bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cochlear Implant Awareness in the United States: A National Survey of 15,138 Adults
Authors: Marinelli John P. , Sydlowski Sarah A. , Carlson Matthew L. 
Published: December 2022

AbstractHearing loss is increasingly recognized as a chronic disease that warrants treatment. Depression, social isolation, loneliness, and poorer cognitive performance have all been linked to untreated and undertreated adult-onset hearing loss. A significant subset of the patient population with hearing loss is inadequately rehabilitated by hearing aids alone and may benefit from cochlear implantation. Yet, it is estimated that less than 10% of those who qualify have received implants to date. A national survey was conducted online in November and December 2021. Subjects were identified using Dynata panelists and river sampling. Enrollment occurred on a rolling basis. Upfront sample management techniques were used to control the distribution, balancing the respondent cohort to the 2018 U.S. Census on age, household income, sex, marital status, household size, race/ethnicity, and education. Among 15,138 adult respondents with a mean (SD) age of 51 (17) years (54% female), only 10% reported being very familiar with cochlear implants, and 31% of those with hearing difficulty reported that they have “never heard” of a cochlear implant. Females were statistically significantly more likely to report some degree of familiarity with cochlear implants than men (34 vs. 26%; p < 0.01). The greatest familiarity with cochlear implants was observed among those aged 35 to 44 years (18% reporting “very familiar”), whereas only 9% of those aged 65 to 74, 10% aged 75 to 84, and 8% ≥85 reported being very familiar (p < 0.01). Those identifying as White/Caucasian were statistically significantly more likely to report familiarity with cochlear implants than those identifying as Black/African American and Hispanic/Latino/Spanish (33 vs. 56 vs. 50% responding that they had “never heard” of cochlear implants; p < 0.01). Among adults with hearing difficulty, nearly 80% report having never talked with a medical or hearing care professional about cochlear implants. Limited cochlear implant awareness likely influences its widespread underutilization across the United States. Sex, age, and race disparities compound these issues among men, the Medicare-aged population, and those identifying as Black/African American and Hispanic/Latino/Spanish.
A Randomized Controlled Trial of Osteopathic Manipulative Therapy to Reduce Cranial Asymmetries in Young Infants with Nonsynostotic Plagiocephaly
Authors: Bagagiolo Donatella , Priolo Claudio G. , Favre Elena M. , Pangallo Antonella , Didio Alessia , Sbarbaro Marco , Borro Tiziana , Daccò Silvia , Manzoni Paolo , Farina Daniele 
Published: December 2022

Objective This study aimed to compare the efficacy of osteopathic manipulative therapy (OMTh) versus light touch therapy (LTT) in reducing cranial asymmetries in infants with nonsynostotic plagiocephaly (NSP).
Study Design A prospective, parallel-group, single-center, LTT-controlled randomized clinical trial was conducted in the Department of Neonatology of Sant'Anna Hospital in Turin, Italy, from September 6, 2016 to February 20, 2020. We enrolled infants of 1 to 6 months of age with NSP, who were then randomly assigned to the study group (repositioning therapy plus six sessions of OMTh) or the control group (repositioning therapy plus six sessions of LTT). The outcome was the reduction of the oblique diameter difference index (ODDI) score <104%, which was assessed at the end of the intervention protocol (at 3 months) and at 1 year of age.
Results A total of 96 infants were randomized, 48 in the OMTh group and 48 in the LTT group, with mean ages of 3.1 versus 3.2 months, and baseline ODDI score of 110.2 versus 108.7%. In the OMTh group, a significant reduction of the ODDI score <104%, compared with the LTT group, was observed in the intension-to-treat (ITT) and per-protocol (PP) analyses. The ITT analysis revealed an ODDI score <104% in the OMTh group at 3 months (risk difference: 0.41; 95% confidence interval [CI]: 0.25–0.53; p < 0.001) and at the follow-up at 1 year of age (risk difference: 0.47; 95% CI: 0.31–0.64; p < 0.001). The PP analysis at 3 months reported a risk difference of 0.44 (95% CI: 0.27–0.60; p < 0.001), and at 1 year of age, a risk difference of 0.54 (95% CI: 0.36–0.72; p < 0.001).
Conclusion In infants with NSP, a course of six OMTh sessions significantly reduced cranial asymmetries at both the 3-month and 1-year follow-up assessments, compared with LTT. This study is registered with ClinicalTrial.gov (identifier: NCT03970395;
www.clinicaltrials.gov
).
Key Points
Feasibility and Impact of a Pilot Neonatal Cuddler Program on Preterm Infants in the Neonatal Intensive Care Unit
Authors: Bushroe Kylie , Lloyd Brieann , McDaneld Chonita , Mathur Amit , Rao Rakesh 
Published: December 2022

