bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of human papillomavirus infection among females and the genetic variations of HPV18 and HPV58 in Henan province, China
Authors: Wang Ying , Han Shuizhong , Wang Xiaochuan , Song Shuya , Wang Xiuli 
Published: February 2023

AbstractThe present study aims to investigate the genotype distribution of Human papillomavirus (HPV) and variations of HPV18 and HPV58 infection among 6538 females in Luoyang city during 2019–2021. The overall positive rate of females with HPV infection was 12.34%, with 9.74% were infected with single HPV and 2.60% with multiple HPVs. The prevalent rate of high-risk HPV (HR-HPV) was 9.85% and the top five HR-HPV genotypes were HPV52 (1.94%), HPV16 (1.93%), HPV58 (1.48%), HPV51 (1.02%) and HPVV39 (0.99%). Two peaks of HPV infections rates were observed in females aged ≤ 20 and 61–65 years old. To characterize mutations, 39 HPV18 and 56 HPV58 L1, E6 and E7 genes were sequenced and submitted to GenBank. In the HPV18 E6-E7-L1 sequences, 38 nucleotides changes were observed with 10/38 were non-synonymous mutations (5 in E6 gene, 1 in E7 gene and 4 in L1 gene). In the HPV58 E6-E7-L1 sequences, 53 nucleotides changes were observed with 23/53 were non-synonymous mutations (3 in E6 gene, 5 in E7 gene and 15 in L1 gene). Phylogenetic analysis based on L1 gene showed that 92.3% (36/39) of HPV18 isolates fell into sublineage A1 and 7.7% (3/39) belonged to A5. For HPV58, 75.0% (42/56) isolates belonged to sublineage A1 and 25.0% (14/56) were sublineage A2. There was no association between amino mutation and cervical lesions. The present study provides basic information about the distribution, genotypes and variations of HPV among females population in Luoyang city, which would assist in the formulation of HPV screening and vaccination programs and preventive strategies for HPV-attributable cancer in this region.
Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients
Authors: Cowley Hannah Paris , Robinette Michael S. , Matelsky Jordan K. , Xenes Daniel , Kashyap Aparajita , Ibrahim Nabeela F. , Robinson Matthew L. , Zeger Scott , Garibaldi Brian T. , Gray-Roncal William 
Published: February 2023

AbstractAs clinicians are faced with a deluge of clinical data, data science can play an important role in highlighting key features driving patient outcomes, aiding in the development of new clinical hypotheses. Insight derived from machine learning can serve as a clinical support tool by connecting care providers with reliable results from big data analysis that identify previously undetected clinical patterns. In this work, we show an example of collaboration between clinicians and data scientists during the COVID-19 pandemic, identifying sub-groups of COVID-19 patients with unanticipated outcomes or who are high-risk for severe disease or death. We apply a random forest classifier model to predict adverse patient outcomes early in the disease course, and we connect our classification results to unsupervised clustering of patient features that may underpin patient risk. The paradigm for using data science for hypothesis generation and clinical decision support, as well as our triaged classification approach and unsupervised clustering methods to determine patient cohorts, are applicable to driving rapid hypothesis generation and iteration in a variety of clinical challenges, including future public health crises.
Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images
Authors: Singh Abhilash , Gaurav Kumar 
Published: February 2023

