bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of the indoor climate in cultural heritage buildings through machine learning: first results from two field tests
Authors: Boesgaard Christian , Hansen Birgit Vinther , Kejser Ulla Bøgvad , Mollerup Søren Højlund , Ryhl-Svendsen Morten , Torp-Smith Noah 
Published: October 2022

Abstract
Control of temperature and relative humidity in storage areas and exhibitions is crucial for long-term preservation of cultural heritage objects. This paper explores the possibilities for developing a proactive system, based on a machine-learning model (XGBoost), for predicting the occurrence of unwanted indoor environmental conditions: either a too high or a too low relative humidity, within the forthcoming 24 h. The features used in the model were hourly indoor and outdoor climate recordings, and it was applied to two indoor heritage environments; a storage facility and a church building. The test accuracy (f1-score) of the model was good (0.93 for high RH; 0.93 for low RH) when applied to the storage building, but only 0.78; 0.62 (high RH; low RH) for the church building test. Challenges encountered include difficulties in obtaining good historical climate data sets for training and testing the model, and the dependency of external IT systems, which, if they fail, inactivates the model without a warning. Several issues call for more research: A desirable improvement of the model would be predictions for periods longer than 24 h ahead, still maintaining a high test accuracy. Further perspectives of using machine learning for indoor environmental forecasting could be for indoor air pollution, or energy consumption due to climate control.
Prevalences and excretion levels of Lawsonia intracellularis, Brachyspira pilosicoli and Escherichia coli F4 and F18 in fecal sock samples from Danish weaner and finisher pig batches and the association with diarrhea
Authors: Musse Susanne Leth , Nielsen Gitte Blach , Stege Helle , Weber Nicolai Rosager , Houe Hans 
Published: October 2022

AbstractBackgroundBacterial enteritis in growing pigs is a matter of concern in Danish pig production challenging herd health as well as production economy, and antimicrobial usage. The aim of this observational study using fecal sock samples was to determine the prevalence and excretion level of Lawsonia intracellularis(LI), Brachyspira pilosicoli(BP),Escherichia coli F4(F4) andF18(F18) and to investigate associations between prevalence or excretion levels of the bacteria and diarrhea. The study was performed in the late weaner and the early finisher period in herds with a history of diarrhea. Every weaner and finisher herd contributed with one sample each.ResultsIn total, 47 weaner and 59 finisher herds were sampled. The overall prevalence and excretion levels (median and range in log(10) copies/gram of feces) were for LI 84.0% (median 6.2; range 3.0–7.7), for BP 45.2% (median 5.6; range 3.0–6.6), for F18 20.8% (median 5.7; range 4.7–7.7), and for F4 4.7% (median 5.5; range 5.2–6.0). In both diarrheic and non-diarrheic samples, the most prevalent bacteria were either LI alone or LI and BP in combination. In general, no association was found between increasing total bacterial excretion levels and diarrhea, but prevalence (p = 0.04) and excretion (p < 0.01) level of F18 was found to be significantly higher in diarrheic samples. Further, a significant association was found between low LI excretion level and lack of diarrhea in weaner herds (p = 0.03). A significant positive correlation was found between excretion levels of LI and BP in diarrheic weaner herd samples (p = 0.02).ConclusionEnteric pathogens were prevalent in a wide range of bacterial excretion levels in both diarrheic and non-diarrheic samples. Especially LI and BP were frequently found and with a positive correlation between excretion levels. Even in the absence of diarrhea, high prevalence and excretion levels of LI and BP were detected, thus making the status of diarrhea an insufficient tool for assessing the severity of their infections.
Identification of tumor-associated antigens and immune subtypes of lower-grade glioma and glioblastoma for mRNA vaccine development
Authors: Wang Zhi-liang , Huang Ruo-yu , Han Bo , Wu Fan , Sun Zhi-yan , Li Guan-zhang , Zhang Wei , Zhao Zheng , Liu Xing 
Published: October 2022

Abstract
Background
mRNA became a promising therapeutic approach in many diseases. This study aimed to identify the tumor antigens specifically expressed in tumor cells for lower-grade glioma (LGG) and glioblastoma (GBM) patients.

