bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sinusitis Detection Using Neural Network Fusion of Different Classifiers on Thermal Images.
Authors: Katual Jayaprakash , Kaul Amit 
Published: January 2023

Abstract
Inflammation or swelling of the tissue lining on the sinuses is known as sinusitis, due to an inflammatory response, or an infection brought on by a virus, bacteria, or fungus. An unchecked sinus infection can spread to the eyes and brain, causing blindness and brain abscess respectively. In this work, a non-invasive technique developed for the detection of sinusitis from thermal images has been presented. CNN, KNN, and SVM have been used as classifiers. For KNN and SVM features were extracted from cropped thermal face images by taking the output of the first fully connected layer of Alexnet and VGGNet. The fusion of these classifiers has been done to improve the detection performance of the individual classifiers. The algorithm has been tested on a publicly available dataset. The performance evaluation has been carried out on the basis of five indices. Based on the results, fusion with neural network illustrates the highest accuracy of 99.59% irrespective of the feature extraction method, followed by the majority voting technique with an accuracy of 99.18% for features extracted by Alexnet and 98.78% for features extracted by VGGNet.
Spatial Analysis of Socioeconomic Factors at Found Locations of Orphaned Mammals in Champaign County
Authors: Elzinga Colleen , Heniff Stephanie , Sander William , Brown William Marshall , Varga Csaba , Sander Samantha 
Published: January 2023

Abstract
Young mammals make up a significant portion of animals brought into wildlife rehabilitation centers. Unfortunately, some of these “orphaned” individuals are inappropriately removed from their native habitat. As such, there is a need for educational community outreach centered on the proper identification of orphaned wildlife that benefit from human intervention, while maximizing limited resources of rehabilitation facilities. This study evaluated found locations of common mammalian orphans presenting from Champaign County to the University of Illinois Wildlife Medical Clinic (WMC) between 2015-2020. The found locations of the orphans (99 Virginia opossums, 80 common raccoons, 441 eastern gray squirrels, 602 eastern cottontails) were mapped using Geographic Information System (GIS) and overlaid with maps of human population density, income, and education level for analysis. The four species were most commonly found in areas with high population density (p < 0.001) and middle family income (p < 0.001). Opossums, squirrels, and cottontails were found more frequently in areas of high education levels (p < 0.001), while there was no significant difference in education level for found raccoons.
Different response of arbuscular mycorrhizal fungal communities in soil and Elymus nutans roots to long-term warming in alpine meadow
Authors: Han Bing , Zhang Wantong , Yu Lu , Wei Xiaoting , Zhou Huakun , Geng Yiyi , Lu Xinmin , Shao Xinqing 
Published: January 2023

Abstract
Background and aims
Arbuscular mycorrhizal fungi (AMF) are symbiotic with most terrestrial plants and are important microorganisms that sustain the activity of alpine meadow ecosystems, while warming affects plant and microbial activity and soil nutrient cycling. However, the response of AMF to long-term warming is still poorly understood, especially in alpine meadows.
Methods
We conducted a 7-year field warming experiment to examine the effects of warming (+ 2°C) on the composition of AMF communities in soil and plant roots.
Results
The results showed that warming significantly affected AMF communities, increasing the α-diversity of soil AMF communities and the relative abundance of Glomeraceae and decreasing the relative abundance of Paralomeraceae, while the relative abundance and diversity of AMF communities within plant roots decreased. Warming increased soil organic carbon and effective phosphorus content and promoted mycorrhizal colonization. In addition, soil AMF communities were strongly influenced by SOC, and intraradical AMF communities were correlated with NH4+-N.
Conclusions
In conclusion, our results suggest that warming mainly changed the composition of soil AMF communities in alpine meadows and enhanced plant-AMF interactions.
Evolutionarily recent retrotransposons contribute to schizophrenia
Authors: Modenini Giorgia , Abondio Paolo , Guffanti Guia , Boattini Alessio , Macciardi Fabio 
Published: January 2023