AbstractWe propose a new architecture based on a fully connected feed-forward Artificial Neural Network (ANN) model to estimate surface soil moisture from satellite images on a large alluvial fan of the Kosi River in the Himalayan Foreland. We have extracted nine different features from Sentinel-1 (dual-polarised radar backscatter), Sentinel-2 (red and near-infrared bands), and Shuttle Radar Topographic Mission (digital elevation model) satellite products by leveraging the linear data fusion and graphical indicators. We performed a feature importance analysis by using the regression ensemble tree approach and also feature sensitivity to evaluate the impact of each feature on the response variable. For training and assessing the model performance, we conducted two field campaigns on the Kosi Fan in December 11–19, 2019 and March 01–06, 2022. We used a calibrated TDR probe to measure surface soil moisture at 224 different locations distributed throughout the fan surface. We used input features to train, validate, and test the performance of the feed-forward ANN model in a 60:10:30 ratio, respectively. We compared the performance of ANN model with ten different machine learning algorithms [i.e., Generalised Regression Neural Network (GRNN), Radial Basis Network (RBN), Exact RBN (ERBN), Gaussian Process Regression (GPR), Support Vector Regression (SVR), Random Forest (RF), Boosting Ensemble Learning (Boosting EL), Recurrent Neural Network (RNN), Binary Decision Tree (BDT), and Automated Machine Learning (AutoML)]. We observed that the ANN model accurately predicts the soil moisture and outperforms all the benchmark algorithms with correlation coefficient (R = 0.80), Root Mean Square Error (RMSE = 0.040$$\mathrm {m^3/m^3}$$m3/m3), and bias = 0.004$$\mathrm {m^3/m^3}$$m3/m3. Finally, for an unbiased and robust conclusion, we performed spatial distribution analysis by creating thirty different sets of training-validation-testing datasets. We observed that the performance remains consistent in all thirty scenarios. The outcomes of this study will foster new and existing applications of soil moisture.
Probabilistic sea level rise flood projections using a localized ocean reference surface
Authors: Paoa Noah , Fletcher Charles H. , Anderson Tiffany R. , Coffman Makena , Habel Shellie 
Published: February 2023

AbstractProjecting sea level rise (SLR) impacts requires defining ocean surface variability as a source of uncertainty. We analyze ocean surface height data from a Regional Ocean Modeling System reanalysis to produce an ocean reference surface (ORS) as a proxy for the local mean higher high water. This method allows incorporation of ocean surface level uncertainty into bathtub modeling and generation of probability-based projections of SLR-induced flooding. For demonstration, we model the NOAA Intermediate, Intermediate-high and High regional SLR scenarios at three locations on the island of Oʻahu, Hawai’i. We compare 80% probability-based flood projections generated using our approach to those generated using the Tidal Constituents and Residual Interpolation (TCARI) method. TCARI is the predecessor of VDatum, the standard method used by NOAA available only for the continental U.S., Puerto Rico, and U.S. Virgin Islands. For validation, ORS pixel values representing the Honolulu tide gauge location are compared to tide gauge observations. The more realistic distribution of daily higher high water provided by ORS improves projections of SLR-induced flooding for locations where VDatum is not available. We highlight the importance of uncertainty and user-defined probability in identifying locations of flooding and pathways for additional sources of flooding.
Universal power-law of terahertz optical properties of borosilicate, tellurite, and chalcogenide glass families
Authors: Tostanoski Nicholas J. , Sundaram S. K. 
Published: February 2023

AbstractTerahertz (THz) time-domain spectroscopy (TDS, THz-TDS) was used to measure THz optical properties, i.e., refractive indices and absorption coefficients, of borosilicate, tellurite, and chalcogenide glass families. We observe that the THz optical properties depend on glass compositions. THz refractive indices recorded an increasing trend from borosilicate to chalcogenide and to tellurite glass families. Our results demonstrate the ability to select a glass family, system, and composition to target THz optical properties for potential use in THz optical and photonic applications. We report K and β fitting parameters for the power-law model used to describe these properties and show how it can be universally applied to several glass families.
Direct formation of carbon nanotube wiring with controlled electrical resistance on plastic films
Authors: Komatsu Hiroaki , Matsunami Takahiro , Sugita Yosuke , Ikuno Takashi 
Published: February 2023

