bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonplanar sensing skins for structural health monitoring based on electrical resistance tomography
Authors: Jauhiainen Jyrki , Pour‐Ghaz Mohammad , Valkonen Tuomo , Seppänen Aku 
Published: May 2021

AbstractElectrical resistance tomography (ERT)‐based distributed surface sensing systems, or sensing skins, offer alternative sensing techniques for structural health monitoring, providing capabilities for distributed sensing of, for example, damage, strain, and temperature. Currently, however, the computational techniques utilized for sensing skins are limited to planar surfaces. In this paper, to overcome this limitation, we generalize the ERT‐based surface sensing to nonplanar surfaces covering arbitrarily shaped three‐dimensional structures; we construct a framework in which we reformulate the image reconstruction problem of ERT using techniques of Riemannian geometry, and solve the resulting problem numerically. We test this framework in series of numerical and experimental studies. The results demonstrate the feasibility of the proposed formulation and the applicability of ERT‐based sensing skins to nonplanar geometries.
Dynamics‐based cross‐domain structural damage detection through deep transfer learning
Authors: Lin Yi‐zhou , Nie Zhen‐hua , Ma Hong‐wei 
Published: May 2021

AbstractStructural damage detection (SDD) still suffers from environmental uncertainties or modeling errors, causing a gap between the numerical model and the real structure. It results in performance degradation in the application of many model‐based methods, which are usually designed on a numerical model and needed to be applied to a real structure. Such a situation is defined as a cross‐domain SDD problem in this work. This paper aims to address the cross‐domain SDD problem by designing a feature‐extractor to generate both damage‐sensitive and domain‐invariant features, instead of trying to reduce the gap, as the traditional methods do. A domain adaptation (DA) neural network is designed and trained on the data from both the numerical model and the real structure at the same time. In addition, no damage label of the real structure is needed. Both numerical and laboratory experiments show that the proposed method has excellent performance and outperforms the baseline model, a traditional convolutional neural network (CNN). This paper provides a new methodology to solve the cross‐domain SDD problem, that is, to learn better features instead of just trying to reduce the gap.
Metrics and methods for evaluating model‐driven reality capture plans
Authors: Ibrahim Amir , Golparvar‐Fard Mani , El‐Rayes Khaled 
Published: May 2021

AbstractThis paper presents new metrics and methods for evaluating the quality of reality capture plans—commonly used to operate camera‐mounted unmanned aerial vehicles (UAVs) or ground rovers—for construction progress monitoring and inspection of as‐is conditions. Using 4D building information model (BIM) or 3D reality model as a priori, these metrics provide feedback on the quality of a plan (within a few minutes), accounting for resolution, visibility, accuracy, completeness of the capture, and satisfying battery capacity and line‐of‐sight requirements. A cloud‐based system is introduced to create and optimize UAV/rover missions in the context of prior model. Results from real‐world construction data sets demonstrate that the proposed metrics offer actionable insights into the accuracy and completeness of reality capture plans. Additionally, a capture plan—with a combination of canonical and noncanonical camera views—that satisfies the introduced metrics is statistically correlated with the quality of reconstructed reality. These metrics can improve computer‐vision progress monitoring and inspection methods that rely on the construction site's appearance and geometry.
A deep reinforcement learning approach to mountain railway alignment optimization
Authors: Gao Tianci , Li Zihan , Gao Yan , Schonfeld Paul , Feng Xiaoyun , Wang Qingyuan , He Qing 
Published: May 2021

AbstractThe design and planning of railway alignments is the dominant task in railway construction. However, it is difficult to achieve self‐learning and learning from human experience with manual as well as automated design methods. Also, many existing approaches require predefined numbers of horizontal points of intersection or vertical points of intersection as input. To address these issues, this study employs deep reinforcement learning (DRL) to optimize mountainous railway alignments with the goal of minimizing construction costs. First, in the DRL model, the state of the railway alignment optimization environment is determined, and the action and reward function of the optimization agent are defined along with the corresponding alignment constraints. Second, we integrate a recent DRL algorithm called the deep deterministic policy gradient with optional human experience to obtain the final optimized railway alignment, and the influence of human experience is demonstrated through a sensitivity analysis. Finally, this methodology is applied to a real‐world case study in a mountainous region, and the results verify that the DRL approach used here can automatically explore and optimize the railway alignment, decreasing the construction cost by 17.65% and 7.98%, compared with the manual alignment and with the results of a method based on the distance transform, respectively, while satisfying various alignment constraints.
Factors responsible for difficult to treat superficial fungal infections: A study from a tertiary healthcare centre in India
Authors: Jain Amit , Dhamale Suyog , Sardesai Vidyadhar 
Published: May 2021