Objective Preterm infants experience daily stress in the neonatal intensive care unit (NICU). Positive sensory experiences mitigate stress responses, but parental participation can be limited by external pressures. This study aimed to describe the impact of a neonatal cuddler program (NCP) on preterm infants' growth.
Study Design A multidisciplinary program trained volunteers to interact with NICU infants when family was not at bedside. Infants were followed prospectively throughout admission. Intervention data included frequency, type, and duration of activity throughout the study period. Student t-test and chi-square test were used to analyze the impact of volunteer interaction on anthropometric measures at discharge.
Results Forty-five infants interacted with a volunteer (intervention group, n = 45) compared with the control group (n = 56) following coronavirus disease 2019 restrictions. The median (range) time of interaction with a volunteer in the intervention group was 90.0 (5.0–705.0) minutes per infant. Infants in the two groups had similar gestational ages, birth weights, lengths, and occipitofrontal circumferences (OFC). Infants in the intervention group had higher rates of spontaneous intestinal perforation, bronchopulmonary dysplasia, and reached full enteral feeds later. However, rates of severe intraventricular hemorrhage, retinopathy of prematurity, and duration of mechanical ventilation were similar. Infants in the two groups did not differ in the NICU length of stay. At discharge, infants in the intervention group weighed more (p = 0.04) and had higher OFC's (p = 0.01) and OFC z-scores (p = 0.03). The change in z-scores from birth to discharge was significant for the weight (p = 0.02) but not length or OFC. In regression analyses, only group allocation was identified as a significant factor for OFC z-scores at discharge (β= 0.279, p = 0.011) and for change in weight z-scores from birth to discharge (β = 0.226, p = 0.041).
Conclusion Growth is positively impacted by an NCP despite limited interaction. Additional work is needed to demonstrate the impact on neurobehavioral and developmental outcomes.
Key Points
Simple and active magnetic-field stabilization for cold atom experiments
Authors: Duan Zhi-Xin , Wu Wei-Tao , Lin Yue-Tong , Yang Sheng-Jun 
Published: December 2022

Cold atom experiments usually need a controllable and low-noise bias magnetic field to provide a quantization axis. Most labs need home-made stabilization of the field according to the actual setup, as commercially available power supply cannot directly satisfy their requirements. Here, by measuring the field fluctuations and active feedback modulating current supply of the applied magnetic field, we successfully demonstrate a field of 10.58 G with a stability to the level of 2.8 × 10−7 in a duration of 5 min. The root mean square noise is reduced to 0.05 mG, compared to the noise of 1.3 mG without stabilization. The coherence time of the magnetic-field sensitive transition between the rubidium ground states F=1,mF=−1 and 1,0, as measured by Rabi oscillation, is extended to 19.2 ms from the unstabilized value of 1.3 ms. This result is long enough for most experiments on quantum simulation and precision measurement. As our system has no passive magnetic shielding and additional compensation coils, it is highly simple and compact to provide the stable magnetic field and would be adapted to various applications with cold atoms.
A novel post-developmental role of the Hox genes underlies normal adult behavior
Authors: Raouf Issa A. , A. C. Menzies Jonathan , Padmanabhan Aishwarya , Alonso Claudio R. 
Published: December 2022