AbstractWe have developed a simple method to fabricate multi-walled carbon nanotube (MWNT) wiring on a plastic film at room temperature under atmosphere pressure. By irradiating a MWNT thin film coated on a polypropylene (PP) film with a laser, a conductive wiring made of a composite of MWNT and PP can be directly fabricated on the PP film. The resistance of MWNT wiring fabricated using this method were ranging from 0.789 to 114 kΩ/cm. By changing the scanning speed of laser, we could fabricate various regions with different resistances per unit length even within a single wiring. The formation mechanism of the MWNT wiring with tunable resistance was discussed from both experimental results, such as microscopic structural observation using cross-sectional scanning electron microscopy and microscopic Raman imaging, and simulation results, such as heat conduction in the film during local laser heating. The results suggest that the MWNT wiring was formed by PP diffusion in MWNT at high temperature. We also demonstrated that excess MWNTs that were not used for wiring could be recovered and used to fabricate new wirings. This method could be utilized to realize all-carbon devices such as light-weight flexible sensors, energy conversion devices, and energy storage devices.
AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms
Authors: Bordin Nicola , Sillitoe Ian , Nallapareddy Vamsi , Rauer Clemens , Lam Su Datt , Waman Vaishali P. , Sen Neeladri , Heinzinger Michael , Littmann Maria , Kim Stephanie , Velankar Sameer , Steinegger Martin , Rost Burkhard , Orengo Christine 
Published: February 2023

AbstractDeep-learning (DL) methods like DeepMind’s AlphaFold2 (AF2) have led to substantial improvements in protein structure prediction. We analyse confident AF2 models from 21 model organisms using a new classification protocol (CATH-Assign) which exploits novel DL methods for structural comparison and classification. Of ~370,000 confident models, 92% can be assigned to 3253 superfamilies in our CATH domain superfamily classification. The remaining cluster into 2367 putative novel superfamilies. Detailed manual analysis on 618 of these, having at least one human relative, reveal extremely remote homologies and further unusual features. Only 25 novel superfamilies could be confirmed. Although most models map to existing superfamilies, AF2 domains expand CATH by 67% and increases the number of unique ‘global’ folds by 36% and will provide valuable insights on structure function relationships. CATH-Assign will harness the huge expansion in structural data provided by DeepMind to rationalise evolutionary changes driving functional divergence.
Financial incentives often fail to reconcile agricultural productivity and pro-conservation behavior
Authors: Bell Andrew Reid , Rakotonarivo O. Sarobidy , Bhargava Apurva , Duthie A. Bradley , Zhang Wei , Sargent Rebecca , Lewis Amy R. , Kipchumba Adams 
Published: February 2023

AbstractPaying resource users to preserve features of their environment could in theory better align production and conservation goals. We show, however, that across a range of conservation dilemmas, they might not. We conduct a synthesis of dynamic games experiments built around collective action dilemmas in conservation, played across Europe, Africa, and Asia. We find, across this range of dilemmas, that while payments can encourage pro-conservation behavior, they often fail to capitalize on the potential for jointly improving productive and environmental outcomes, highlighting the more nuanced challenge of reconciling livelihoods with conservation goals. We further find production (yield) and the joint production-environment product (i.e., a measure of agricultural production multiplied by a measure of pro-conservation practice) are better preserved in groups that are more educated, more gender diverse and that better represent women. We discuss how the design of incentive programs can better align livelihood and environment goals.
Speech emotion recognition with artificial intelligence for contact tracing in the COVID‐19 pandemic
Authors: Pucci Francesco , Fedele Pasquale , Dimitri Giovanna Maria 
Published: February 2023

AbstractIf understanding sentiments is already a difficult task in human‐human communication, this becomes extremely challenging when a human‐computer interaction happens, as for instance in chatbot conversations. In this work, a machine learning neural network‐based Speech Emotion Recognition system is presented to perform emotion detection in a chatbot virtual assistant whose task was to perform contact tracing during the COVID‐19 pandemic. The system was tested on a novel dataset of audio samples, provided by the company Blu Pantheon, which developed virtual agents capable of autonomously performing contacts tracing for individuals positive to COVID‐19. The dataset provided was unlabelled for the emotions associated to the conversations. Therefore, the work was structured using a sort of transfer learning strategy. First, the model is trained using the labelled and publicly available Italian‐language dataset EMOVO Corpus. The accuracy achieved in testing phase reached 92%. To the best of their knowledge, thiswork represents the first example in the context of chatbot speech emotion recognition for contact tracing, shedding lights towards the importance of the use of such techniques in virtual assistants and chatbot conversational contexts for psychological human status assessment. The code of this work was publicly released at: https://github.com/fp1acm8/SER.
Magnetic helicity and free magnetic energy as tools for probing eruptions in two differently evolving solar active regions
Authors: Liokati E. , Nindos A. , Georgoulis M. K. 
Published: February 2023