Methods
In this work, the mRNA microarray expression profile and clinical data were obtained from 301 samples in the Chinese Glioma Genome Atlas (CGGA) database, the mRNA sequencing data and clinical data of 701 samples were downloaded from The Cancer Genome Atlas (TCGA) database. Genetic alterations profiles were extracted from CGGA and cBioPortal datasets. R language and GraphPad Prism software were applied for the statistical analysis and graph work.

Results
PTBP1 and SLC39A1, which were overexpressed and indicated poor prognosis in LGG patients, were selected as tumor-specific antigens for LGG patients. Meanwhile, MMP9 and SLC16A3, the negative prognostic factors overexpressed in GBM, were identified as tumor-specific antigens for GBM patients. Besides, three immune subtypes (LGG1-LGG3) and eight WGCNA modules were identified in LGG patients. Meanwhile, two immune subtypes (GBM1–GBM2) and 10 WGCNA modules were selected in GBM. The immune characteristics and potential functions between different subtypes were diversity. LGG2 and GBM1 immune subtype were associated with longer overall survival than other subtypes.

Conclusion
In this study, PTBP1 and SLC39A1 are promising antigens for mRNA vaccines development in LGG, and MMP9 and SLC16A3 were potential antigens in GBM. Our analyses indicated that mRNA vaccine immunotherapy was more suitable for LGG2 and GBM1 subtypes. This study was helpful for the development of glioma immunotherapies.
The AYA Care Plan: Initial Evaluation of a Web-Based Psychosocial Intervention
Authors: Markwardt Haley S. , Taghavi Sarah E. , Williams Addison P. , Olivares Matthew N. , McDuffee Peyton R. , Al Achkar Morhaf , Hall Brittany C. 
Published: October 2022

PURPOSEAdolescents and young adults (AYA) with cancer do not fit neatly into pediatric or older adult oncology care settings. Recent efforts have led to the development of psychosocial interventions for AYAs, but studies show AYAs demonstrate low levels of engagement in psychosocial services. The AYA Care Plan is one of the only web-based tools providing a personalized, psychosocial resource that addresses unmet needs for AYAs in active treatment and post-treatment survivorship. The current study aims to assess the usability and utility of the AYA Care Plan and identify opportunities for improvement.METHODSClinic staff administered an online distress and needs assessment to AYA patients with cancer at outpatient oncology clinics. Personalized care plans were sent to participants on the basis of their responses. A total of 11 AYAs between the ages 18 and 39 years, with a mean age of 31.64 years, then completed qualitative interviews about their experiences. Thematic analysis was used to identify themes on the AYA Care Plan.RESULTSA majority of participants reported positive usability features. Half of the participants reported using their care plan to make health care decisions. One person indicated not finding the resources helpful, and the other half of participants reported not engaging with the care plan. Participants also offered suggestions for improvement.CONCLUSIONThe AYA Care Plan appears to be a useful psychosocial intervention for some AYAs with cancer. Future research should continue to examine the AYA Care Plan's usability and utility, and specify when, how, and for whom the AYA Care Plan is useful.
A Two-Step Frailty Assessment Strategy in Older Patients With Solid Tumors: A Decision Curve Analysis
Authors: González Serrano Adolfo , Laurent Marie , Barnay Thomas , Martínez-Tapia Claudia , Audureau Etienne , Boudou-Rouquette Pascaline , Aparicio Thomas , Rollot-Trad Florence , Soubeyran Pierre , Bellera Carine , Caillet Philippe , Paillaud Elena , Canouï-Poitrine Florence 
Published: October 2022