Abstract
Transposable Elements (TEs) are mobile genetic elements that constitute half of the human genome. Recent studies suggest that polymorphic non-reference TEs (nrTEs) may contribute to cognitive diseases, such as schizophrenia, through a cis-regulatory effect. The aim of this work is to identify sets of nrTEs putatively linked to an increased risk of developing schizophrenia. To do so, we inspected the nrTE content of genomes from the Dorsolateral Prefrontal Cortex of schizophrenic and control individuals, and identified 38 nrTEs which possibly contribute to the emergence of this psychiatric disorder. Furthermore, we performed in silico functional inferences and found, for instance, that 9 of the 38 nrTEs act as expression/alternative splicing quantitative trait loci (eQTLs/sQTLs) in the brain, suggesting a possible role in shaping the human cognitive genome structure. Therefore, to our knowledge, this is the first attempt at identifying polymorphic nrTEs that can contribute to the functionality of the brain. Finally, we suggest that a neurodevelopmental genetic mechanism, which involves evolutionarily young nrTEs, can be the key to understanding the ethiopathogenesis of this complex disorder.
Measures of social connectedness in adult populations: A systematic review
Authors: Plackett Ruth , Hulin Joe , Mukuria Clara , Clowes Mark , Ramsey Sheena E. , Spencer Liam , Adams Emma A. , Dykxhoorn Jennifer , Walters Kate , Osborn David P.J. , Zamperoni Victoria , Jones Oliver , Weich Scott 
Published: January 2023

Abstract

Background: Poor social connectedness has been identified as a risk factor for poor mental health but there is a lack of standardisation in how it is measured. This systematic review aimed to identify suitable measures of social connectedness for use in UK adult general populations.
Methods: Searches were undertaken in two stages to identify: (1) measures of social connectedness from review articles and grey literature and (2) studies reporting on the psychometric properties of the identified measures. Grey literature and five databases were searched: MEDLINE, Embase and PsycINFO; CINAHL and Web of Science. Studies based on UK adult general populations (16-65 years) or other English language speaking countries with similar cultures (US, Canada, Ireland, Australia and New Zealand) were included. Psychometric evidence was extracted relating to six general domains: conceptual model, content validity, reliability, construct validity, scoring and interpretability, and respondent burden and presentation. A narrative synthesis summarised these psychometric properties.
Results: Stage (1) 2,396 studies were retrieved and, 24 possible measures of social connectedness were identified; stage (2) 6,218 studies were identified reporting on psychometrics of identified measures and 22 studies were included. These studies provided psychometric evidence for 10 measures, and we did not find psychometric studies for the other identified measures. Six measures (6/10, 60%) reported assessing loneliness and four (4/10, 40%) reported assessing social support but there was a degree of overlap between the assessments of each concept. There was good evidence of reliability across measures, 90% (9/10) had adequate internal consistency, but evidence of content validity was only available for one scale. Five measures (5/10, 50%) reported on at least half of the psychometric criteria, and these were: UCLA-3 (for loneliness), and MSPSS, F-SozU K-6, SPS-10 and SPS-5 (for social support).
Conclusions: Some support was found for the use of social connectedness measures in public mental health research, as the measures were largely reliable. Further testing is required to establish content validity, and to clarify the definition and conceptualisation of social connectedness, to enable standardisation in the approach to measuring social connectedness.
Wavelet thresholding and F-NLM filtering based denoising algorithms applied to high resolution SAR ship detection
Authors: Tong Liang , Liu Dan , Peng Zhongbo , Zou Han 
Published: January 2023

