bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Science Student Electronic Exit Ticket (SEET) System
Authors: Raza Ali , Sumner Tamara , Penuel William R. 
Published: March 2024

This study examined the ways in which an equity analytics tool — the SEET system — supported middle school science teachers’ reflections on the experiences of diverse students in their classrooms. The tool provides teachers with “equity visualizations” — disaggregated classroom data by gender and race — designed to support teachers to notice and reflect on inequitable patterns in student participation in classroom knowledge-building activities, as well as “whole class visualizations” that enable teachers to look at participation patterns. The visualizations were based on survey data collected from students reflecting on the day’s lessons, responding to questions aligned with three theoretical constructs indicative of equitable participation in science classrooms: coherence, relevance, and contribution. The study involved 42 teachers, divided into two cohorts, participating in a two-month professional learning series. Diary studies and semi-structured interviews were used to probe teachers’ perceptions of the visualizations’ usability, usefulness, and utility for supporting their reflections on student experiences and instructional practices. A key result is that only the “equity visualizations” prompted teacher reflections on diverse student experiences. However, despite the support equity visualizations provided for this core task, the teachers consistently ranked the whole class visualizations as more usable and useful.
Isolation and Characterization of Enterobacter sp Capable towards Tolerating Degradation Products and Fermenting Pentoses
Authors: Ouahbi Karim El , Asli Abdelghani El , Benlemlih Mohammed 
Published: March 2024

<p>The depletion of fossil fuel resources, in addition to the growing demand for energy, has prompted the development of renewable energies, including bioethanol from lignocellulosic biomass. The acid pretreatment of hemicellulose releases inhibiting compounds in addition to xylose. With the possibility of exploitation of lignocellulose as a fermentation substrate, we isolated an <em>Enterobacter </em>characterized by its ability to ferment xylose and tolerate high concentrations of inhibitors. The selection was performed in media containing different carbon and energy sources; glucose, cellobiose, CMC, furfural and 5-HMF. Characterization strategies of the selected strain such as, xylose concentration (from 25 g liter-1 to 100 g liter-1), furfural (0 mM to 25 mM), cell immobilization, were used to quantify the maximum yield of ethanol produced. The results obtained show that our strain can ferment up to 100 g liter-1 of xylose in the presence of 20 mM furfural at 37°C to produce ethanol with a maximum yield of 2.22 g liter- 1 for 24 h under 160 rpm magnetic stirring. The results obtained in this study suggest that the isolated <em>Enterobacter </em>sp. is a promising strain for the bioconversion of lignocellulosic biomass pretreatment hydrolysate into bioethanol.</p><p> </p>
Harnessing GPT for Efficient Review of Research and Development Publications
Authors: Grokhowsky Nicholas 
Published: March 2024

Abstract
GPT, or Generative Pre-trained Transformer, revolutionizes the efficiency of reviewing research and development (R&D) publications by leveraging its natural language processing capabilities. Traditional methods of literature review are time-consuming and labor-intensive, often requiring researchers to sift through vast amounts of text to extract relevant information. GPT streamlines this process through its ability to comprehend, analyze, and summarize text swiftly.

Firstly, GPT can quickly scan through a plethora of publications, identifying key concepts, methodologies, and findings. Its advanced language understanding enables it to grasp complex scientific language and extract essential information accurately. This rapid processing significantly reduces the time researchers spend on manual literature review.

Secondly, GPT generates concise summaries of research articles, condensing lengthy texts into digestible snippets without sacrificing critical details. These summaries offer researchers a quick overview of the content, allowing them to prioritize articles based on relevance to their own work.

Moreover, GPT can assist in identifying connections between different studies and trends within a particular field. By analyzing large volumes of literature, it can detect patterns, emerging topics, and gaps in knowledge, guiding researchers towards fruitful areas for further investigation.