The molecular mechanisms underlying the stability of mature neurons and neural circuits are poorly understood. Here we explore this problem and discover that the
Hox
genes are a component of the genetic program that maintains normal neural function in adult
Drosophila
. We show that post-developmental downregulation of the
Hox
gene
Ultrabithorax
(
Ubx
) in adult neurons leads to substantial anomalies in flight. Mapping the cellular basis of these effects reveals that
Ubx
is required within a subset of dopaminergic neurons, and cell circuitry analyses in combination with optogenetics allow us to link these dopaminergic neurons to flight control. Functional imaging experiments show that
Ubx
is necessary for normal dopaminergic activity, and neuron-specific RNA-sequencing defines two previously uncharacterized ion channel-encoding genes as potential mediators of
Ubx
behavioral roles. Our study thus reveals a novel role of the
Hox
system in controlling adult behavior and neural function. Based on the broad evolutionary conservation of the Hox system across distantly related animal phyla, we predict that the Hox genes might play neurophysiological roles in adult forms of other species, including humans.
Reflections on the perceived longer-term impact of an ERPP course
Authors: Corcoran James N. 
Published: December 2022

Abstract
Research-intensive universities in the global peripheries have begun to mount English for research publication purposes (ERPP) initiatives to increase plurilingual scholars’ publishing success. Though research into pedagogical initiatives is still limited, investigations of such programs can provide researchers with a greater understanding of the broader experiences and perspectives of scholars as well as the potential impact of interventions on course participants’ scholarly writing. Answering the call for more longitudinal work in ERPP, this article outlines a small-scale, qualitative investigation of the perceived impact of an intensive ERPP course at a Mexican university on two environmental scientists’ research writing five years following course completion. Data analysis included systematic review of participant CVs, as well as semi-structured interviews with two plurilingual EAL scientists and two ERPP practitioners connected to the ERPP course. Employing a critical plurilingual lens, this article discusses findings that not only outline the perceived impact of the intervention on these scientists’ research writing at different stages of their academic trajectories, but also highlight the plurilingual nature of their evolving scholarly practices. The article culminates with data-driven suggestions for plurilingual conceptualization and enactment of scholarly writing pedagogies, policies, and research agendas.
Twin prototype networks with noisy label self-correction for fault diagnosis of wind turbine gearboxes
Authors: Liu Xiaoli , Tang Baoping , Li Qikang , Yang Qichao 
Published: December 2022

Abstract
Deep strong-supervised learning-based methods have been widely used and have made significant progress in intelligent fault diagnosis for wind turbine (WT) gearboxes. The superior performance of such methods relies on high-quality labels. However, correctly labeling the data is challenging because of the complexity of fault vibration signals and fault modes in real industrial scenarios, resulting in noisy labels in datasets, which significantly restricts the application of strong-supervised fault diagnosis models. In this study, a method based on twin prototype networks with noisy label self-correction was proposed to address fault diagnosis for WT gearboxes with noisy labels. This method introduced a collaborative learning architecture to improve the confirmation bias in the self-training of individual networks and to slow the speed of learning noisy-labeled samples. Simultaneously, the loss distribution of the samples from each network was modeled using the Gaussian mixture model to dynamically identify mislabeled samples in the training dataset. Finally, a collaborative relabeling prototype refinement module was designed to optimize the prototype learning process and enable self-correction of noisy labels. The experiments demonstrated the effectiveness and superiority of the proposed method.
Low-cost and simple fabrication of hierarchical Al nanopit arrays for deep ultraviolet refractive index sensing
Authors: Wang Huimin , Huang Liqing , Zhang Yu , Cai Yakun , Cheng Lin , Zhai Lipeng , Liu You , Zhang Xiangzhe , Zhu Jingping 
Published: December 2022