Aims. We study the role of magnetic helicity and free magnetic energy in the initiation of eruptions in two differently evolving solar active regions (ARs).
Methods. Using vector magnetograms from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory and a magnetic connectivity-based method, we calculate the instantaneous relative magnetic helicity and free magnetic energy budgets for several days in two ARs, AR11890 and AR11618, both with complex photospheric magnetic field configurations.
Results. The ARs produced several major eruptive flares while their photospheric magnetic field exhibited different evolutionary patterns: primarily flux decay in AR11890 and primarily flux emergence in AR11618. Throughout much of their evolution, both ARs featured substantial budgets of free magnetic energy and of both positive (right-handed) and negative (left-handed) helicity. In fact, the imbalance between the signed components of their helicity was as low as in the quiet Sun and their net helicity eventually changed sign 14−19 h after their last major flare. Despite this incoherence, the eruptions occurred at times of net helicity peaks that were co-temporal with peaks in the free magnetic energy. The percentage losses, associated with the eruptive flares, in the normalized free magnetic energy were significant, in the range of ∼10−60%. For the magnetic helicity, changes ranged from ∼25% to the removal of the entire excess helicity of the prevailing sign, leading a roughly zero net helicity, but with significant equal and opposite budgets of both helicity senses. Respective values ranged from (0.3 − 2)×1032 erg and (1.3 − 20)×1042 Mx2 for energy and helicity losses. The removal of the slowly varying background component of the free energy and helicity (either the net helicity or the prevailing signed component of helicity) time series revealed that all eruption-related peaks of both quantities exceeded the 2σ levels of their detrended time series above the removed background. There was no eruption when only one or none of these quantities exceeded its 2σ level.
Conclusions. Our results indicate that differently evolving ARs may produce major eruptive flares even when, in addition to the accumulation of significant free magnetic energy budgets, they accumulate large amounts of both left- and right-handed helicity without a strong dominance of one handedness over the other. In most cases, these excess budgets appear as localized peaks, co-temporal with the flare peaks, in the time series of free magnetic energy and helicity (and normalized values thereof). The corresponding normalized free magnetic energy and helicity losses can be very significant at certain times.
Nowcasting geoelectric fields in Ireland using magnetotelluric transfer functions
Authors: Malone-Leigh John , Campanyà Joan , Gallagher Peter T. , Neukirch Maik , Hogg Colin , Hodgson Jim 
Published: February 2023

Geomagnetically induced currents (GIC) driven by geoelectric fields pose a hazard to ground-based infrastructure, such as power grids and pipelines. Here, a new method is presented for modelling geoelectric fields in near real time, to provide valuable information to help mitigate the impact of GIC. The method uses magnetic field measurements from the Magnetometer Network of Ireland (MagIE; https://www.magie.ie), interpolates the geomagnetic field variations between magnetometers using spherical elementary current systems (SECS), and estimates the local electric field using a high-density (< 40 km) network of magnetotelluric transfer functions (MT-TF) encompassing the island. The model was optimised to work in near real time, with a correction curve applied to the geoelectric field time series. This approach was successfully validated with measured electric fields at four sites for a number of geomagnetic storms, providing accurate electric fields up to a 1-minute delay from real time, with high coherence (0.70 – 0.85) and signal-to-noise ratio (SNR; 3.2 – 6.5) relative to measured electric field validation time series. This was comparable to a standard non-real-time geoelectric field model (coherence = 0.80 − 0.89 and SNR = 4.0 − 7.0). The impact of galvanic distortion on the model was also briefly evaluated, with a galvanic distortion correction leading to a more homogeneous representation of the direction of the electric field, at a regional scale.
What Is the Microbiome? A Description of a Social Network
Authors: van Praagh J.B. , Havenga Klaas 
Published: February 2023

