facultative anaerobic, rod-shaped strain, named S-FG-1T, was isolated from mud sediment samples collected from mangroves in Zinian Town. The novel strains, S-FG-1T, was abled to grow at 0.5–7% NaCl (optimum, 0.5–2%), 10–42°C (optimum, 28°C) and pH 6–8 (optimum, pH 6). Phylogenetic analysis based on the 16S rRNA gene sequence indicated that strain S-FG-1T was a member of the genus Photobacterium with high similarity to Photobacterium ganghwense FR 1311T (97.91%), Photobacterium arenosum CAU 1568T (97.09%) and Photobacterium atrarenae M3-4T (96.18%). The polar lipids consisted of phosphatidylethanolamine, phosphatidylglycerol and aminophospholipid. The major respiratory quinone was ubiquinone-8. The predominant cellular fatty acids were summed feature 3 (C16:1ω7c/16:1ω6c) and summed feature 8 (C18:1ω5c/18:0). The whole genome size of strain S-FG-1T was 5.04Mb with 53.6mol% G + C content.These taxonomic data support S-FG-1T as representing a novel Photobacterium species, for which the name Photobacterium mangrovi sp. nov. is proposed. The type strain of this novel species is S-FG-1T (= KCTC 8388T = MCCC 1A19761T ).
Marathi Sign Language Recognition using MediaPipe and Deep Learning Algorithm
Authors: Giri Shraddha , Patil Ashwini 
Published: April 2024

Abstract
Sign language is the hand gesture-based manual way of communication for mute and deaf people. The majorityof other people do not know this sign language, so it creates isolation among physically disabled people. The majority of research is already done for sign language recognition using machine and deep learning techniques for the English language. The attention needs to focus on regional sign language recognition as some of the signs vary according to region. We have considered the regional language, i.e., Marathi, for our recognition work.
In this paper, we proposed the real-time method for hand gesture detection for sign language recognition using the Media Pipe along with a long short-term memory (LSTM) neural network model for the recognition of Marathi sign language. The system is built for the automatic recognition of Marathi sign language. The implemented model is trained and tested over our own dataset designed for 15 different Marathi words that are used in day-to-day communication by physically disabled people. The dataset contains a total of 37500 frames. With 97.50% accuracy, we can successfully recognize Marathi sign language.
Clinical significance of zoledronic acid in combination with calcium tablets and calcitriol for hip biomechanics and bone mineral density after total hip replacement: a prospective randomized controlled trial
Authors: 徐 贞东 , 杜 庄 , 里 清 , 王 辛 , 王 紫 , 邵 华 , 胡 宇通 , 刘 莫真 
Published: April 2024

Abstract

Purpose: To investigate the effects of zoledronic acid (ZA) combined with calcium tablets and calcitriol on bone mineral density (BMD), hip function after total hip arthroplasty (THA).
Methods: 50 elderly patients with THA from January 2022 to December 2022 were included in this study. The ZA group was given ZA combined with calcium tablets and calcitriol, while the control group was only given calcium tablets and calcitriol. The preoperative and postoperative BMD, bone metabolism-related indexes, Harris score, incidence of prosthesis loosening and hip biomechanics between the two groups were compared.
Results: There were no significant differences in age, sex, Body Mass Index. Postoperative systemic BMD and periprosthetic BMDin ZA group were higher than those in the control group. The BMD in Gruen zones 1, 6 and 7 at postoperative 6 months, Gruen zones 1, 2, 4, 6 and 7 at postoperative 1 year was significantly higher than that in the control group. Postoperative 1 year, the 25-hydroxyvitamin D, procollagen 1 intact N-terminal and Harris score in ZA group were higher than those in control group, the β-type Ⅰ collagen carboxy-terminal peptide was lower. Acetabular height and acetabular deviation in ZA group were significantly better than those in control group at postoperative 1 year. Only 2 cases of prosthesis loosening in control group.
Conclusion: ZA can effectively restore the loss of BMD, maintain the biomechanical stability of the hip, and reduce the incidence of prosthesis loosening. It is an effective method to prevent osteoporosis after THA.
Trial registration: This study has been registered in the Chinese Clinical Registry (registration No.: ChiCTR2200065144, date: January 2022)
A single cell RNA sequence atlas of the early Drosophila larval eye
Authors: Raja Komal Kumar Bollepogu , Yeung Kelvin , Li Yumei , Chen Rui , Mardon Graeme 
Published: April 2024