PURPOSE The intended clinical value of frailty screening is to identify unfit patients needing geriatric assessment (GA) and to prevent unnecessary GA in fit patients. These hypotheses rely on the sensitivity and specificity of screening tests, but they have not been verified. METHODS We performed a cross-sectional analysis of outpatients age ≥ 70 years with prostate, breast, colorectal, or lung cancer included in the ELCAPA cohort study (ClinicalTrials.gov identifier: NCT02884375 ) between February 2007 and December 2019. The diagnostic accuracy of the G8 Geriatric Screening Tool (G8) and modified G8 scores for identifying unfit patients was determined on the basis of GA results. We used decision curve analysis to calculate the benefit of frailty screening for detecting unfit patients and avoiding unnecessary GA in fit patients across different threshold probabilities. RESULTS We included 1,648 patients (median age, 81 years), and 1,428 (87%) were unfit. The sensitivity and specificity were, respectively, 85% (95% CI, 84 to 87) and 59% (95% CI, 57 to 61) for G8, and 86% (95% CI, 84 to 87) and 60% (95% CI, 58 to 63) for the modified G8 score. For decision curve analysis, the net benefit (NB) for identifying unfit patients were 0.72 for G8, 0.72 for the modified G8, and 0.82 for GA at a threshold probability of 0.25. At a threshold probability of 0.33, the NBs were 0.71, 0.72, and 0.80, respectively. At a threshold probability of 0.5, the NBs were 0.68, 0.69, and 0.73, respectively. No screening tool reduced unnecessary GA in fit patients at predefined threshold probabilities. CONCLUSION Although frailty screening tests showed good diagnostic accuracy, screening showed no clinical benefits over the GA-for-all strategy. NB approaches, in addition to diagnostic accuracy, are necessary to assess the clinical value of tests.
Adaptation of Remote Symptom Monitoring Using Electronic Patient-Reported Outcomes for Implementation in Real-World Settings
Authors: Rocque Gabrielle B. , Dent D’Ambra N. , Ingram Stacey A. , Caston Nicole E. , Thigpen Haley B. , Lalor Fallon R. , Jamy Omer H. , Giri Smith , Azuero Andres , Young Pierce Jennifer , McGowen Chelsea L. , Daniel Casey L. , Andrews Courtney J. , Huang Chao-Hui Sylvia , Dionne-Odom J. Nicholas , Weiner Bryan J. , Howell Doris , Jackson Bradford E. , Basch Ethan M. , Stover Angela M. 
Published: October 2022

PURPOSE: Despite evidence of clinical benefits, widespread implementation of remote symptom monitoring has been limited. We describe a process of adapting a remote symptom monitoring intervention developed in a research setting to a real-world clinical setting at two cancer centers. METHODS: This formative evaluation assessed core components and adaptations to improve acceptability and fit of remote symptom monitoring using Stirman's Framework for Modifications and Adaptations. Implementation outcomes were evaluated in pilot studies at the two cancer centers testing technology (phase I) and workflow (phase II and III) using electronic health data; qualitative evaluation with semistructured interviews of clinical team members; and capture of field notes from clinical teams and administrators regarding barriers and recommended adaptations for future implementation. RESULTS: Core components of remote symptom monitoring included electronic delivery of surveys with actionable symptoms, patient education on the intervention, a system to monitor survey compliance in real time, the capacity to generate alerts, training nurses to manage alerts, and identification of personnel responsible for managing symptoms. In the pilot studies, while most patients completed > 50% of expected surveys, adaptations were identified to address barriers related to workflow challenges, patient and clinician access to technology, digital health literacy, survey fatigue, alert fatigue, and data visibility. CONCLUSION: Using an implementation science approach, we facilitated adaptation of remote symptom monitoring interventions from the research setting to clinical practice and identified key areas to promote effective uptake and sustainability.
Anther development in Arabidopsis thaliana involves symplastic isolation and apoplastic gating of the tapetum-middle layer interface
Authors: Truskina Jekaterina , Boeuf Sophy , Renard Joan , Andersen Tonni Grube , Geldner Niko , Ingram Gwyneth 
Published: October 2022