Abstract
Herein, we proposed a simple non-lithographic way to fabricate hierarchical Al nanopit arrays performed as deep ultraviolet (DUV, 200–300 nm) refractive index sensing. Only by adjusting the Al deposition thickness on the Al nanopit array, the hierarchical Al nanopit arrays with tunable plasmonic properties in the DUV region were obtained. The prepared hierarchical Al nanopit arrays are of very good time stability and its RI sensitivity and concentration detection limit of adenine ethanol solution reach 311 nm/RIU and

5
×
10

−
6

M
,

respectively, as the Al deposition thickness is 60 nm. Furthermore, the electric field distribution simulation results show that high RI sensing characteristic are mainly attributed to the local surface plasmon resonance. This investigation provides a facile way to develop low cost, high efficient and easily fabricated Al-based RI sensor in the DUV region.
EDIR: exome database of interspersed repeats
Authors: Vo Ngoc Laura D T , Osei Randy , Dohr Katrin , Olsen Catharina , Seneca Sara , Gheldof Alexander 
Published: December 2022

Abstract

Motivation
Intragenic exonic deletions are known to contribute to genetic diseases and are often flanked by regions of homology.

Results
In order to get a more clear view of these interspersed repeats encompassing a coding sequence, we have developed EDIR (Exome Database of Interspersed Repeats) which contains the positions of these structures within the human exome. EDIR has been calculated by an inductive strategy, rather than by a brute force approach and can be queried through an R/Bioconductor package or a web interface allowing the per-gene rapid extraction of homology-flanked sequences throughout the exome.

Availability and implementation
The code used to compile EDIR can be found at https://github.com/lauravongoc/EDIR. The full dataset of EDIR can be queried via an Rshiny application at http://193.70.34.71:3857/edir/. The R package for querying EDIR is called ‘EDIRquery’ and is available on Bioconductor. The full EDIR dataset can be downloaded from https://osf.io/m3gvx/ or http://193.70.34.71/EDIR.tar.gz.

Supplementary information
Supplementary data are available at Bioinformatics online.
A Hybrid-Convolution Spatial–Temporal Recurrent Network For Traffic Flow Prediction
Authors: Zhang Xu , Wen Shunjie , Yan Liang , Feng Jiangfan , Xia Ying 
Published: December 2022

Abstract
Accurate traffic flow prediction is valuable for satisfying citizens’ travel needs and alleviating urban traffic pressure. However, it is highly challenging due to the complexity of the urban geospatial structure and the highly nonlinear temporal and spatial dependence on human mobility. Most existing works proposed to rely on strict periods (e.g. daily and weekly) and separate the extraction of temporal and spatial features. Besides, most Recurrent Neural Network (RNN)-based models either fail to capture variations of spatial–temporal features in adjacent timestamps or ignore details of closeness. In this paper, we propose a Multi-attention based Hybrid-convolution Spatial-temporal Recurrent Network (MHSRN) for region-based traffic flow prediction. In MHSRN, we leverage a hybrid-convolution module to capture both shifting features and rich information at the nearest timestamps, and we apply the downsampling procedure to reduce the computation of RNN-based model. Furthermore, we propose to adopt a space-aware multi-attention module to re-perceive global and local spatial–temporal features. We conduct extensive experiments based on three real-world datasets. The results show that the MHSRN outperforms other challenging baselines by approximately 0.2–8.1% in mean absolute error on all datasets. On datasets other than TaxiBJ, the MHSRN reduces the root mean square error by at least 2.8% compared with the RNN-based model.
Epidemiology of heart failure in young adults: a French nationwide cohort study
Authors: Lecoeur Emmanuel , Domengé Orianne , Fayol Antoine , Jannot Anne-Sophie , Hulot Jean-Sébastien 
Published: December 2022

Abstract

Aims
Heart failure (HF) in young adults is uncommon, and changes in its incidence and prognosis in recent years are poorly described.

