bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of ovarian cancer on individuals and their caregivers: A qualitative analysis
Authors: Tan Jit Hui , Sharpe Louise , Russell Hayley 
Published: September 2020

AbstractObjectiveOvarian cancer remains an understudied cancer with poor prognosis, few effective treatments and little understanding of the how individuals and their families face the challenges and uncertainty following diagnosis. This study synthesized the subjective experiences of individuals and their caregivers in the face of the uncertainty produced by the disease.MethodsQualitative data were obtained from the Ovarian Cancer Australia 2017 Consumer Survey. An inductive thematic analysis was conducted on responses from 219 individuals with ovarian cancer and 78 caregivers.ResultsNine themes were identified from the individual's responses and seven themes from the caregivers. For both groups, the uncertainty created at diagnosis led to a cascade of complex responses. For the individuals, uncertainty gave rise to fears for the future, which were exacerbated by unmet healthcare needs or treatment‐related difficulties. For some individuals, these fears led to disruption to their lives, isolation and emotional distress. For others, helpful coping styles and social support protected them from these negative consequences. For caregivers, the processes were similar, but uncertainty predominantly led to feelings of hopelessness and “survivor guilt.”ConclusionsOur results identified processes that may guide future interventions and research targeting unmet needs and protective factors for individuals with ovarian cancer and their caregivers. Findings also suggest the potential to facilitate effective support between individuals and their caregivers.
Parental attitude and knowledge towards asthma care measures for their children in Saudi Arabia
Authors: Alhammad Abdullah M. , Alajmi Ghada , Alenizi Ahmed , Alrashidi Essa , Alghannam Ghannam , Alaki Emadia , Alsaadi Muslim M , Mayet Ahmed Y. 
Published: September 2020

AbstractBackgroundAppropriate asthma management in children reduces emergency department visits, hospitalization, and improves the quality of life. We aim to assess the level of children asthma control and its association with parental knowledge.MethodsA prospective study conducted to measure childhood asthma control with a validated childhood asthma control test (C‐ACT), and to assess asthma knowledge among the parents of children aged 4–11 years and their parents upon asthma clinic visits. C‐ACT score ≤ 19 is considered as uncontrolled child asthma.ResultsWe have invited 238 parents to participate in the study; 177 (74.4%) completed the survey. The mean age of the parents and their children were 38.8 ± 7.6 and 7.8 ± 2.7 years, respectively; 28.2% of parents were smokers, and 46.3% of them were college graduated. Nearly 61.6% of the parents and children scored ≤ 19 on C‐ACT; 54.2% and 37.9% of parents knew how inhaled salbutamol and corticosteroids work, respectively. A quarter of the parents received an asthma action plan. Multinomial logistic regression analysis showed that parents who did not know their children's medications name (OR, 6.1; 95% CI, 2.15–17.29), and when to use inhaled corticosteroid (OR, 2.1; 95% CI, 1.32–3.45) were independent factors predicting uncontrolled asthma in children with score ≤ 19.ConclusionsThe study indicated that there is an association between poor asthma control (scored ≤ 19 on C‐ACT) and parental knowledge of asthma medications. The parents should be educated thoroughly on asthma care, including medications used to minimize asthma exacerbations in their children.
Tube‐based robust economic model predictive control with practical and relaxed stability guarantees and its application to smart grid
Authors: Sebghati Ashkan , Shamaghdari Saeed 
Published: September 2020