Additionally, GPT can aid in writing literature reviews by suggesting structured outlines and integrating relevant information seamlessly. This not only saves time but also enhances the quality and coherence of the review.
Overall, GPT's ability to expedite the process of reviewing R&D publications is invaluable in accelerating the pace of scientific discovery and innovation. By automating tedious tasks and providing insightful analyses, GPT empowers researchers to focus their efforts on advancing knowledge and solving pressing challenges.
Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal
Authors: Ram Ashok Kumar , Lamichhane Babu Ram , Subedi Naresh , Yadav Nabin Kumar , Karki Ajay , Pandav Bivash , Brown Cory , Khatri Top B. , Yackulic Charles B. 
Published: March 2024

Abstract

Large mammals with general habitat needs can persist throughout mixed used landscapes, however, increasing human threats often restrict them to protected areas. Conservation efforts, especially for reducing conflicts with humans, can enhance tolerance of species like Asian elephants (Elephas maximus) in human-dominated landscapes. Here, we examine how elephant use of the Chure Terai Madhesh Landscape (CTML) covering the entire elephant range of Nepal changed between 2012 and 2020. We systematically surveyed ~ 42,000 km2of potential habitat, by dividing the study area into 159 grid cells of 15x15 km2and recording elephant signs during the cool dry season in three years (2012, 2018 and 2020). We analyzed the survey data in a single-species multi season (dynamic) occupancy modeling framework to test hypotheses regarding the influence of environmental and management conditions in landscape use by elephants over time. The best-supported model included protected area effects on initial use, colonization, and detection probability as well as temporal variation in colonization and detection probability. Initial use and colonization rates were higher in protected areas, however elephants increasingly used both protected areas and outside protected areas, and the difference in use between protected areas and outside protected areas declined as elephants use became prevalent across most of the landscape. While elephants were patchily distributed in the first year of surveys consistent with past descriptions of four sub-populations, elephant use consolidated into a western and eastern region in subsequent years suggesting two sub-populations. The only gap in their distribution occurs in the area west of Chitwan National Park and east of Banke National Park. Increasing elephant use outside protected areas may cause higher human-elephant conflicts. Management interventions that focus on reducing conflicts can promote human-elephant co-existence in the landscape.
UGT1A7 altered HER2-positive breast cancer response to trastuzumab by affecting epithelial-to-mesenchymal transition: A potential biomarker to identify patients resistant to trastuzumab treatment.
Authors: Yuan Yuan , Wang Cong , Bai Chenguang , Zhang Zhe , Zhou Hao , Gao Huanyao , Wang Siwei 
Published: March 2024

Abstract

Background: HER2-positive (HER2+) breast cancer accounts for 20–30% of all breast cancers. Although trastuzumab has significantly improved the survival of patients with HER2+ breast cancer, more than 70% of patients develop drug resistance within one year of treatment. Understanding the molecular mechanisms of trastuzumab resistance and identifying biomarkers that predict early trastuzumab resistance would greatly benefit patients receiving trastuzumab therapy.
Methods: Differential-gene-expression analysis of trastuzumab-sensitive and resistant HER2+ breast cancer cell lines from GSE15043 was performed to identify the biomarkers associated with trastuzumab resistance. Differential biomarker expression was confirmed in FFPE tissues collected from clinical HER2+ breast cancer tumor samples that were sensitive or resistant to trastuzumab treatment. The function of the biomarkers associated with trastuzumab resistance was studied using western blotting, immunofluorescence, electron microscopy, and siRNA knockdown and overexpression to elucidate the role and mechanisms of the biomarker in affecting the trastuzumab response.
Results: UGT1A7, a member of the uronic acid transferase family, was associated with trastuzumab resistance. UGT1A7 expression was downregulated in trastuzumab-resistant tumor tissues and in a cell line that developed trastuzumab resistance (BT474TR). Overexpressing UGT1A7 in BT474TR restored their sensitivity to trastuzumab treatment, whereas downregulating UGT1A7 expression in parental cells led to trastuzumab resistance. Importantly, UGT1A7 localized to the endoplasmic reticulum and altered stress responses. Furthermore, downregulating UGT1A7 expression promoted epithelial-to-mesenchymal transition (EMT) by affecting TWIST, SNAIL, and GRP78 expression and the AMP-activated protein kinase signaling pathway, thus contributing to trastuzumab resistance.
Conclusions:
This study demonstrated the important role and novel mechanisms of UGT1A7 in tumor responses to trastuzumab. Low UGT1A7 expression plays an important role in EMT and contributes to trastuzumab resistance. UGT1A7 has the potential to be developed as a biomarker for identifying patients who are resistant to trastuzumab treatment.
Unravelling the Cell-Penetrating Potential of Endogenous Opioid Neuropeptide Dynorphin A through Computational Dissection of Membrane Disruption Principles
Authors: Peralvarez-Marin Alex , Catalina-Hernandez Eric , Lopez-Martin Mario , Aguilella-Arzo Marcel 
Published: March 2024

