bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification of Ice Crystal Habits by Deep Transfer Learning
Authors: Xu Yefeng , Jiao Ruili , Huang Minsong 
Published: December 2023

Abstract
Ice crystal particle shape is an important factor affecting cloud microphysical processes. Accurately identifying the shapes of ice crystal particle within clouds is a fundamental requirement for calculating various cloud microphysical parameters. In this study, we set up an ice crystal image dataset, encompassing nine distinct habit categories with 8100 images. These images were captured using three probes with varying resolutions: the Cloud Particle Imager (CPI), the Two-dimensional Stereo Probe (2D-S), and the High Volume Precipitation Spectrometer (HVPS). In addition, we introduce a deep convolutional neural network (CNN) based on transfer learning for ice crystal particle shape classification model, TL-AlexNet, which demonstrates the capability to simultaneously classify ice crystal particle habits observed by both the Line Scan Imager and the Area Scan Imager. The results indicate that the TL-AlexNet model could achieve superior performance in ice crystal shapes classification for two types of imagers, and the classification with the accuracy of 97.16%. It is much higher than the traditional shape recognition methods, and has certain application value for Climate and cloud microphysics research.
scSemiProfiler: Advancing Large-scale Single-cell Studies through Semi-profiling with Deep Generative Models and Active Learning
Authors: Ding Jun , Wang Jingtao , Fonseca Gregory 
Published: December 2023

Abstract

Single-cell sequencing is a crucial tool for dissecting the cellular intricacies of complex diseases. Its prohibitive cost, however, hampers its application in expansive biomedical studies. Traditional cellular deconvolution approaches can infer cell type proportions from more affordable bulk sequencing data, yet they fall short in providing the detailed resolution required for single-cell-level analyses. To overcome this challenge, we introduce "scSemiProfiler", an innovative computational framework that marries deep generative model with active learning strategies. This method adeptly infers single-cell profiles across large cohorts by fusing bulk sequencing data with targeted single-cell sequencing from a few carefully chosen representatives. Extensive validation across heterogeneous datasets verifies the precision of our semi-profiling approach, aligning closely with true single-cell profiling data and empowering refined cellular analyses. Originally developed for extensive disease cohorts, "scSemiProfiler" is adaptable for broad applications. It provides a scalable, cost-effective solution for single-cell profiling, facilitating in-depth cellular investigation in various biological domains.
Stable skyrmion bundles at room temperature and zero magnetic field in a chiral magnet
Authors: Tang Jin , Zhang Yongsen , Wu Yaodong , Shi Meng , Xu Xitong , Wang Shouguo , Tian Mingliang , Du Haifeng 
Published: December 2023

Abstract
Topological spin textures are characterized by topological magnetic charges Q, which govern their fascinating electro-magneto properties. Recent studies have achieved skyrmion bundles with arbitrary integer values of Q, opening up possibilities for exploring topological spintronics based on the parameter freedom of Q. However, the realization of stable skyrmion bundles in chiral magnets at room temperature and zero magnetic field, which is the prerequisite for realistic device applications, has remained exclusive. Here, through the combination of pulsed currents and reversed magnetic fields, we experimentally achieved skyrmion bundles with different inter-Q values, reaching a maximum of 24 at above room temperature and zero magnetic field in a β-Mn-type Co8Zn10Mn2 chiral magnet. We demonstrate the field-driven topological quantitated annihilation of high-Q bundles and present a stable phase diagram as a function of temperature and field. Our experimental findings are consistently corroborated by micromagnetic simulations. The observation of skyrmion bundles and their multi-Q topological properties at room temperature and zero fields could promote realistic multi-Q-based topological spintronic devices.
Harmonizing the Scale: An End-to-End Self-Supervised Framework for Cross-Modal Search and Retrieval in Histopathology Archives
Authors: Tizhoosh Hamid , Maleki Danial , Rahnamayan Shahryar 
Published: December 2023

Abstract
The exponential growth of data across various medical domains has generated a substantial demand for techniques to analyze multimodal big data. This demand is particularly pronounced in fields such as computational pathology due to the diverse nature of the tissue. Cross-modal retrieval aims to identify a common latent space where different modalities, such as image-text pairs, exhibit close alignment. The primary challenge, however, often lies in the representation of tissue features. While language models can be trained relatively easily, visual models frequently struggle due to the scarcity of labeled data. To address this issue, the innovative concept of harmonization has been introduced, extending the learning scheme distillation without supervision, known as DINO. The harmonization of scale refines the DINO paradigm through a novel patching approach, overcoming the complexities posed by gigapixel whole slide images in digital pathology. Experiments conducted on diverse datasets have demonstrated that the proposed approach significantly enhances cross-modal retrieval in tissue imaging. Moreover, it exhibits vast potential for other fields that rely on gigapixel imaging.
Periodontitis-induced neuroinflammation triggers IFITM3-Aβ axis to cause Alzheimer's disease-like pathology and cognitive decline
Authors: Kong Lingwenyao , Li Juanjuan , Gao Lu , Zhao Yonggang , Chen Weixian , Wang Xumeng , Wang Songlin , Wang Fu 
Published: December 2023