ABSTRACT
During flowering plant reproduction, anthers produce pollen grains, the development of which is supported by the tapetum, a nourishing maternal tissue that also contributes non-cell-autonomously to the pollen wall, the resistant external layer on the pollen surface. How the anther restricts movement of the tapetum-derived pollen wall components, while allowing metabolites such as sugars and amino acids to reach the developing pollen, remains unknown. Here, we show experimentally that in arabidopsis thaliana the tapetum and developing pollen are symplastically isolated from each other, and from other sporophytic tissues, from meiosis onwards. We show that the peritapetal strip, an apoplastic structure, separates the tapetum and the pollen grains from other anther cell layers and can prevent the apoplastic diffusion of fluorescent proteins, again from meiosis onwards. The formation and selective barrier functions of the peritapetal strip require two NADPH oxidases, RBOHE and RBOHC, which play a key role in pollen formation. Our results suggest that, together with symplastic isolation, gating of the apoplast around the tapetum may help generate metabolically distinct anther compartments.
Underwater hearing in sea ducks with applications for reducing gillnet bycatch through acoustic deterrence
Authors: McGrew Kathleen A. , Crowell Sarah E. , Fiely Jonathan L. , Berlin Alicia M. , Olsen Glenn H. , James Jennifer , Hopkins Heather , Williams Christopher K. 
Published: October 2022

ABSTRACT
As diving foragers, sea ducks are vulnerable to underwater anthropogenic activity, including ships, underwater construction, seismic surveys and gillnet fisheries. Bycatch in gillnets is a contributing source of mortality for sea ducks, killing hundreds of thousands of individuals annually. We researched underwater hearing in sea duck species to increase knowledge of underwater avian acoustic sensitivity and to assist with possible development of gillnet bycatch mitigation strategies that include auditory deterrent devices. We used both psychoacoustic and electrophysiological techniques to investigate underwater duck hearing in several species including the long-tailed duck (Clangula hyemalis), surf scoter (Melanitta perspicillata) and common eider (Somateria mollissima). Psychoacoustic results demonstrated that all species tested share a common range of maximum auditory sensitivity of 1.0–3.0 kHz, with the long-tailed ducks and common eiders at the high end of that range (2.96 kHz), and surf scoters at the low end (1.0 kHz). In addition, our electrophysiological results from 4 surf scoters and 2 long-tailed ducks, while only tested at 0.5, 1 and 2 kHz, generally agree with the audiogram shape from our psychoacoustic testing. The results from this study are applicable to the development of effective acoustic deterrent devices or pingers in the 2–3 kHz range to deter sea ducks from anthropogenic threats.
Thermal sensitivities of respiration and protein synthesis differ among larval families of the Pacific oyster, Crassostrea gigas
Authors: DellaTorre Melissa B. , Pan Francis T. C. , Griffith Andrew W. , Li Ning , Manahan Donal T. 
Published: October 2022

ABSTRACT
Understanding the mechanisms of biological responses to environmental change is a central theme in comparative and evolutionary physiology. Here, we analyzed variation in physiological responses to temperature, using 21 full-sibling larval families of the Pacific oyster, Crassostrea gigas. Pedigrees were confirmed with genetic markers for adult broodstock obtained from our breeding program. From these 21 larval families, 41 determinations of thermal sensitivity (Q10 values) were assayed for larvae of different sizes. For respiration, thermal sensitivity was consistent within a larval family during growth, but showed significant differences among families. Different Q10 values were evident among 21 larval families, with family accounting for 87% of variation. Specifically, four larval families maintained an increased thermal sensitivity for respiration (Q10 of 3). This physiology would confer resilience to rising temperature by matching the increased energy demand of protein synthesis (Q10 of 3 previously reported). For protein synthesis, differences in Q10 values were also observed. Notably, a family was identified that had a decreased thermal sensitivity for protein synthesis (Q10 of 1.7 cf. Q10 of 3 for other families), conferring an optimal energy allocation with rising temperature. Different thermal sensitivities across families for respiration (energy supply) and protein synthesis (energy demand) were integrated into models of energy allocation at the whole-organism level. The outcome of these analyses provides insights into the physiological bases of optimal energy allocation with rising temperature. These transgenerational (egg-to-egg) experiments highlight approaches to dissect components of phenotypic variance to address long-standing questions of genetic adaptation and physiological resilience to environmental change.
Evaluation of the DAISY (Diseases Attacking the Immune SYstem) Award for recognising excellence in nursing
Authors: Williamson Lauren , Burog Walter , Taylor Rachel M 
Published: October 2022

