bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biochar and alternate partial root-zone irrigation greatly enhance the effectiveness of mulberry in remediating lead-contaminated soils
Authors: Wang Lei , Dang Qing-Lai , Tedla Binyam 
Published: September 2020

Abstract

Aims
Soil lead contamination has become increasingly serious and phytoremediation can provide an effective way to reclaim the contaminated soils. This study aims to examine the growth, lead resistance and lead accumulation of mulberry (Morus alba L.) seedlings at four levels of soil lead contamination with or without biochar addition under normal or alternative partial root-zone irrigation (APRI).

Methods
We conducted a three-factor greenhouse experiment with biochar (with vs. without biochar addition), irrigation method (APRI vs. normal irrigation) and four levels of soil lead (0, 50, 200 and 800 mg·kg−1). The performance of the seedlings under different treatments was evaluated by measuring growth traits, osmotic substances, antioxidant enzymes and lead accumulation and translocation.

Important Findings
The results reveal that mulberry had a strong ability to acclimate to soil lead contamination, and that biochar and APRI synergistically increased the biomass and surface area of absorption root across all levels of soil lead. The seedlings were able to resist the severe soil lead contamination (800 mg·kg−1 Pb) by adjusting glutathione metabolism, and enhancing the osmotic and oxidative regulating capacity via increasing proline content and the peroxidase activity. Lead ions in the seedlings were primarily concentrated in roots and exhibited a dose–effect associated with the lead concentration in the soil. Pb, biochar and ARPI interactively affected Pb concentrations in leaves and roots, translocation factor and bioconcentration. Our results suggest that planting mulberry trees in combination with biochar addition and APRI can be used to effectively remediate lead-contaminated soils.
The Needle in the Haystack: Identifying Credible Mobile Health Apps for Pediatric Populations during a Pandemic and beyond
Authors: Psihogios Alexandra M , Stiles-Shields Colleen , Neary Martha 
Published: September 2020

Abstract

Background
The COVID-19 pandemic has ignited wider clinical adoption of digital health tools, including mobile health apps (mHealth apps), to address mental and behavioral health concerns at a distance. While mHealth apps offer many compelling benefits, identifying effective apps in the crowded and largely unregulated marketplace is laborious. Consumer demand and industry productivity are increasing, although research is slower, making it challenging for providers to determine the most credible and safe apps for patients in need.

Objectives/Methods
This commentary offers a practical, empirically guided framework and associated resources for selecting appropriate mHealth apps for pediatric populations during the pandemic and beyond.

Results
In the first stage, Narrow the target problem, end user, and contender apps. Beginning the search with continuously updated websites that contain expert app ratings can help expedite this process (e.g., Psyberguide). Second, Explore each contender app’s: (a) scientific and theoretical support (e.g., are app components consistent with health behavior change theories?), (b) privacy policies, and (c) user experience (e.g., through crowdsourcing feedback about app usability and appeal via social media). Third, use clinical expertise and stakeholder feedback to Contextualize whether the selected app is a good fit for a particular patient and/or caregiver (e.g., by considering age, race/ethnicity, ability, gender, sexual orientation, technology access), including conducting a brief self-pilot of the app.

Conclusion
Youth are increasingly turning to technology for support, especially during the pandemic, and pediatric psychologists must be primed to recommend the most credible tools. We offer additional recommendations for rapidly disseminating evidence-based apps to the public.
‘Not one action but many’: institutional work by commissioners of children's mental health services in the English NHS
Authors: Passey Andrew 
Published: September 2020

Abstract
This article enhances our understanding of institutional work, through a study of professional health commissioners in the English National Health Service. Using a case study of mental health policy implementation, commissioners are conceptualized as institutional agents involved in shaping the organizational field and its boundary. Health service commissioners face a series of challenges as institutional agents. Commissioning is a relatively new health profession. It lacks a strong professional association and has predominantly been externally professionalized. Commissioners have limited direct organizational strategic management control. In the case study, commissioners were charged with leading implementation of the policy, which required them to address fragmentation in the field. Using existing typologies as an analytical frame, activities by commissioners in the case study are identified and explored as different modes of institutional work. Commissioners created a new normative network and instigated specific processes to embed and routinize cross-organization working. They undertook boundary-spanning cognitive institutional work, creating new knowledge by commissioning education of school staff in the basics of children’s mental health. Their institutional work involved challenging existing working practices, both in the health field and in the contiguous education field. The article elucidates connections between different modes of institutional work and attends to boundary work by commissioners in parallel with institutional work in the field. It also outlines how a profession seemingly lacking many of the ingredients of institutional power might pursue its own professional project through institutional work. Findings have resonance in other geographical and policy areas and fields.
Reversible regulation of conjugation of Bacillus subtilis plasmid pLS20 by the quorum sensing peptide responsive anti-repressor RappLS20
Authors: Singh Praveen K , Serrano Ester , Ramachandran Gayetri , Miguel-Arribas Andrés , Gago-Cordoba César , Val-Calvo Jorge , López-Pérez Arancha , Alfonso Carlos , Wu Ling Juan , Luque-Ortega Juan R , Meijer Wilfried J J 
Published: September 2020