Abstract
Background
Periodontitis is a risk factor linked to Alzheimer's disease (AD), and amyloid-beta (Aβ) is a pathological characteristic of AD. Increasing evidence suggests that periodontitis contributes to the formation and progression of AD. Type I interferons are upregulated in Porphyromonas gingivalis (Pg)-induced periodontitis in mice. Colonization of Pg has been identified in the brains of patients with AD. Recently, interferon-induced transmembrane protein 3 (IFITM3), an inflammation-induced innate immunity protein, was identified as a novel γ-secretase modulatory protein for Aβ production in AD. However, it is unknown whether periodontitis also increases type I interferons in the brain and induces AD-like pathology by triggering the innate immune response of glial cells and activating the IFITM3-Aβ axis. Whether colonization of Pg in brain induces innate immune in astrocytes and microglia remains elusive.
Methods
We evaluated the effects of periodontitis on cognitive impairment in C57BL/6J and APP/PS1 mice using behavioral tests. The effects of Periodontitis/Pg on microglia and astrocytes were measured using qRT-PCR, western blotting, and histological staining.
Results
Pg-induced periodontitis caused cognitive impairment in C57BL/6J mice and exacerbated a cognitive decline in APP/PS1 mice. Furthermore, periodontitis increased the level of interferon (IFN)-β, IFITM3, and Aβ deposition of C57BL/6J and APP/PS1 mice in the brain. And we identified Pg DNA, apoptotic cells, glial activation, and the expression of inflammatory mediators in the brain of a mouse periodontitis model. Furthermore, our results confirmed that astrocytes were the main responders to Pg-induced innate immunity and inflammation in vitro and in vivo. Periodontitis also induces an increase in IFITM3 expression in periodontal tissue, salivary glands, and saliva.
Conclusions
We define a previously unidentified link between periodontitis and cognitive decline, and provide new evidence linking oral pathogenic bacteria-induced innate immunity and neuroinflammation to AD pathogenesis and cognitive decline in part by disrupting the BBB, triggering neuroinflammation and increasing IFITM3 in glial cells for Aβ deposition. Periodontitis also exacerbates innate immunity and cognitive impairment in AD mice, which implies the necessity of preventing and controlling periodontal disease in AD patients.
Automated Benchmarking for the Purchase of Second-hand Cars and Motorcycles in Colombia through Web Scraping and Prescriptive Analytics
Authors: Ariza Camila , Conti Dante , Garzon Wilmer 
Published: December 2023

Abstract
In the current context of the automotive market in Colombia there is an exorbitant rise in prices of second-hand vehicles and in the absence of structured tools to access quickly and reliably to the market information, it is necessary to create a centralized dataset that reflects the inventory offered on the web, in order to facilitate the comparison, collection and decision making in the process of buying and selling second-hand vehicles. Under this premise, this applied research article proposes the creation of a minimum viable product that allows to extract, prepare, process, transform and compare the information via Web Scraping and propose decision alternatives using prescriptive analytics based on decision trees and benchmarking for users of the second-hand car and motorcycle market in Colombia. The results of the developed tool are satisfactory since they offered the user two options according to the sought characteristics of the motor vehicle, one of minimum price and the other of minimum mileage-lowest price. Finally, to go further, it is recommended to explore more complete frameworks for a more personalized experience.
Evaluation of antioxidant and anti-cancer potential of ethanolic and n-hexane extracts of fresh water algae from Lahore
Authors: REHAN SAMAN SAFDAR , Aftab Saira 
Published: December 2023

Abstract
Context: Algae have importance in different fields especially in medical aspects due to nature source for production of bioactive metabolic compounds.
Aims: Research focused on activity of algal compounds and their applications in medical therapy such as antitumor and antioxidant agents.
Methods: Freshwater algal extract prepared in ethanol, hexane and chloroform. The required algal sample were treated with GC-MS analysis, phytochemical analysis and in vitro anti cancer potential.
Key results: Gas chromatography analysis showed different type of hydrocarbons, ketones, esters, and carboxylic compounds. The results revealed that extracts contain higher antioxidant activity and by consequence, they can be considered as good source of natural products that may be employed in the treatment of the different diseases that associated with oxidative stress.
Quantization of linear acoustic and elastic waves in isomorphic pattern of characterizations
Authors: Yang Chen 
Published: December 2023