Abstract

Dynorphins are endogenous neuropeptides that function as opioids. In addition to opioid activity, dynorphins can induce several pathological effects such as neurological dysfunctions and cell death. Previous studies have suggested that Dynorphin A (DynA) and its clinical variants (L5S, R6W, and R9C) mediate some pathogenic actions through formation of transient pores in lipid domains of the plasma membrane. Here, we use a combination of steered and conventional molecular dynamics simulations to evaluate the ability of DynA and its variants to disturb lipid membranes in comparison to well established cell-penetrating peptides to determine how these peptides interact and permeate model lipid bilayers. We show that in our setup DynA and its variants (except for R9C) exhibit a strong membrane disturbing potential that may lead to translocation through the formation of water pores, which is likely prevented in cholesterol containing bilayers for R6W. When cholesterol and negative charge in the bilayers are present, the membrane disruption potential of DynA and its variants is minimal, but the hydrophobic-to-polar substitution in L5S favors peptide translocation. Altogether, these results show the importance of out-of-the-box computational studies to design membrane disruptive peptides to exploit their cell-penetrating and antimicrobial capabilities.
Ascent and attachment in pea plants: a matter of iteration
Authors: Guerra Silvia , Bruno Giovanni , Spoto Andrea , Panzeri Anna , Wang Qiuran , Bonato Bianca , Simonetti Valentina , Bulgheroni Maria , Castiello Umberto 
Published: March 2024

Abstract
Pea plants (Pisum sativum L.) can sense the presence of potential supports in the environment and flexibly adapt their behavior to clasp it. How pea plants control and perfect this behavior during growth remains unexplored. Here, we attempt to fill this gap by studying the movement of the apex and the tendrils at different leaves using three–dimensional (3D) kinematical analysis. We hypothesized that plants accumulate information and resources through the circumnutation movements of each leaf. Information generates the kinematical coordinates for the final launch towards the potential support. Results suggest that developing a functional approach to grasp movement may involve an interactive trial and error process based on continuous cross–talk across leaves. This internal communication provides evidence that plants adopt plastic responses in a way that optimally corresponds to support search scenarios.
A Comprehensive Investigation of Glycoprotein-based Nucleic Acid Vaccines for Hantaan Virus
Authors: yang kun , zhang Jiaxing , Zhang Junqi , Wang Yanbo , Sun Yubo , Wang Yongkai , Wang Yueyue , Yang Duan , Qiao Xupeng , Liu Xiaoqian , Ding Jiaqi , Zhang Xiyang , Zhang Wenbiao , Wang Zhenjie , Hu Chenchen , Han Chenying , Liu Tianyue , Yang Shuya , Sun Yuanjie , Cheng Linfeng , Jiang Dongbo 
Published: March 2024