Abstract
High resolution (HR) SAR ship images have distinctive features of multi-scale, multi-scene and densely arranged distribution of targets, while it is still challenging to have fast and accurate detection. To address the above problem, a SAR ship target detection framework using wavelet thresholding and Fast NLM (F-NLM) joint filtering is proposed. Firstly, wavelet thresholding and F-NLM are used to filter and de-noise the high-resolution SAR images to reduce background clutter noise, while enhancing the detection target detail features and edge information, solving the problem of high false alarm rate in multi-scale, inshore and offshore scenes of ships in SAR images of high resolutions.Then, the YOLOv5 detection network combined with the bi-directional feature fusion module (Bi-FPN) is selected to enable the model to better balance feature information. It can strengthen the aggregation of low and high semantic information and further improve the accuracy of the model. Experimental results show that the SAR ship detection framework has better robustness and target detection accuracy than other deep-learning based algorithms. Compared with SSDD and YOLOv5 network model, the Average Precision (AP) is improved by 1.33% and 2.25% respectively.
Intestinal Helminths Infections as Infrequent Cause of Emergency Abdominal Surgery: A Retrospective Study in a University Hospital Over 20 Years
Authors: Barquín-Yagüez José , Juez Luz divina , Hernández Patricia I. , Ballestero Araceli , Martín Oihane , Campo Rosa , Vaello Victor , García-Pérez Juan Carlos 
Published: January 2023

Abstract
Introduction
All organs of any organism can be affected by helminths. They can be seen in a broad spectrum, from simple infestations to extensive, life-threatening involvement. Symptomatology is usually of chronic latent course. However, sometimes the presentation is acute and requires urgent surgical intervention.
Material and methods
We conducted a retrospective observational prospective recruitment study of patients undergoing emergency surgery for helminth infection from January 2000 to December 2019 at a university hospital. Sociodemographic and analytical variables, variables related to the clinical process, and the diagnostic test were analysed. Variables related to the surgical procedure and postoperative complications were also analysed.
Results
A total of 36 patients required emergency surgery for their helminth infection, which represented 0.26% of emergency abdominal surgeries. The mean age was 34.91 ± 21.5 years, with a predominance of men (69.4%). Most patients presented with pain in the right iliac fossa (69.4%), followed by symptoms compatible with intestinal obstruction (19.4%). The most frequent surgical interventions were appendectomy (38,9%) followed bowel resection (33,3%) and ileocecal resection (11,1%). Enterobious vermicularis and Anisakis simplex both together accounted for 75% of the sample. Statistically significant differences were identified in age (p<0.001), diagnostic test performed (p=0.032), intraoperative clinical diagnosis (p=0.005) and surgical treatment received (p<0.001).
Conclusion
The prevalence of emergency surgeries for intestinal helminth parasitism is decreasing. However, the majority of these are E. vermicularis and Anisakis simplex, which have distinctly different clinical presentations. Identification and recognition by surgeons continue to be necessary for further postoperative management and possible complications.
Breaking down the fences among registries on Autoinflammatory diseases: the E-Merge project
Authors: Vyzhga Yulia , Hentgen Veronique , Caorsi Roberta , Wittkowski Helmut , Hofer Michael , Ruperto Nicolino , Lainka Elke , Theodoropoulou Katerina , Foell Dirk , Mosci Eugenia , Gattorno Marco 
Published: January 2023

Abstract
Background. Between the various number of different AIDs, the absolute majority remains to be rare, with a single representative among big populations. Project, endorsed by PRES and supported by the EMERGE fellowship program, performed in line with the Metadata registry for the ERN RITA (MeRITA), had an objective to perform data harmonization attempt of the most relevant research questions regarding clinical features, diagnostic strategy, and optimal management of the autoinflammatory diseases. Results. Analysis of 3 large European registries: Eurofever, JIR-cohort, and AID-Net with total coverage of 7825 patients from 278 participating centers all over the world was performed in the context of the epidemiological and clinical data merging. Information summarized in the registries covers not only pediatric patients, but as well adults, with newly diagnosed AID. General aspects of the existing epidemiological data were discussed in the context of patient distribution around the world, potential diagnostic delay, access to genetic testing, and availability of the treatment. Conclusions. Overall work results indicate great potential for upcoming collaborative work using existing data in cohorts, which will definitely benefit the quality of medical care performed for patients with autoinflammatory diseases.
Influence of Gingival Display on Smile Attractiveness Assessed by Saudi Arabian Laypersons and Dental Professionals
Authors: Alaqeely Razan , AlShehri Fahad , AlRowis Raed , AlSeddiq Amal 
Published: January 2023