Abstract

The Drosophila eye has been an important model to understand principles of differentiation, proliferation, apoptosis and tissue morphogenesis. However, a single cell RNA sequence resource that captures gene expression dynamics from the initiation of differentiation to the specification of different cell types in the larval eye disc is lacking. Here, we report transcriptomic data from 13,000 cells that cover six developmental stages of the larval eye. Our data show cell clusters that correspond to all major cell types present in the eye disc ranging from the initiation of the morphogenetic furrow to the differentiation of each photoreceptor cell type as well as early cone cells. We identify dozens of cell type-specific genes whose function in different aspects of eye development have not been reported. These single cell data will greatly aid research groups studying different aspects of early eye development and will facilitate a deeper understanding of the larval eye as a model system.
Hybrid Firefly and Particle Swarm Optimization Designed for Xgboosttuning Problem: Intrusion Detection in Network
Authors: Mensah Paul 
Published: April 2024

Abstract

The growing of threads and intrusions on networks make the need for developing efficient and effective intrusion detection systems a necessity. Powerful solutions of intrusion detection systems should be capable of dealing with central network issues such as huge data, high-speed traffic, and wide variety in threat types. This paper proposes a feature selection method that is based on firefly algorithm, particle swarm optimization and xgboost. The proposed method improves the performance of intrusion detection by removing the irrelevant features and reduces the time of classification by reducing the dimension of data. The XGBoost model was employed to evaluate each of the feature subsets produced from firefly and particle swarm optimization technique. The main merit of the proposed method is its ability in modifying the firefly algorithm and particle swarm optimization to become suitable for selection of features. To validate the proposed approach, the popular NSL-KDD dataset was used in addition to the common measures of intrusion detection systems such as overall accuracy, detection rate, and false alarm rate. The proposed method achieved an overall accuracy of 78.89
Multidisciplinary treatment for severe torsion of anterior teeth : a case report
Authors: Tang Qianwei , Chen Wenjin , Zhao Jingjing , Chen Shuolin , Huang Hua , Qin Xiurong 
Published: April 2024

Abstract
Maxillary permanent incisor torsion caused by supernumerary teeth is not frequently encountered in dental practice, but its treatment is challenging because of its importance for facial esthetics and the complexity of treatment. Timely intervention is often required to avoid severe complications. This article presents the case of a 7-year-old male patient with severe torsion of anterior teeth in mixed dentition. Multidisciplinary treatment was proposed to meet the patient’s needs, involving extracting the supernumerary teeth, using an intra-maxillary casting distractor and the 2×4 fixed orthodontic technique to align the severely twisted anterior teeth, and employing a Hawley retainer during the day and a customized silicone guide at night to maintain and guide occlusal development. At the end of treatment, the patient attained molar and canine class I with normal overjet and overbite. The combination of an intra-maxillary casting distractor and the 2×4 fixed orthodontic technique is very effective for treating severe torsion of upper anterior teeth if the patient is cooperative with using a retainer to prevent recurrence.
Conditional Generative Adversarial Networks for Subsurface Modeling: How Good They Really Are?
Authors: Merzoug Ahmed , Pyrcz Michael 
Published: April 2024

Abstract
Generative adversarial networks (GANs) are increasingly recognized for their potential in subsurface modeling and uncertainty quantification, thanks to their capability to learn complex geological patterns from spatial training images and their ability to perform rapid local data conditioning in a lower-dimensional latent space compared to the full-dimensional space of the images. However, the performance of these algorithms often receives acceptance based primarily on visual inspection or limited qualitative assessment. To address this, we propose a minimum acceptance criteria workflow designed to quantitatively assess and verify the adequacy of GAN-generated subsurface models. This evaluation is carried out through three key metrics: (1) reproduction of data distribution, (2) reproduction of spatial continuity, and (3) local data conditioning. Our proposed workflow applied to GANs trained on a variety of images from sequential Gaussian simulations demonstrates that while data distribution and spatial continuity are consistently well-reproduced, local data conditioning faces several challenges. These include increasing prediction error and the need for more iterations for conditioning as the number of conditioning data increases. Additionally, the conditioning process at these data locations tends to introduce artifacts near the data locations including high local variogram nugget effects. Our minimum acceptance criteria offer a comprehensive framework for evaluating various models ensuring a higher control on modeling quality acceptance and rejection.
Tolvaptan use in a patient with TSC2 - PKD1 contiguous gene deletion syndrome – a case report
Authors: Iyasere Osasuyi , Jinadu Yusuf , Craft Emily 
Published: April 2024

Abstract
The TSC2 gene is contiguous to the PKD1 gene on chromosome 16. A large deletion in this region is associated with a clinical phenotype involving features of tuberous sclerosis and polycystic kidney disease (TSC-PKD CGD). While Tolvaptan use in patients with autosomal dominant polycystic kidney disease is well established, it is less so in those TSC-PKD CGD syndrome. Here, we report a case of Tolvaptan use in a 23 year old woman diagnosed with TSC - PKD CGD using micro-array testing. She had a known diagnosis of tuberous sclerosis, but renal imaging had shown enlarged polycystic kidneys and no angiomyolipomas. Following a rapid decline in kidney function, micro-array testing was arranged, which confirmed a large deletion involving the TSC2 and PKD 1 genes respectively. She was subsequently commenced on Tolvaptan therapy, which has been well tolerated, without significant side effects. After 12 months of therapy, the rate of decline in kidney function is slower in comparison to the pre-Tolvaptan phase.
Geospatial Variability of Vegetation Response to Meteorological Drought in North-East and North-West Nigeria
Authors: Oyemitan Suraju Oluwanifemi 
Published: April 2024