SummaryThis article deals with an improved scheme of tube‐based robust economic model predictive control (TEMPC). The controller is robust to unknown but bounded disturbances where guarantees recursive feasibility, robust stability, and convergence to the economically optimal operating point. Time‐varying economic criteria are considered in the stage cost function of the control design. Initial states of the nominal—nondisturbed—system are considered as decision variables. It lets the controller know more information about the real—disturbance affected—system to take advantage of the recursive horizon approach. It also increases the control degree of freedom and enlarges the region of attraction. Making the closed‐loop system work at the economically optimal operating point contradicts with the economic behavior. A convex optimization problem is represented to keep the economic performance from degradation as much as possible. It modifies the control optimization problem to economic optimally guarantee the closed‐loop robust stability, which is called practical stability. It is shown that more economic behavior could be achieved under some conditions by relaxing the stability but maintaining the recursive feasibility guarantee, which is called relaxed stability. To show the efficiency of the proposed method, it is applied to the building energy management of smart grid. A commercial microgrid with battery energy storage dynamics and refrigeration dynamics of a supermarket are considered as a smart building system where the time‐varying electricity price of the main grid is considered in the objective function. The results show valuable achievements in the TEMPC economic performance.
Moving horizon estimation with multirate measurements and correlated noises
Authors: Zou Lei , Wang Zidong , Dong Hongli , Han Qing‐Long 
Published: September 2020

SummaryThis article is concerned with the moving horizon estimation (MHE) problem for a class of linear discrete‐time systems subject to multirate measurements and correlated noises. The sensors of the plant are grouped into two nodes with different sampling periods, which give rise to the multirate measurements. Under the effects of multirate measurements, the underlying system is then described by a periodic system with correlated noises. A MHE strategy is formulated and the corresponding analytical solution of the state estimation is derived by using the “completing the square” technique. Based on the lifting approach, the dynamics of the estimation error covariance is analyzed and the desired estimator parameters are obtained by solving a set of linear matrix inequalities. An illustrative example is given to show the effectiveness of our proposed MHE method.
Performance of variable and function selection methods for estimating the nonlinear health effects of correlated chemical mixtures: A simulation study
Authors: Lazarevic Nina , Knibbs Luke D. , Sly Peter D. , Barnett Adrian G. 
Published: September 2020

Statistical methods for identifying harmful chemicals in a correlated mixture often assume linearity in exposure‐response relationships. Nonmonotonic relationships are increasingly recognized (eg, for endocrine‐disrupting chemicals); however, the impact of nonmonotonicity on exposure selection has not been evaluated. In a simulation study, we assessed the performance of Bayesian kernel machine regression (BKMR), Bayesian additive regression trees (BART), Bayesian structured additive regression with spike‐slab priors (BSTARSS), generalized additive models with double penalty (GAMDP) and thin plate shrinkage smoothers (GAMTS), multivariate adaptive regression splines (MARS), and lasso penalized regression. We simulated realistic exposure data based on pregnancy exposure to 17 phthalates and phenols in the US National Health and Nutrition Examination Survey using a multivariate copula. We simulated data sets of size N = 250 and compared methods across 32 scenarios, varying by model size and sparsity, signal‐to‐noise ratio, correlation structure, and exposure‐response relationship shapes. We compared methods in terms of their sensitivity, specificity, and estimation accuracy. In most scenarios, BKMR, BSTARSS, GAMDP, and GAMTS achieved moderate to high sensitivity (0.52‐0.98) and specificity (0.21‐0.99). BART and MARS achieved high specificity (≥0.90), but low sensitivity in low signal‐to‐noise ratio scenarios (0.20‐0.51). Lasso was highly sensitive (0.71‐0.99), except for quadratic relationships (≤0.27). Penalized regression methods that assume linearity, such as lasso, may not be suitable for studies of environmental chemicals hypothesized to have nonmonotonic relationships with outcomes. Instead, BKMR, BSTARSS, GAMDP, and GAMTS are attractive methods for flexibly estimating the shapes of exposure‐response relationships and selecting among correlated exposures.
Discovery of Novel Procaine‐Imidazole Derivative as Inhibitor of Monoamine Oxidase‐B for Potential Benefit in Parkinson's Disease
Authors: Wu Jiane , Liu Qionghua , Hu Yuping , Wang Wenhua , Gao Xinming 
Published: September 2020