Abstract
From the macroscopic to the microscopic world, quantum mechanical effects in acoustics and elastic waves have become increasingly important. Studies on the quantum effects of acoustic and elastic waves using experimental methods have been reported in the literature. However, the conventional formulations of acoustic and elastic waves are still mainly governed by classical models. In this study, we investigated the quantization of acoustic and elastic waves using generalized Lorenz gauges. The potential variables of acoustic and elastic waves can be quantized in a manner similar to that of electrodynamics. The results include the Schrödinger equation with minimal coupling between the field and particles. The quantization of field variables is established as a consequence of the gauge symmetry property of the Schrödinger equation. Later, we explored the connections between the parallel formulations of mechanics and waves through an algebraic aspect. This highlights the isomorphism pattern from the characterization of parallel formulations. To support the results, the derivations of potential formulations based on Lorenz gauges and functional mapping between field variables are presented.
A new taxonomy to map evidence on carbon dioxide removal side effects
Authors: Prütz Ruben , Fuss Sabine , Lück Sarah , Stephan Leon , Rogelj Joeri 
Published: December 2023

Abstract
Carbon dioxide removal (CDR) is key to climate change mitigation, yet implications of its deployment remain unclear. Recent exponential growth in literature is rapidly filling this gap but makes the synthesis of the evidence on CDR side effects increasingly challenging. We address this issue by mapping this literature and proposing a taxonomy to synthesize and compare evidence on CDR side effects. The expansive evidence warrants the use of machine learning to systematically select relevant research and provide an inventory of nearly 400 side effects and challenges. We find rich evidence in Europe but little information for Africa, South America, and Oceania, where large-scale CDR is nevertheless projected. There is a predominance of articles discussing negative effects compared to positive ones. Starting from the limitations of our analysis and literature gaps, we provide entry points for future studies that can build on our literature-based taxonomy.
Identification and characterization of a novel species, Providencia xianensis sp. nov., isolated from clinical infections
Authors: Dong Xu , Xiang Yanghui , Yang Peihong , Wang Shanmei , Yan Wenjuan , Yuan Youhua , Zhou Shan , Zhou Ke , Liu Jiayun , Zhang Ying 
Published: December 2023

Abstract
It is widely acknowledged that the Providencia genus harbors certain opportunistic pathogens capable of causing human infections, some of which may be severe. In our collection of clinical Providencia isolates, we identified two strains of multidrug-resistant bacteria identified as Providencia rettgeri from two distinct sources. These strains were characterized phenotypically and confirmed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S rRNA sequencing, multilocus sequence analysis (MLSA), and whole-genome sequencing. Phylogenetic analysis suggests that these two strains, sharing high average nucleotide identity (ANI) of 99.28% and in silico DNA-DNA hybridization (dDDH) of 95.1%, represent the same species and constitute a novel branch within the Providencia genus. However, their respective ANI (79.84-84.20%) and dDDH (21.1-25.6%) values fall below the accepted species delineation threshold for Providencia rettgeri. Consequently, we propose that these isolates be recognized as a novel species, Providencia xianensis sp. nov. Alarmingly, both strains, which were isolated from locations far apart exhibited resistance to last-resort antibiotics used in clinical settings, indicating possible wide distribution of this new species, underscoring the emergent threat they pose due to potential multidrug resistance, a matter demanding immediate clinical vigilance.
Customer Orientated Indices and Reliability Evaluation of Meshed Power Distribution System
Authors: Aditya Tiwary 
Published: December 2023

Aim. Reliability evaluation of a system or component or element is very important in order to predict its availability and other relevant indices. Reliability is the parameter which tells about the availability of the system under proper working conditions for a given period of time. The study of different reliability indices are very important considering the complex and uncertain nature of the power system. In this paper reliability evaluation of the meshed distribution system is presented. This paper also evaluates basic indices such as average failure rate, average outage time and average annual outage time. Along with basic indices, customer orientated indices such as system average interruption frequency index, system average interruption duration index and customer average interruption duration index of an electrical power distribution system is also evaluated. The electrical power distribution system taken for study is meshed distribution system in nature.Aditya Tiwary. "Customer Orientated Indices and Reliability Evaluation of Meshed Power Distribution System" Reliability: Theory & Applications, vol. 15, no. 1, 2020, pp. 10-19. doi:10.24411/1932-2321-2020-11001
Barriers to and Facilitators of Older People’s Engagement With Web-Based Services: Qualitative Study of Adults Aged >75 Years
Authors: Money Annemarie , Hall Alex , Harris Danielle , Eost-Telling Charlotte , McDermott Jane , Todd Chris 
Published: December 2023