AbstractBackgroundRecurrent and clinically unresponsive dermatophytosis is being increasingly observed in India. However, there is little information regarding the extent of the problem and the factors responsible for these difficult to treat superficial fungal infections.AimTo identify factors contributing to difficult to treat recurrent superficial fungal infections.Materials and methodsThis prospective cross‐sectional study enrolled 105 patients of all age groups presenting with either recurrent or long‐standing dermatophyte infection attending the outpatient department of Dermatology, Venerology and Leprosy of Bharati Hospital, Pune, India, between September 2018 and March 2020. Patients were clinically examined, clinical history was taken and questions were asked regarding their current complaints and recorded in a proforma. Data were analysed using the SPSS software package.ResultsThe males outnumbered females (74.3% vs 25.7%). A strong association was observed between the presence of past history and duration of disease (p = .007). The association of use of topical steroids or keratolytic agents with the duration of disease was statistically significant (p = .022). There was a statistically significant inverse association of duration of disease with dermatologist consultation (p < .001). The association between consultation with non‐dermatologist and the duration of disease was statistically significant (p = .035).ConclusionHyperhidrosis, obesity, positive family history, tight clothing and chronic diseases may be considered important factors in acquiring dermatophytic infection. However, when it comes to difficult to treat tinea infections, irrational usage of topical steroids, treatment from non‐dermatologists and a past history of tinea appear to be more critical causative factors. Treatment of dermatophytosis by dermatologists/ trained physicians and increasing general awareness of the public regarding the current situation about tinea in the country would help to alleviate the current crisis.
Implementation of rapid diagnostics assays for detection of histoplasmosis and cryptococcosis in central american people living with HIV
Authors: Caceres Diego H. , Arauz Ana B. , Flores Carlos , Santiago Erika , Montoya Sandra , Saenz Carlos , Torres‐Meneses Felipe A. , Peralta Hortencia , Zuniga‐Moya Julio Cesar , Lainez Arteaga Isis Zohar , Garcia Arturo , Abdo Jose , Verweij Paul E. , Chiller Tom M. , Forno Diana 
Published: May 2021

AbstractObjectivesHistoplasmosis and cryptococcosis are important public health problems in people living with HIV (PLHIV) in Central America. Conventional laboratory assays, based on microscopy and culture, are not optimal for the diagnosis of either disease. However, antigen (Ag) assays are rapid and highly accurate for the diagnosis of these infections.MethodsLaboratory surveillance of PLHIV was carried out in four hospitals in Panama, Honduras and Nicaragua, between 2015 and 2019. Detection of Histoplasma antigens in urine was performed by enzyme immunoassay (EIA), and Cryptococcus antigen detection in sera and cerebrospinal fluid specimens was performed by lateral flow assay (LFA).ResultsA total of 4,453 PLHIV with clinical suspicion of histoplasmosis (n = 1,343) or cryptococcosis (n = 3,110; 2,721 sera and 389 CSF) were tested. Of 1,343 patients suspected of having histoplasmosis, 269 (20%) were Histoplasma Ag positive. Of 3,110 patients tested using the Cryptococcus Ag assay, 329 (11%) were positive. Honduras reported the highest positivity rates (32% for Histoplasma Ag, and 16% for Cryptococcus Ag); Panama reported the largest number of patients testing positive using the Histoplasma Ag assay (n = 201); and Nicaragua reported the largest number of patients testing positive using the Cryptococcus Ag assay (n = 170).ConclusionHere, we show how the implementation of rapid diagnostics assays impacted case detection and was useful for the care of people with advanced HIV. Rapid and accurate diagnosis could reduce mortality associated with histoplasmosis and cryptococcosis in PLHIV.
Gait apraxia as a presenting sign of Gerstmann‐Sträussler‐Scheinker disease
Authors: Fukumoto Tatsuya , Miyamoto Ryosuke , Fujita Koji , Harada Masafumi , Izumi Yuishin 
Published: May 2021