AbstractQuorum sensing plays crucial roles in bacterial communication including in the process of conjugation, which has large economical and health-related impacts by spreading antibiotic resistance. The conjugative Bacillus subtilis plasmid pLS20 uses quorum sensing to determine when to activate the conjugation genes. The main conjugation promoter, Pc, is by default repressed by a regulator RcopLS20 involving DNA looping. A plasmid-encoded signalling peptide, Phr*pLS20, inactivates the anti-repressor of RcopLS20, named RappLS20, which belongs to the large group of RRNPP family of regulatory proteins. Here we show that DNA looping occurs through interactions between two RcopLS20 tetramers, each bound to an operator site. We determined the relative promoter strengths for all the promoters involved in synthesizing the regulatory proteins of the conjugation genes, and constructed an in vivo system uncoupling these regulatory genes to show that RappLS20 is sufficient for activating conjugation in vivo. We also show that RappLS20 actively detaches RcopLS20 from DNA by preferentially acting on the RcopLS20 molecules involved in DNA looping, resulting in sequestration but not inactivation of RcopLS20. Finally, results presented here in combination with our previous results show that activation of conjugation inhibits competence and competence development inhibits conjugation, indicating that both processes are mutually exclusive.
A Major Regional Measles Outbreak: Description of Hospitalized Cases in 2017–2018 at Bordeaux University Hospital, France
Authors: Barthod Laure , Fourgeaud Jacques , Puges Mathilde , Rogues Anne-Marie , Coppry Maïder , Sarlangue Jean , Boyer Alexandre , Neau Didier , Vabret Astrid , Dina Julia , Lafon Marie-Edith , Cazanave Charles 
Published: September 2020

Abstract

Background
Measles remains endemic worldwide, despite current vaccination recommendations, and is associated with high morbidity and mortality rates. We describe all cases hospitalized in Bordeaux University Hospital (BUH), the starting point of a national significant measles outbreak in 2017–2018.

Methods
In this retrospective study, we included all patients hospitalized in BUH from September 1, 2017, to May 31, 2018. Inclusion criteria were age &gt;1 year, clinical symptoms, and biological confirmation by measles immunoglobulin M or measles reverse transcription polymerase chain reaction positivity.

Results
We included 171 patients. Most patients were immunocompetent; only 19% had preexisting medical histories. Most patients had rash and fever (97%), but some cases were atypical and difficult to diagnose. Köplik’s spots were reported in 66 cases (38%). The most frequent biological markers were blood inflammation markers (96%) and lymphopenia (81%). Unexpectedly, we found hyponatremia (&lt;135 mmol/L) in 40% of patients. We identified peaks in January and March, corresponding to 76 D8 genotypes and 28 B3 strains. The following complications were reported in 65 patients (38%): pneumonia, hepatitis, and keratitis; 10 had neurological symptoms. One patient had Guillain-Barré syndrome, and a young immunocompromised patient died from measles inclusion-body encephalitis. Most of the patients (80%) had not been correctly vaccinated, including 28 health care workers. Some patients (n = 43, 25%) developed measles despite having plasma IgG. These included 12 possible vaccination failure cases.

Conclusions
During the BUH outbreak, measles was often complicated and sometimes atypical. Vaccination coverage was dramatically insufficient. We also describe vaccination failure cases that must be better investigated.
Incidence of Health Care–Associated COVID-19 During Universal Testing of Medical and Surgical Admissions in a Large US Health System
Authors: Long Dustin R , O’Reilly-Shah Vikas , Rustagi Alison S , Bryson-Cahn Chloe , Jerome Keith R , Weiss Noel S , Sunshine Jacob E 
Published: September 2020

Abstract
Concerns about severe acute respiratory syndrome coronavirus 2 exposure in health care settings may cause patients to delay care. Among 2992 patients testing negative on admission to an academic, 3-hospital system, 8 tested positive during hospitalization or within 14 days postdischarge. Following adjudication of each instance, health care–associated infection incidence ranged from 0.8 to 5.0 cases per 10 000 patient-days.
Small sleepers, big data: leveraging big data to explore sleep-disordered breathing in infants and young children
Authors: Ehsan Zarmina , Glynn Earl F , Hoffman Mark A , Ingram David G , Al-Shawwa Baha 
Published: September 2020

Abstract

Study Objectives
Infants represent an understudied minority in sleep-disordered breathing (SDB) research and yet the disease can have a significant impact on health over the formative years of neurocognitive development that follow. Herein we report data on SDB in this population using a big data approach.