Background
The COVID-19 pandemic has accelerated the shift toward the digital provision of many public services, including health and social care, public administration, and financial and leisure services. COVID-19 services including test appointments, results, vaccination appointments and more were primarily delivered through digital channels to the public. Many social, cultural, and economic activities (appointments, ticket bookings, tax and utility payments, shopping, etc) have transitioned to web-based platforms. To use web-based public services, individuals must be digitally included. This is influenced by 3 main factors: access (whether individuals have access to the internet), ability (having the requisite skills and confidence to participate over the web), and affordability (ability to pay for infrastructure [equipment] and data packages). Many older adults, especially those aged >75 years, are still digitally excluded.

Objective
This study aims to explore the views of adults aged >75 years on accessing public services digitally.

Methods
We conducted semistructured qualitative interviews with a variety of adults aged ≥75 years residing in Greater Manchester, United Kingdom. We also interviewed community support workers. Thematic analysis was used to identify the key themes from the data.

Results
Overall, 24 older adults (mean age 81, SD 4.54 y; 14/24, 58% female; 23/24, 96% White British; and 18/24, 75% digitally engaged to some extent) and 2 support workers participated. A total of five themes were identified as key in understanding issues around motivation, engagement, and participation: (1) “initial motivation to participate digitally”—for example, maintaining social connections and gaining skills to be able to connect with family and friends; (2) “narrow use and restricted activity on the web”—undertaking limited tasks on the web and in a modified manner, for example, limited use of web-based public services and selected use of specific services, such as checking but never transferring funds during web-based banking; (3) “impact of digital participation on well-being”—choosing to go to the shops or general practitioner’s surgery to get out of the house and get some exercise; (4) “the last generation?”—respondents feeling that there were generational barriers to adapting to new technology and change; and (5) “making digital accessible”—understanding the support needed to keep those engaged on the web.

Conclusions
As we transition toward greater digitalization of public services, it is crucial to incorporate the perspectives of older people. Failing to do so risks excluding them from accessing services they greatly rely on and need.
Use of Metadata-Driven Approaches for Data Harmonization in the Medical Domain: Scoping Review
Authors: Peng Yuan , Bathelt Franziska , Gebler Richard , Gött Robert , Heidenreich Andreas , Henke Elisa , Kadioglu Dennis , Lorenz Stephan , Vengadeswaran Abishaa , Sedlmayr Martin 
Published: December 2023

Background
Multisite clinical studies are increasingly using real-world data to gain real-world evidence. However, due to the heterogeneity of source data, it is difficult to analyze such data in a unified way across clinics. Therefore, the implementation of Extract-Transform-Load (ETL) or Extract-Load-Transform (ELT) processes for harmonizing local health data is necessary, in order to guarantee the data quality for research. However, the development of such processes is time-consuming and unsustainable. A promising way to ease this is the generalization of ETL/ELT processes.

Objective
In this work, we investigate existing possibilities for the development of generic ETL/ELT processes. Particularly, we focus on approaches with low development complexity by using descriptive metadata and structural metadata.

Methods
We conducted a literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We used 4 publication databases (ie, PubMed, IEEE Explore, Web of Science, and Biomed Center) to search for relevant publications from 2012 to 2022. The PRISMA flow was then visualized using an R-based tool (Evidence Synthesis Hackathon). All relevant contents of the publications were extracted into a spreadsheet for further analysis and visualization.

Results
Regarding the PRISMA guidelines, we included 33 publications in this literature review. All included publications were categorized into 7 different focus groups (ie, medicine, data warehouse, big data, industry, geoinformatics, archaeology, and military). Based on the extracted data, ontology-based and rule-based approaches were the 2 most used approaches in different thematic categories. Different approaches and tools were chosen to achieve different purposes within the use cases.

Conclusions
Our literature review shows that using metadata-driven (MDD) approaches to develop an ETL/ELT process can serve different purposes in different thematic categories. The results show that it is promising to implement an ETL/ELT process by applying MDD approach to automate the data transformation from Fast Healthcare Interoperability Resources to Observational Medical Outcomes Partnership Common Data Model. However, the determining of an appropriate MDD approach and tool to implement such an ETL/ELT process remains a challenge. This is due to the lack of comprehensive insight into the characterizations of the MDD approaches presented in this study. Therefore, our next step is to evaluate the MDD approaches presented in this study and to determine the most appropriate MDD approaches and the way to integrate them into the ETL/ELT process. This could verify the ability of using MDD approaches to generalize the ETL process for harmonizing medical data.