AbstractGerstmann‐Sträussler‐Scheinker disease (GSS) is a rare inherited prion disease that shows variable clinical symptoms, including cerebellar ataxia, dementia, and leg weakness. These symptoms may result in gait disturbance which frequently occurs in the early stage of the disease; however, precise descriptions focused on its phenomenology and etiology have been scarce. Here, we report a unique case of GSS presenting with gait apraxia as the initial symptom. Moreover, SPECT showed hypoperfusion in the bilateral superior frontal gyri, which suggests that dysfunction in the lesions is largely responsible for gait apraxia.
The influence of spirituality and religion on critical care nursing: An integrative review
Authors: Badanta Bárbara , Rivilla‐García Estefanía , Lucchetti Giancarlo , de Diego‐Cordero Rocío 
Published: May 2021

AbstractBackgroundSpiritual care could help family members and critically ill patients to cope with anxiety, stress and depression. However, health care professionals are poorly prepared and health managers are not allocating all the resources needed.Aims and objectivesTo critically review the empirical evidence concerning the influence of spirituality and religion (S‐R) on critical care nursing.MethodsAn integrative review of the literature published in the last 10 years (2010‐2019) was conducted in PubMed, Scopus, CINHAL, PsycINFO, Web of Science, Cochrane and LILACS. In addition, searches were performed in the System for Information on Grey Literature in Europe and the Grey Literature Report. Quantitative and/or qualitative studies, assessing S‐R and including health care professionals caring for critically ill patients (i.e. adults or children), were included.ResultsForty articles were included in the final analysis (20 qualitative, 19 quantitative and 1 with a mixed methodology). The studies embraced the following themes: S‐R importance and the use of coping among critical care patients and families; spiritual needs of patients and families; health care professionals' awareness of spiritual needs; ways to address spiritual care in the intensive care unit (ICU); definition of S‐R by health care professionals; perceptions and barriers of addressing spiritual needs; and influence of S‐R on health care professionals' outcomes and decisions. Our results indicate that patients and their families use S‐R coping strategies to alleviate stressful situations in the ICU and that respecting patients' spiritual beliefs is an essential component of critical care. Although nurses consider spiritual care to be very important, they do not feel prepared to address S‐R and report lack of time as the main barrier.Conclusion and implications for practiceCritical care professionals should be aware about the needs of their patients and should be trained to handle S‐R in clinical practice. Nurses are encouraged to increase their knowledge and awareness towards spiritual issues.
Hydraulic variability of three temperate broadleaf tree species along a water availability gradient in central Europe
Authors: Fuchs Sebastian , Leuschner Christoph , Mathias Link Roman , Schuldt Bernhard 
Published: May 2021

Summary

Plant hydraulic traits are key for understanding and predicting tree drought responses. Information about the degree of the traits’ intra‐specific variability may guide the selection of drought‐resistant genotypes and is crucial for trait‐based modelling approaches.

For the three temperate minor broadleaf tree species Acer platanoides, Carpinus betulus and Tilia cordata, we measured xylem embolism resistance (P50), leaf turgor loss point (PTLP), specific hydraulic conductivity (KS), Huber values (HVs), and hydraulic safety margins in adult trees across a precipitation gradient. We further quantified trait variability on different organizational levels (inter‐specific to within‐canopy variation), and analysed its relationship to climatic and soil water availability.

Although we observed a certain intra‐specific trait variability (ITV) in safety‐related traits (P50, PTLP) with higher within‐tree and between‐tree than between populations variability, the magnitude was small compared to inter‐specific differences, which explained 78.4% and 58.3% of the variance in P50 and PTLP, respectively. In contrast, efficiency‐related traits (KS, HV) showed a high ITV both within populations and within the crowns of single trees. Surprisingly, the observed ITV of all traits was neither driven by climatic nor soil water availability.