Abstract

Hemorrhagic fever with renal syndrome (HFRS) occurs throughout Eurasia with considerable morbidity and mortality. Currently, the absence of specific treatments or effective antiviral drugs for hantavirus infection makes developing safe and effective vaccines a high priority. Here, we report the development of three novel nucleic acid vaccine candidates, mRNA, DNA, and DNA encapsulated in lipid nanoparticles, encoding the glycoproteins of the Hantaan virus (HTNV). To comprehensively evaluate the potential of candidate HTNV nucleic acid vaccines in preventing HFRS, we focus on evaluating their immunogenicity and efficacy in mice and comparing them with an inactivated vaccine as the benchmark. Our findings reveal that all candidate vaccines activated instant and sustained immune responses, offering effective in vivo protection. Notably, the nucleic acid vaccines demonstrated distinct advantages over the inactivated vaccine, in both humoral and cellular immunity. These results mark a significant step in developing nucleic acid vaccines for HTNV, suggesting that sequential immunization with DNA and mRNA vaccines could further amplify the advantages of nucleic acid vaccines.
Effective spin-1 breathing kagome Hamiltonian induced by the exchange hierarchy in the maple leaf mineral bluebellite
Authors: Ghosh Pratyay , Müller Tobias , Iqbal Yasir , Thomale Ronny , Jeschke Harald 
Published: March 2024

Abstract

The Heisenberg quantum antiferromagnet on the maple leaf lattice has been shown to feature highly exotic phases and thus material realizations are intensely sought after. We determine the magnetic Hamiltonian of the copper mineral bluebellite using density functional theory based energy mapping. Due to significant distortion of the spin-1/2 maple leaf lattice, we find two of the five dis tinct nearest-neighbor couplings to be ferromagnetic. The solution of this Hamiltonian with density matrix renormalization group calculations points us to the surprising insight that this particular imperfect maple leaf lattice, due to the strongly ferromagnetic Cu2+dimer, realizes an effective S = 1 breathing kagome Hamiltonian. In fact, this is another highly interesting Hamiltonian that has rarely been realized in materials. Analysis of the effective model within a bond-operator for malism then allows us to identify a valence bond solid ground state and extract thermodynamic quantities using a low-energy bosonic mean-field theory. We resolve the puzzle of the apparent one dimensional character of bluebellite as our calculated specific heat has a Bonner-Fisher-like shape, in good agreement with the experiment.
RNA-seq reveals the gene expression in patterns in Populus × euramericana 'Neva' plantation forests under different precision water and fertilizer-intensive management
Authors: Wang Zhou , Zhang Weixi , Ding Changjun , Xia Yongxiu , Yuan Zhengsai , Guo Jiangtao , Yu Jinjin , Zhang Bingyu , Su Xiaohua 
Published: March 2024

Abstract

Background: Populus spp. is a crucial fast-growing and productive tree species extensively cultivated in the mid-latitude plains of the world. However, the impact of intensive cultivation management on gene expression in plantation forestry remains largely unexplored.
Results: Precision water and fertilizer-intensive management substantially increased key enzyme activities of nitrogen transport, assimilation, and photosynthesis (1.12–2.63 times than CK) in Populus × euramericana 'Neva' plantation. Meanwhile, this management approach had a significant regulatory effect on the gene expression of poplar plantations. 1554 differential expression genes (DEGs)were identified in drip irrigation (ND) compared with conventional irrigation. Relative to ND, 2761–4116 DEGs, predominantly up-regulated, were identified under three drip fertilization combinations, among which 202 DEGs were mainly regulated by fertilization. Moreover, drip irrigation reduced the expression of cell wall synthesis-related genes to reduce unnecessary water transport. Precision drip and fertilizer management promotes the synergistic regulation of carbon and nitrogen metabolism and up-regulates the expression of major genes in nitrogen transport and assimilation processes (5 DEGs), photosynthesis (15 DEGs), and plant hormone signal transduction (11 DEGs). The incorporation of trace elements further enhanced the up-regulation of secondary metabolic process genes. In addition, the co-expression network identified nine hub genes regulated by precision water and fertilizer management, suggesting a pivotal role in regulating the growth of poplar.
Conclusion: Precision water and fertilizer-intensive management demonstrated the ability to regulate the expression of key genes and transcription factor genes involved in carbon and nitrogen metabolism pathways, plant hormone signal transduction, and enhance the activity of key enzymes involved in related processes. This regulation facilitated nitrogen absorption and utilization, and photosynthetic abilities such as light capture, light transport, and electron transport, which faintly synergistically regulate the growth of poplar plantations. These results provide a reference for proposing highly efficient precision intensive management to optimize the expression of target genes.
A generalized fractional hepatitis B virus infection modelwith both cell-to-cell and virus-to-cell transmissions
Authors: Yaagoub Zakaria , Sadki Marya , Allali Karam 
Published: March 2024