Abstract
This research investigated extreme drought variability and future trends in North-East and North-West Nigeria, addressing essential questions regarding the temporal and spatial variations in rainy and dry seasons. Daily and Monthly observation datasets at (0.50 x 0.50) resolution was obtained from the global gridded climatology of Climate Research covering 1981 to 2019. Simulated daily datasets from the Rossby Centre for Atmospheric Regional Climate Model (RCA4-RCM) under two emission scenarios (RCP4.5 and RCP8.5) for the periods 1976-2005 (historical) and 2020-2100 (projection) were retrieved from CORDEX at a resolution of (0.440 x 0.440) over Africa. The Standardized Precipitation Evaporation Index (SPEI) assessed drought intensities, revealing near normal, moderate, and severe conditions within the range of 1.99 to -1.99. A linear regression model established the relationship between Normalized Difference Vegetation Index (NDVI) and rainfall. Spatial analysis of Consecutive dry days (Drought Index) over three 30-year periods (near, mid, and far future) set a critical/threshold level at -0.4 to 1.2, unveiling distinctive drought severity patterns. Findings highlighted regions with low vulnerability (Bornu, Kano, Katsina) and high risk (Bauchi, Zamfara, Yobe) during the historical period. Projected trends indicated fewer consecutive dry days between 2020 and 2040 under RCP 4.5 and RCP 8.5, with greater emissions and warming in RCP 8.5 leading to increased dry days between 2041 and 2070. The mid-century outlook suggests a rise in dry days, signalling prolonged drought in the region. SPEI analysis revealed potential future aridity in Northern Nigeria due to rising Potential Evaporation (PET) and continuous Climatic Water Balance (CWB) deficits observed over West Africa, leading to increased evaporation losses and higher irrigation demands for drier soils.
Flux Density Distribution Forecasting in Concentrated Solar Tower Plants: A Data-Driven Approach
Authors: Kuhl Mathias , Pargmann Max , Cherti Mehdi , Jitsev Jenia , Quinto Daniel Maldonado , Pitz-Paal Robert 
Published: April 2024

Abstract
Concentrated Solar Power (CSP) systems, particularly those employing heliostat fields combined with a central tower, demonstrate substantial capacity for producing dispatchable, sustainable energy and fuel. This is achieved by focusing the sunlight with up to thousands of individual heliostats onto a single receiver. Forecasting the focal spot of each heliostat at any solar position becomes imperative to ensure optimal control. Nevertheless, the existing cutting-edge techniques aimed at predicting this flux density distribution either suffer from inaccuracies or entail substantial costs. In response to these challenges, our study introduces a novel approach involving a generative model that learns the shape and intensity patterns of the focal spots directly from images captured of the calibration target. We developed a purely data-driven methodology to generate the focal spots of the heliostats corresponding to various sun positions. The model is based on the StyleGAN architecture with adapted learnable input vectors for each individual heliostat and sun positions as input condition. The methodology’s effectiveness is demonstrated through training and evaluation on data collected from a research power plant, where it achieved a flux prediction accuracy of 89% on the calibration target surface. Our work offers a novel solution for predicting flux density distributions in solar power plants in a fully data-driven way with a neural network. Notably, this method achieves cost efficiency by utilizing data obtained during standard operational procedures. Impressively, this method attains accuracy levels comparable to or exceeding those of current state-of-the-art techniques.
Selective Photocatalytic Conversion of CO2 to Formate by Dimeric Cu(II) Complexes
Authors: Kim Jinheung 
Published: April 2024

Abstract

Efficient and selective molecular catalysts for visible-light-driven CO2 conversion to liquid or solid fuels are highly desired to achieve carbon neutralization. Although catalysts utilizing earth-abundant metals have shown some progress for CO and formate production, their conversion efficiency and product selectivity are still quite lacking for practical applications. In this study, we report binuclear Cu complexes of bridging ligands containing two pyridyltriazole units developed during the study of the active sites of related metalloenzymes. Surprisingly, the dimeric complexes with a flexible cavity between two coppers exhibit high activity in catalytic CO2 reduction, converting CO2 to formate with high selectivity and efficiency under visible light irradiation. The turnover number and formate selectivity were 43000 and >99%, respectively. The results of the study suggest that a deep understanding of the effect of the ligand environment and structural factors of metal compounds on catalytic activity when used as a catalyst will be helpful.