AbstractThe gut microbiome has coevolved with its hosts over the years, forming a complex and symbiotic relationship. It is formed by what we do, what we eat, where we live, and with whom we live. The microbiome is known to influence our health by training our immune system and providing nutrients for the human body. However, when the microbiome becomes out of balance and dysbiosis occurs, the microorganisms within can cause or contribute to diseases. This major influencer on our health is studied intensively, but it is unfortunately often overlooked by the surgeon and in surgical practice. Because of that, there is not much literature about the microbiome and its influence on surgical patients or procedures. However, there is evidence that it plays a major role, showing that it needs to be a topic of interest for the surgeon. This review is written to show the surgeon the importance of the microbiome and why it should be taken into consideration when preparing or treating patients.
The Effects of Monaural Stimulation on Frequency-Following Responses in Adults Who Can Sing in Tune and Those Who Cannot
Authors: Sanfins Milaine Dominici , Gielow Ingrid , Madazio Glaucya , Honorio Francine , Bordin Tatiana , Skarzynski Piotr Henryk , Skarzynska Magdalena Beata , Behlau Mara 
Published: February 2023

Abstract
Introduction Musicians have an advantage over non-musicians in detecting, perceiving, and processing nonverbal (i.e., environmental sounds, tones and others) and verbal sounds (i.e., consonant, vowel, phrases and others) as well as instrumental sounds. In contrast to the high skill of musicians, there is another group of people who are tone-deaf and have difficulty in distinguishing musical sounds or singing in tune. These sounds can originate in different ways, such as a musical instrument, orchestra, or the human voice.
Objective The objective of the present work is to study frequency-following responses (FFRs) in individuals who can sing in-tune and those who sing off-tune.
Methods Electrophysiological responses were recorded in 37 individuals divided in two groups: (i) control group (CG) with professional musicians, and (ii) experimental group (EG) with non-musicians.
Results There was homogeneity between the two groups regarding age and gender. The CG had more homogeneous responses in the latency of the FFRs waves when responses between the right and left ears were compared to those of the EG.
Conclusion This study showed that monaural stimulation (right or left) in an FFR test is useful for demonstrating impairment of speech perception in individuals who sing off tune. The response of the left ear appears to present more subtlety and reliability when identifying the coding of speech sound in individuals who sing off tune.
Cloacal Malformation with Associated Urethral Atresia
Authors: Al-Shamaileh Tamador , Tiusaba Laura , Jacobs Shimon Eric , Russell Teresa Lynn , Bokova Elizaveta , Pohl Hans G. , Varda Briony K. , Ho Christina , Feng Christina , Badillo Andrea , Levitt Marc A. 
Published: February 2023

Abstract
Introduction Cloacal malformations comprise a heterogeneous group of anomalies that are considered the most complex anorectal malformations (ARMs) in females. Precise evaluation to identify the unique anatomy prior to reconstruction with collaboration between colorectal surgeons, urologists, and gynecologists is vital. Here, we present a rare anatomical variation in a patient with a cloacal malformation which affected operative and postoperative management.
Case description A 6-year-old female with cloaca who underwent colostomy, vaginostomy, and vesicostomy as a newborn presented for reconstruction. Her VACTERL workup was negative except for an atretic right kidney. Her ARM index included the cloaca, a normal spine, and sacrum with a lateral sacral ratio of 0.7, predicting good potential for bowel continence. Cystoscopy through the vesicostomy showed a small bladder with normal ureteral orifices, and a closed bladder neck, with no identifiable urethra. A cloacagram showed an atretic common channel, a single small vagina, and a rectum below the pubococcygeal line. The patient underwent a posterior sagittal anorectovaginourethroplasty, vaginal patch using rectum, rectoplasty, and perineal body reconstruction. The urethra was not amenable to reconstruction, so the vesicostomy was preserved and a future Mitrofanoff was planned.
Conclusion Urethral atresia is a rare and challenging finding in cloaca patients, and a vesicostomy is needed to drain urine in the newborn period. Preoperative examination under anesthesia, cystoscopy, vaginoscopy, and cloacagram are crucial to identify the precise anatomy and to plan accordingly.