In conclusion, the high degree of conservatism in safety‐related traits highlights their potential for trait‐based modelling approaches.
Overloading stress–induced progressive degeneration and self‐repair in condylar cartilage
Authors: Fang Lingli , Ye Yusi , Tan Xi , Huang Lan , He Yao 
Published: May 2021

AbstractOverloading stress–induced condylar cartilage degeneration acts as the main pathologic change in temporomandibular joint osteoarthritis (TMJ‐OA). However, the progression of degeneration and the ability for self‐repair remain poorly understood. Here, we explored the progression of cartilage degeneration by dividing pathological stages using a steady mouth‐opening mouse model. Then, we observed changes of cartilage by removing the loading at different stages to test the potential self‐repair after degeneration induced. Three‐dimensional confocal microscopy combined with histology and micro‐CT scanning was applied to examine TMJ at different stages of degeneration before and after self‐repair. We found the cartilage underwent progressive and thorough degeneration as the overloading stress developed. During the initial adaptation stage, robust proliferation of posteromedial cartilage began at the area of direct loading. Subsequently, widespread chondrocyte apoptosis was found, followed by new chondrocyte proliferation in aggregates with matrix degradation and subchondral bone catabolism. Finally, with cartilage surface damage, the degeneration reached a point where the lesion could not be reversed by self‐repair. While the cartilage nearly returned to normal when the interference was removed within 5 days. These results suggested overloading force induces a pathological process of successive degeneration in TMJ cartilage, which can be reversed by self‐repair at early stages.
Dental long axes using digital dental models compared to cone‐beam computed tomography
Authors: Cong Amalia , Massaro Camila , Ruellas Antonio Carlos de Oliveira , Barkley Mary , Yatabe Marilia , Bianchi Jonas , Ioshida Marcos , Alvarez María Antonia , Aristizabal Juan Fernando , Rey Diego , Cevidanes Lucia 
Published: May 2021

AbstractObjectiveStandard methods of evaluating tooth long axes are not comparable (digital dental models [DDMs], panoramic and cephalometric radiographs) or expose patients to more radiation (cone‐beam computed tomography [CBCT]). This study aimed to compare angular changes in tooth long axes using DDMs vs using CBCTs.Settings and sample populationSecondary data analysis of DDMs and CBCTs, taken before and after orthodontic treatment with piezocision of 24 patients.MethodsAngular changes in tooth long axes were evaluated using landmarks on first molars (centre of the occlusal surface and centre of the furcation), canines and incisors (cusp tip and centre of the root at the cementoenamel junction). Wilcoxon test, intraclass correlation coefficient (ICC) and Bland‐Altman plots were used to test intra‐ and inter‐rater agreement and compare DDM and CBCT measurements.ResultsThe mesiodistal angulation and buccolingual inclination DDM measurements were reproducible. Overall mean differences between DDM and CBCT measurements of mesiodistal angulation, 1.9°±1.5°, and buccolingual inclination, 2.2 ± 2.2°, were not significant for all teeth. ICC between DDM and CBCT measurements ranged from good (0.85 molars) to excellent (0.94 canines; 0.96 incisors). The percentages of measurements outside the range of ±5 were 17.4% for molars, 13.8% for canines and 4.5% for incisors.ConclusionsDDM assessment of changes in tooth long axes has good reproducibility and yields comparable measurements to those obtained from CBCT within a 5° range. These findings lay the groundwork for machine learning approaches that synthesize crown and root canal information towards planning tooth movement without the need for ionizing radiation scans.
A community detection analysis of malocclusion classes from orthodontics and upper airway data
Authors: Di Carlo Gabriele , Gili Tommaso , Caldarelli Guido , Polimeni Antonella , Cattaneo Paolo M. 
Published: May 2021