Methods
Data were abstracted using the Cerner Health Facts database. Demographics, sleep diagnoses, comorbid medication conditions, healthcare utilization, and economic outcomes are reported.

Results
In a cohort of 68.7 million unique patients, over a 9-year period, there were 9,773 infants and young children with a diagnosis of SDB (obstructive sleep apnea [OSA], nonobstructive sleep apnea, and “other” sleep apnea) who met inclusion criteria, encompassing 17,574 encounters, and a total of 27,290 diagnoses across 62 U.S. health systems, 172 facilities, and 3 patient encounter types (inpatient, clinic, and outpatient). Thirty-nine percent were female. Thirty-nine percent were ≤1 year of age (6,429 infants), 50% were 1–2 years of age, and 11% were 2 years of age. The most common comorbid diagnoses were micrognathia, congenital airway abnormalities, gastroesophageal reflux, chronic tonsillitis/adenoiditis, and anomalies of the respiratory system. Payor mix was dominated by government-funded entities.

Conclusions
We have used a novel resource, large-scale aggregate, de-identified EHR data, to examine SDB. In this population, SDB is multifactorial, closely linked to comorbid medical conditions and may contribute to a significant burden of healthcare costs. Further research focusing on infants at highest risk for SDB can help target resources and facilitate personalized management.
Melanopsin-dependent phototransduction is impaired in delayed sleep–wake phase disorder and sighted non–24-hour sleep–wake rhythm disorder
Authors: Abbott Sabra M , Choi Jin , Wilson John , Zee Phyllis C 
Published: September 2020

Abstract

Study Objectives
The circadian system must perform daily adjustments to align sleep–wake and other physiologic rhythms with the environmental light–dark cycle: This is mediated primarily through melanopsin containing intrinsically photosensitive retinal ganglion cells. Individuals with delayed sleep–wake phase disorder (DSWPD) exhibit a delay in sleep–wake timing relative to the average population, while those with sighted non–24-hour sleep–wake rhythm disorder (N24SWD) exhibit progressive delays. An inability to maintain appropriate entrainment is a characteristic of both disorders. In this study, we test the hypothesis that individuals with DSWPD exhibit alteration in melanopsin-dependent retinal photo-transduction as measured with the postillumination pupil response (PIPR).

Methods
Twenty-one control and 29 participants with DSWPD were recruited from the community and clinic. Of the 29 DSWPD participants, 17 reported a history of N24SWD. A pupillometer was used to measure the PIPR in response to a bright 30-second blue or red-light stimulus. The PIPR was calculated as the difference in average pupil diameter at baseline and 10–40 seconds after light stimulus offset.

Results
The PIPR was significantly reduced in the DSWPD group when compared with the control group (1.26 ± 1.11 mm vs 2.05 ± 1.04 mm, p &lt; 0.05, t-test). The PIPR was significantly reduced in the sighted N24SWD subgroup when compared with individuals with the history of only DSWPD (0.88 ± 0.58 mm vs 1.82 ± 1.44 mm, p &lt; 0.05, analysis of variance [ANOVA]) or controls (0.88 ± 0.58 mm vs 2.05 ± 1.04 mm, p &lt; 0.01, ANOVA).

Conclusions
These results indicate that reduced melanopsin-dependent retinal photo-transduction may be a novel mechanism involved in the development of DSWPD and sighted N24SWD.
Use of a Support Surface Standard to Test the Effects of a Turning and Positioning Device Versus Low-Air-Loss Therapy on Temperature and Humidity
Authors: Call Evan , Oberg Craig , Rappl Laurie M. 
Published: September 2020

ABSTRACT

BACKGROUND
Turning and repositioning devices (TRDs) help to reduce strain on caregivers, but clinicians question their effects on humidity and temperature (microclimate) at the skin surface that may increase risk of pressure ulcers.

OBJECTIVE
To pilot the use of a standard test for support surfaces to compare microclimate at the skin surface in three scenarios: (1) on a low-air-loss (LAL) surface, (2) on a representative TRD with a basic underpad (TRDU) placed on a LAL surface, and (3) on a negative control with full occlusion. The results are designed to inform clinical decision-making in using a TRD on a LAL surface and the viability of using this test to study TRDs.

DESIGN
Measuring humidity and temperature at the device-surface interface using a heated moisture-exuding bronze thermodynamic human model in a laboratory setting.

MAIN OUTCOME MEASURE
Humidity and temperature levels across 3 hours 15 minutes of continuous loading with a 45-second complete unloading to simulate a position change at 3 hours.