Methods and results
The incidence and prognosis of HF in young adults (18–50 years) were characterized using nationwide medico-administrative data from the French National Hospitalization Database (period 2013–2018). A total of 1,486 877 patients hospitalized for incident HF were identified, including 70 075 (4.7%) patients aged 18–50 years (estimated incidence of 0.44‰ for this age group). During the study period, the overall incidence of HF tended to decrease in the overall population but significantly increased by ∼0.041‰ in young adults (P &lt; 0.001). This increase was notably observed among young men (from 0.51‰ to 0.59‰, P &lt; 0.001), particularly those aged 36–50 years. In these young men, ischaemic heart disease (IHD) was the most frequently reported cause of HF, whereas non-ischaemic HF was mainly observed in patients ≤ 35 years old. In contrast to non-ischaemic HF, the incidence of IHD increased over the study period, which suggests that IHD-related HF is progressively affecting younger patients. Concordantly, young HF patients presented with high rates of traditional IHD risk factors, including obesity, smoking, hypertension, dyslipidaemia, or diabetes. Lastly, the rates of re-hospitalization (for HF or for any cause) within two years after the first HF event and in-hospital mortality were high in all groups, indicating a poor-prognosis population.

Conclusion
Strategies for the prevention of HF risk factors should be strongly considered for patients under 50 years old.
Prediction and determination of mildew grade in grain storage based on FOA-SVM algorithm
Authors: Yuan Jianghao , Tang Fang , Qi Zhihui , Zhao Huiyi 
Published: December 2022

AbstractGrain mildew is a significant hazard that causes food loss and poses a serious threat to human health when severe. Therefore, effective prediction and determination of mildew grade is essential for the prevention and control of mildew and global food security. In the present study, a model for predicting and determining the mildew grade of rice was constructed using logistic regression, back propagation neural network and GS-SVM (a grid search-based support vector machine algorithm) based on laboratory culture data and actual data from a granary, respectively. The results show that the GS-SVM model has a better prediction effect, but the model cannot automatically adjust the parameters and is more subjective, and the accuracy may decrease when the data set changes. Therefore, this paper establishes a new model for a support vector machine based on a fruit fly optimization algorithm (FOA-SVM), which can achieve automatic parameter search and automatically adjust its parameters to find the best result when the data set changes, with a strong ability of self-adjustment of parameters. In addition, the FOA-SVM converges quickly and the model is stable. The results of this study provide a technical method for early identification of mildew grade during grain storage, which is beneficial for the prevention and control of rice mildew during grain storage.
Insight into weevil biology from a reference quality genome of the boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae)
Authors: Cohen Zachary P , Perkin Lindsey C , Sim Sheina B , Stahlke Amanda R , Geib Scott M , Childers Anna K , Smith Timothy P L , Suh Charles 
Published: December 2022

Abstract
The boll weevil, Anthonomus grandis grandis Boheman, is one of the most historically impactful insects due to its near destruction of the US cotton industry in the early 20th century. Contemporary efforts to manage this insect primarily use pheromone baited traps for detection and organophosphate insecticides for control, but this strategy is not sustainable due to financial and environmental costs. We present a high-quality boll weevil genome assembly, consisting of 306 scaffolds with approximately 24,000 annotated genes, as a first step in the identification of gene targets for novel pest control. Gene content and transposable element distribution are similar to those found in other Curculionidae genomes; however, this is the most contiguous and only assembly reported to date for a member in the species-rich genus Anthonomus. Transcriptome profiles across larval, pupal, and adult life stages led to identification of several genes and gene families that could present targets for novel control strategies.
Genomic prediction of hybrid performance for agronomic traits in sorghum
Authors: Sapkota Sirjan , Boatwright Jon Lucas , Kumar Neeraj , Myers Matthew , Cox Alex , Ackerman Arlyn , Caughman William , Brenton Zachary W , Boyles Richard E , Kresovich Stephen 
Published: December 2022

Abstract
Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency &gt; 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76–0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12–90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.