AbstractObjectiveThe interaction between skeletal class and upper airway has been extensively studied. Nevertheless, this relationship has not been clearly elucidated, with the heterogeneity of results suggesting the existence of different patterns for patients' classification, which has been elusive so far, probably due to oversimplified approaches. Hence, a network analysis was applied to test whether different patterns in patients' grouping exist.Settings and sample populationNinety young adult patients with no obvious signs of respiratory diseases and no previous adeno‐tonsillectomy procedures, with thirty patients characterized as Class I (0 < ANB < 4); 30 Class II (ANB > 4); and 30 as Class III (ANB < 0).Materials and methodsA community detection approach was applied on a graph obtained from a previously analysed sample: thirty‐two measurements (nineteen cephalometric and thirteen upper airways data) were considered.ResultsAn airway‐orthodontic complex network has been obtained by cross‐correlating patients. Before entering the correlation, data were controlled for age and gender using linear regression and standardized. By including or not the upper airway measurements as independent variables, two different community structures were obtained. Each contained five modules, though with different patients' assignments.ConclusionThe community detection algorithm found the existence of more than the three classical skeletal classifications. These results support the development of alternative tools to classify subjects according to their craniofacial morphology. This approach could offer a powerful tool for implementing novel strategies for clinical and research in orthodontics.
Epidemiology of tongue squamous cell carcinoma: A retrospective cohort study
Authors: da Silva Souto Ana Carolina , Vieira Heimlich Fernanda , Lima de Oliveira Leticia , Bergmann Anke , Dias Fernando Luiz , Spíndola Antunes Héliton , de Melo Andreia Cristina , Thuler Luiz Claudio Santos , Cohen Goldemberg Daniel 
Published: May 2021

AbstractObjectiveTo analyze the epidemiological profile and the specific survival of patients diagnosed with tongue squamous cell carcinoma at the National Cancer Institute (INCA).Materials and methodsHospital Cancer Registry System Data and Mortality Information from 2007 to 2009 were retrieved in a retrospective cohort study of patients diagnosed with tongue squamous cell carcinoma. Specific survival was estimated using the Kaplan–Meier method. The association between independent variables and the risk of death was explored in a Cox proportional hazards regression model.ResultsA total of 346 patients were eligible, mostly male (77.5%), smokers (87.6%), with alcohol consumption (80.9%), with low education (65.6%), advanced staging at the time of diagnosis (71.1%), and presenting a high mortality rate (72.5%). In total, 44.5% of patients underwent a surgical approach alone or associated with another treatment modality, of which 85.1% of patients underwent neck dissection and 90.1% had free surgical margins. Specific survival was 40.6% in two years and 31.2% in five years.ConclusionThe 5‐year specific survival was considered worse in individuals over 60 years, and who did not undergo surgical treatment or had surgery associated with another treatment, compared to patients undergoing isolated surgery.
Pattern and localization of perineural invasion predict poor survival in oral tongue carcinoma
Authors: Caponio Vito Carlo Alberto , Troiano Giuseppe , Togni Lucrezia , Zhurakivska Khrystyna , Santarelli Andrea , Laino Luigi , Rubini Corrado , Lo Muzio Lorenzo , Mascitti Marco 
Published: May 2021

AbstractBackgroundSurvival rate for oral tongue squamous cell carcinoma (OTSCC) is still poor and, despite Tumor–Node–Metastasis staging system has been recently updated, patients included under the same stage still show difference in prognosis. Perineural invasion (PNI) emerged to be an indicator of tumor aggressive behavior and unfortunate events. In this study, we investigate the clinic and prognostic value of PNI in a cohort of OTSCC patients.MethodsAbout 200 patients with OTSCC were retrospectively evaluated the presence of PNI. PNI was furtherly descripted as uni‐/multifocal and as intra‐/peritumoral. Disease‐Specific and Relapse‐Free Survival (DSS; RFS) were estimated; moreover, we included PNI in the current AJCC 8th Staging System, improving the prognostication model.ResultsPerineural invasion was found in 40.5% of patients. Intratumoral PNI predicted patients at high risk of being diagnosed with lymph–node metastasis. Tumors with positive PNI reported a worse DSS (Hazard Ratio=1.878, p‐value = 0.008). Moreover, patients exhibiting both multifocal intra‐ and peritumoral PNI reported poorest DSS (Hazard Ratio = 2.409, p‐value = 0.010). Patients were reclassified in a new staging system in case of multifocal PNI, providing better stratification capacity.ConclusionsPerineural invasion might serve as an additional prognostic factor in OTSCC, and by integrating PNI in the staging system, further improvements in prognostication might be reached.