AbstractObjective:To evaluate the influence of changes in the gingival display of the maxillary teeth on smile attractiveness assessed by Saudi Arabian dental professionals and laypeople.Materials and methods:A total of 138 dental professional and 182 laypeople rated the attractiveness of male and female smiles in a computerized survey. Each smile was digitally altered to achieve different levels of gingival exposure. Each photo was accompanied by a visual analog scale (VAS) for rating.Results:Among dental professionals, 61% rated the female photo with a 1-mm low lip line as the most attractive smile (VAS score±SE, 7.3±3.18), while 52.7% of laypeople considered the smile with a 2-mm low lip line as the most attractive (6.7±3.4). Regarding male smile photos, 61.6% of dental professionals found the 1-mm low lip line the most attractive (7.3±3.18). The same rating was given by 48.3% of laypeople (6.1±3.6) (p≤0.009). The least attractive smile photo was the smile showing 4 mm of gingiva for male and female smiles. More than half of the laypeople believed that an attractive smile highly affects social life and communication.Conclusion:TheSaudi Arabian population appears to be sensitive to the amount of gingival display. The difference in female smile assessment between dental professionals and laypeople highlights the importance of dentist-patient consensus regarding decisions for esthetic treatments.Clinical Relevance:Esthetic treatment is of a major concern for both dentist and patient. The careful assessment of smile pillars including gingival display must be tailored to each patient.
Garcidepsidon B from Garcinia parvifolia: Antimicrobial Activities of The Medicinal Plants from North Kalimantan against Dental Caries and Periodontal Disease Pathogen
Authors: egra saat , Kuspradini Harlinda , Kusuma Irawan Wijaya , Batubara Irmanida , Yamauchi Kosei , Mitsunaga Tohru 
Published: January 2023

Abstract
In this study, to find the potential of antibacterial materials, we focused on the plant used for oral treatment by native people of North Kalimantan. We have selected 10 medicinal plants usually used in daily life by native people. We determine samples using antimicrobial assay and Gtase Inhibitory activity. We obtained the most effective sample, Garcinia parvifolia, as antimicrobial activity against the Streptococcus sobrinus and Porphyromonas gingivaliswith a MIC value of 0.5 mg/ml inhibition on both of bacteria and MBC value of 0.5 mg/ml and 1 mg/ml, respectively. The methanol extract of G. parvifolia leaf showed antimicrobial activity in a MIC, and MBC assay by activity-guide fractionation, garcidepsidone B (1) was isolated as an active com-pound. The MIC of (1) against S. sobrinus was 0.02 mg/mL and against P. gingivalis was 0.05 mg/mL. Based on these results, we validated that the leaf extract has been used by the traditional tribe of North Kalimantan.
Fast model-free standardization and integration of single-cell transcriptomics data
Authors: Xu Yang , Kramann Rafael , McCord Rachel , Hayat Sikander 
Published: January 2023

Abstract
Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). MASI first identifies putative cell-type markers from reference data through an ensemble approach. Then, it converts gene expression matrix to cell-type score matrix with the identified putative cell-type markers for the purpose of cell-type annotation and data integration. Because of integration through cell-type markers instead of model inference, MASI can annotate approximately one million cells on a personal laptop, which provides a cheap computational alternative for the single-cell community. We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods based on speed. Its performance for both tasks of data integration and cell-type annotation are comparable or even superior to these existing methods. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively.
Spatio-Temporal Analysis on the Optical Properties of Vembanad Lake, Kerala, India – A Remote Sensing Approach
Authors: S Parthasarathy K S , Kundapura Subrahmanya 
Published: January 2023