MAIN RESULTS
Relative humidity on the TRDU was below that on the LAL surface for the first 110 minutes and was markedly lower than the negative control for the remainder of humidity testing. Temperature on the TRDU was well below the negative control and negligibly higher than the surface alone throughout testing. The position change enhanced the effects of the TRDU.

CONCLUSIONS
The support surface standard test appears useful in evaluating TRDs. This TRD along with the basic underpad is more comparable to a LAL surface than to full occlusion in managing the microclimate of the skin and pressure ulcer risk.
Wireless power transfer-based eddy current non-destructive testing using a flexible printed coil array
Authors: Daura Lawal Umar , Tian GuiYun , Yi Qiuji , Sophian Ali 
Published: September 2020

Eddy current testing (ECT) has been employed as a traditional non-destructive testing and evaluation (NDT&E) tool for many years. It has developed from single frequency to multiple frequencies, and eventually to pulsed and swept-frequency excitation. Recent progression of wireless power transfer (WPT) and flexible printed devices open opportunities to address challenges of defect detection and reconstruction under complex geometric situations. In this paper, a transmitter–receiver (Tx–Rx) flexible printed coil (FPC) array that uses the WPT approach featuring dual resonance responses for the first time has been proposed. The dual resonance responses can provide multiple parameters of samples, such as defect characteristics, lift-offs and material properties, while the flexible coil array allows area mapping of complex structures. To validate the proposed approach, experimental investigations of a single excitation coil with multiple receiving coils using the WPT principle were conducted on a curved pipe surface with a natural dent defect. The FPC array has one single excitation coil and 16 receiving (Rx) coils, which are used to measure the dent by using 21 C-scan points on the dedicated dent sample. The experimental data were then used for training and evaluation of dual resonance responses in terms of multiple feature extraction, selection and fusion for quantitative NDE. Four features, which include resonant magnitudes and principal components of the two resonant areas, were investigated for mapping and reconstructing the defective dent through correlation analysis for feature selection and feature fusion by deep learning. It shows that deep learning-based multiple feature fusion has outstanding performance for 3D defect reconstruction of WPT-based FPC-ECT.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Machine learning at the interface of structural health monitoring and non-destructive evaluation
Authors: Gardner P. , Fuentes R. , Dervilis N. , Mineo C. , Pierce S.G. , Cross E.J. , Worden K. 
Published: September 2020

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Analysis of electromagnetic non-destructive evaluation modelling using Stratton-Chu formulation-based fast algorithm
Authors: Bao Yang , Song Jiming 
Published: September 2020

The eddy current non-destructive evaluation (NDE) modelling using Stratton-Chu formulation-based fast algorithm is analysed. Stratton-Chu formulations, which have no low frequency breakdown issue, are selected for modelling electromagnetic NDE problems with low frequency and high conductivity approximations. As the main contribution of this article, the robustness and efficiency of the approximations, which result in big savings in both memory and CPU time, are validated and analysed using examples from practical EC testing. The boundary element method (BEM) is used to discretize the integral equations into a linear system of equations: the first order Rao-Wilton-Glisson (RWG) vector basis functions with the flat triangle meshes of the object and pulse basis functions are selected to expand the equivalent surface currents and the normal component of magnetic fields, respectively. Then the multilevel adaptive cross approximation (MLACA) algorithm is applied to accelerate the iterative solution process. The performance and efficiency of adaptively applying a multi-stage (level) algorithm based on the criteria concluded for the operators are shown.This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Hierarchical low-rank and sparse tensor micro defects decomposition by electromagnetic thermography imaging system
Authors: Wu Tongle , Gao Bin , Woo Wai Lok 
Published: September 2020

With the advancement of electromagnetic induction thermography and imaging technology in non-destructive testing field, this system has significantly benefitted modern industries in fast and contactless defects detection. However, due to the limitations of front-end hardware experimental equipment and the complicated test pieces, these have brought forth new challenges to the detection process. Making use of the spatio-temporal video data captured by the thermal imaging device and linking it with advanced video processing algorithm to defects detection has become a necessary alternative way to solve these detection challenges. The extremely weak and sparse defect signal is buried in complex background with the presence of strong noise in the real experimental scene has prevented progress to be made in defects detection. In this paper, we propose a novel hierarchical low-rank and sparse tensor decomposition method to mine anomalous patterns in the induction thermography stream for defects detection. The proposed algorithm offers advantages not only in suppressing the interference of strong background and sharpens the visual features of defects, but also overcoming the problems of over- and under-sparseness suffered by similar state-of-the-art algorithms. Real-time natural defect detection experiments have been conducted to verify that the proposed algorithm is more efficient and accurate than existing algorithms in terms of visual presentations and evaluation criteria.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.