Abstract
In this paper, we suggest a generalized fractional hepatitis B viral infection model with twomodes of transmission that are cell-to-cell and virus-to-cell. These two modes of transmissionwill be represented by two generalized incidence functions. We take into account the humanbody adaptive immunity, that is represented by antibody and cytotoxic T-lymphocyte immuneresponses. We begin the study of this model by giving some theorems concerning the existence,positivity and boundness of the model solutions. We have shown that the model has a free-disease equilibrium point and other four endemic steady states. We give the relationship betweenthe existence of these steady states and their corresponding reproductive numbers. By usingthe Lyapunov method and LaSalle's invariance principle, we have shown the different theoremsof global stability to the problem steady states. Some numerical simulations are presented inorder to confirm our theoretical fndings about the stability of steady states and to show the effectiveness of fractional derivative order on the stability of all equilibria. We observe that thechoice of generalized incidence functions can provide a clearer understanding of the stability of equilibria and can incorporate a wide range of classical incidence functions. Finally, good infectiontreatment helps considerably to irradiate the infection.
CleftGAN: Adapting A Style-Based Generative Adversarial Network To Create Images Depicting Cleft Lip Deformity
Authors: Hayajneh Abdullah , Serpedin Erchin , Shaqfeh Mohammad , Glass Graeme , Stotland Mitchell A. 
Published: March 2024

Abstract

Background
Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. We have built a deep learning-based cleft lip generator called CleftGAN designed to produce an almost unlimited number of high-fidelity facsimiles of cleft lip facial images with wide variation.
Methods
A transfer learning protocol testing different versions of StyleGAN as the base model was undertaken. Data augmentation maneuvers permitted input of merely 514 frontal photographs of cleft-affected faces adapted to a base model of 70,000 normal faces. The Frechet Inception Distance was used to measure the similarity of the newly generated facial images to the cleft training dataset. Perceptual Path Length and the novel Divergence Index of Normality measures also assessed the performance of the novel image generator.
Results
CleftGAN generates vast numbers of unique faces depicting a wide range of cleft lip deformity with variation of ethnic background. Performance metrics demonstrated a high similarity of the generated images to our training dataset and a smooth, semantically valid interpolation of images through the transfer learning process. The distribution of normality for the training and generated images were highly comparable.
Conclusions
CleftGAN is a novel instrument that generates an almost boundless number of realistic facial images depicting cleft lip. This tool promises to become a valuable resource for the development of machine learning models to objectively evaluate facial form and the outcomes of surgical reconstruction.
Fabric Soft Pneumatic Actuators with Programmable Turing Pattern Textures
Authors: TANAKA MASATO , Song Yuyang , Nomura Tsuyoshi 
Published: March 2024

Abstract

Turing patterns, a concept derived from Alan Turing's work on morphogenesis and patterns, can be found in nature at multiple spatial scales, such as lizard skin, fish skins, and sand dunes. Readers might also find the application of Turing pattern used into textile industry, where an element of uniqueness and artistic expression is preferred for the user experience. However, commercially available Turing patterns from this industry do not yet demonstrate advanced functionality. This research introduces a fabric based soft pneumatic actuators (FSPAs) based on textile material from advanced computational design and fabrication method, where different actuation motion of FSPAs are achieved driving by programmable Turing patterns. The proposed method designs and fine-tunes the geometric pattern of a reinforcement sheet embedded into a stretchable, unstructured fabric. In this study, this embedding is achieved through two techniques: heat bonding and embroidery. Through these approaches, the local deformation of the surface membrane can be precisely programmed, allowing for controlled global shaping of the inflatable structure. By leveraging commonly used fabrication methods in the fashion industry, the shape-morphing inflatable structure can be realized using lightweight fabric materials on a large scale. These techniques are anticipated to impact the design and fabrication of shape-morphing inflatable structures for future applications, such as architectural arches or emergency shelters, in an easy and cost-effective manner.