Abstract
Water quality is one of the most essential parts of environmental monitoring; even a little variation in its characteristics may have a large influence on the ecosystem. The water quality parameters such as diffuse attenuation (Kd(490)), turbidity, Suspended Particulate Matter (SPM) and Chlorophyll-a (Chl-a) are considered in this study to evaluate the water quality of Vembanad Lake, Kerala, India. The lake is considered of ecological importance by the Ramsar Convention and has faced serious concerns over the recent years. This study aims to examine the change in the water quality using Sentinel-2 satellite data in the ACOLITE software from 2016 to 2021. The analysis showed 2.5% decrease in the values of Kd whereas SPM and turbidity show a decrease of about 4.3% from the year 2016 to 2021. The flood and the COVID lockdown had an impact on the improvement in the quality of water during this time. There is an anticipation of the increase in Chl-a content during the period but there is no substantial change in the Chl-a till the year 2020 whereas 2021 showed a 12% decrease in the Chl-a values. This may be due to the reduction in the Hydrological Residence Time (HRT) in the lake.
Air quality and cancer risk in the All of Us Research Program
Authors: Craver Andrew , Luo Jiajun , Kibriya Muhammad G. , Randorf Nina , Bahl Kendall , Connellan Elizabeth , Powell Johnny , Zakin Paul , Jones Rena R. , Argos Maria , Ho Joyce , Kim Karen , Daviglus Martha L. , Greenland Philip , Ahsan Habibul , Aschebrook-Kilfoy Briseis 
Published: January 2023

Abstract
Introduction

The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks.

Materials and Methods

This work was performed on data from 325,264 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA’s Earth Observing System Data and Information Center and assigned using participants’ 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships.

Results

A total of 32,073 prevalent cancer cases were ascertained from participant EHR data, while 16,688 cases were ascertained from self-reported survey data; 7,692 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2006 to 2016 was 9.4 µg/m3 (min 3.0, max 15.1). In analysis of cancer cases from both sources combined (n = 41,069), each unit increase in PM2.5 was associated with increased odds for blood cancer (OR = 1.02, 95% CI: 1.01–1.03), brain cancer (OR = 1.06, 95% CI: 1.03–1.09), breast cancer (OR = 1.03, 95% CI: 1.02–1.04), colon and rectum cancer (OR = 1.02, 95% CI: 1.00-1.04), and endometrial cancer (OR = 1.06, 95% CI: 1.03–1.10). In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer.

Conclusions

We found evidence of an association of PM2.5 with brain, breast, blood, colon and rectum, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.
Early Detection and Control of Anthracnose Disease in Cashew Leaves to Improve Crop Yield using Image Processing and Machine Learning Techniques
Authors: P Sudha , P Kumaran 
Published: January 2023

Abstract
Agriculture is one of the primary pillars powering India's economy. It is alarming to note that India's agriculture rate is declining steeply. Climate change, environmental pollution, and soil erosion are well-known factors affecting crop productivity. The increasing prevalence of plant diseases is also a significant contributing factor affecting agriculture. Early disease detection and mitigation actions based on identified diseases in the plants are critical in increasing crop productivity. This study considers a machine-learning model for detecting disease in cashew leaves. This work concentrates on Anthracnose disease, which leads to severe yield loss when it affects the cashew plant. In this regard, cashew leaves are collected and used to train various machine learning classifiers to identify and classify the disease. This work focuses on the segmentation and classification of leaves using various Machine Learning models. For this, Basic segmentation approaches like Global threshold, Adaptive Gaussian, Adaptive Mean, Otsu, Canny, Sobel, and K-Means, and Machine Learning models like Random Forest, Decision Tree, KNN, Logistic Regression, Gaussian Naive Bayes Classifiers are employed. The final classification employs a Hard and Soft voting classifier in addition to the Decision Tree, KNN, Logistic Regression, and Gaussian Naive Bayes classifiers. Finally, we observe that K-Means segmentation with Random Forest outperforms other classifiers. The accuracy obtained from the Random Forest classifier is 96.7% for the CCDDB dataset, and the accuracy obtained from the Random Forest classifier is 99.7% for the PDDB dataset.