Background: With increasing demand for nursing services worldwide, the onus is on healthcare systems to implement measures to improve retention. The DAISY Award was designed to celebrate nursing with the suggestion that it may improve staff retention. Aim: To describe the experience and impact of winning the DAISY Award. Method: Data were collected through virtual semistructured interviews from award winners (n=4), nominees (n=4) and nominators (n=4). An analytical framework was developed to allow the responses of the three groups to be compared. Findings: Four major themes emerged from the responses: awareness of the DAISY Award; the nomination process, the impact on retention and winner benefits. Conclusion: Being nominated or winning a DAISY Award had a positive impact on nurses' feelings towards their role. This was a small evaluation in a single organisation, so the value of adopting the DAISY Award for recognising nurses' contributions to patient care merits further investigation, especially with regards to its effects on retention.
Public Stigmatization of People With Intellectual Disability During the COVID-19 Pandemic
Authors: Dekker Maria R. , Hendriks Alexander H. C. , Frielink Noud , Embregts Petri J. C. M. 
Published: October 2022

Abstract
This study aimed to examine the level of discrimination against people with intellectual disability during COVID-19, and assessed stereotypes, levels of familiarity with people with intellectual disability, and personal experiences with COVID-19 as potential correlates. A cross-sectional study was conducted using a large sample from the Dutch population (n = 1,797). Salient stereotype factors of people with intellectual disability were “friendly” and “in need of help,” but not “give nuisance.” Those respondents who were unfamiliar with people with intellectual disability in real life demonstrated higher levels of discrimination, perceiving them as more of a nuisance and as being less in need of help, in comparison to those who were more familiar. People with intellectual disability were judged by an ambivalent set of stereotypes during the COVID-19 pandemic that were in line with pre-COVID-19 findings and as such seemed to be fairly persistent and robust. There is a pressing need to both raise awareness of stereotypes towards and discrimination against people with intellectual disability via advocacy and education, and to facilitate positive encounters.
Reconfigurable hybrid dielectric antenna with less graphene surface area
Authors: Xie Bowen , Li Dezhi , Jiao Rongzhen 
Published: October 2022

A hybrid dielectric reconfigurable graphene
antenna is designed by combining the Yagi antenna and absorption
characteristics of graphene. Graphene is selectively covered in the
Yagi antenna directors to obtain a change of the beam from
unidirectional to bidirectional by changing the graphene potential. By
reducing the area covered by graphene, we obtain a radiation
efficiency of more than 95 percent. After adding a gold bowtie antenna
at 1550 nm, the antenna shows a larger directivity and a
smaller beam width, as well as a maximum directivity of 7.2 dBi.
Furthermore, the surface area of graphene has been reduced three
times, while the directivity improves from 4.7 to 5.6 dBi after
comparing the effect of different surface distributions, which will be
helpful to reduce the difficulty of graphene antenna manufacturing and
improve the performance of the antenna beam.
Towards explainable artificial intelligence in optical networks: the use case of lightpath QoT estimation
Authors: Ayoub Omran , Troia Sebastian , Andreoletti Davide , Bianco Andrea , Tornatore Massimo , Giordano Silvia , Rottondi Cristina 
Published: October 2022

Artificial intelligence (AI) and machine learning (ML) continue to demonstrate substantial capabilities in solving a wide range of optical-network-related tasks such as fault management, resource allocation, and lightpath quality of transmission (QoT) estimation. However, the focus of the research community has been centered on ML models’ predictive capabilities, neglecting aspects related to models’ understanding, i.e., to interpret how the model reasons and makes its predictions. This lack of transparency hinders the understanding of a model’s behavior and prevents operators from judging, and hence trusting, the model’s decisions. To mitigate the lack of transparency and trust in ML, explainable AI (XAI) frameworks can be leveraged to explain how a model correlates input features to its outputs. In this paper, we focus on the application of XAI to lightpath QoT estimation. In particular, we exploit Shapley additive explanations (SHAP) as the XAI framework. Before presenting our analysis, we provide a brief overview of XAI and SHAP, then discuss the benefits of the application of XAI in networking and survey studies that apply XAI to networking tasks. Then, we model the lightpath QoT estimation problem as a supervised binary classification task to predict whether the value of the bit error rate associated with a lightpath is below or above a reference acceptability threshold and train an ML extreme gradient boosting model as the classifier. Finally, we demonstrate how to apply SHAP to extract insights about the model and to inspect misclassifications.