AbstractThe clinically utility of selective monoamine oxidase (MAO)‐B inhibitors in Parkinson disease is widely recognized due to significant improvement in altered motor function and long‐term benefit. Therefore, in the present study, a series of procaine‐imidazole was synthesized and subsequently evaluated for MAO‐A and MAO‐B inhibitory activity in an enzymatic assay. Comparative inhibitory activity suggest that, target compounds selectively inhibit MAO‐B, as compared to MAO‐A. Among the tested derivatives, compound 8 i (2‐(diethylamino)ethyl4‐(4‐(4‐fluorophenyl)‐2‐(4‐hydroxyphenyl)‐1H‐imidazol‐1‐yl)benzoate) selectively inhibited MAO‐B with IC50 of 0.032±0.002 (selectivity index over MAO‐A=475). The anti‐Parkinson effect of compound 8 i was further evaluated in MPTP (1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine) induced animal model of PD. It has been found that, compound 8 i causes significant improvement in motor function of mice as revealed by motor behavioral assessment using the footprint and horizontal wire test. Compound 8 i also improved the level of anti‐oxidant enzymes in the striatum of animal brains. Our study demonstrated the development of procaine‐imidazole derivatives as potent and selective MAO‐B inhibitor as potential agent against PD.
Base Promoted Cascade Reaction: A Convenient Route to Hybrid S and N Polyheterocycles
Authors: Jayarajan Ramasamy , Kottha Thirumalaswamy , Subbaramanian Sabarinathan , Vasuki Gnanasambandam 
Published: September 2020

AbstractBiologically privileged fused pyrimidine spirocycles were synthesized via a metal‐free three‐component cascade reaction utilizing mercapto/aza lactam active methylene compounds. This rapid and efficient one‐pot operation quickly delivered seven different polycyclic and spirocyclic scaffolds such as pyranothiazolopyrimidine, benzothiazolopyranopyrimidine, pyranotriazolopyrimidine, benzoimidazolopyranopyrimidine, spiroindolinepyranothiazolopyrimidine, spirobenzothiazolopyranopyrimidineindoline, and spirobenzo‐imidazolopyranopyrimidineindoline at room temperature with excellent regio/chemoselectivity.
Quantum Anomalous Hall Effect in Magnetic Doped Topological Insulators and Ferromagnetic Spin‐Gapless Semiconductors—A Perspective Review
Authors: Nadeem Muhammad , Hamilton Alex R. , Fuhrer Michael S. , Wang Xiaolin 
Published: September 2020

AbstractQuantum anomalous Hall effect, with a trademark of dissipationless chiral edge states for electronics/spintronics transport applications, can be realized in materials with large spin–orbit coupling and strong intrinsic magnetization. After Haldane's seminal proposal, several models have been presented to control/enhance the spin–orbit coupling and intrinsic magnetic exchange interaction. After brief introduction of Haldane model for spineless fermions, following three fundamental quantum anomalous Hall models are discussed in this perspective review: i) low‐energy effective four band model for magnetic‐doped topological insulator (Bi,Sb)2Te3 thin films, ii) four band tight‐binding model for graphene with magnetic adatoms, and iii) two (three) band spinful tight‐binding model for ferromagnetic spin‐gapless semiconductors with honeycomb (kagome) lattice where ground state is intrinsically ferromagnetic. These models cover 2D Dirac materials hosting spinless, spinful, and spin‐degenerate Dirac points where various mass terms open bandgap and lead to quantum anomalous Hall effect. With emphasis on the topological phase transition driven by ferromagnetic exchange interaction and its interplay with spin–orbit‐coupling, various symmetry constraints on the nature of mass term and the materialization of these models are discussed. This study will shed light on the fundamental theoretical perspectives of quantum anomalous Hall materials.
High Carbonization Temperature to Trigger Enzyme Mimicking Activities of Silk‐Derived Nanosheets
Authors: Xiong Xueqing , Tang Yonghua , Xu Chengjie , Huang Yanyan , Wang Yupeng , Fu Lianlian , Lin Changxu , Zhou Dongfang , Lin Youhui 
Published: September 2020

AbstractHerein, it is demonstrated that N‐rich carbonized silk fibroin materials (CSFs) can serve as efficient peroxidase, and oxidase mimics. Their enzyme‐like activities are highly dependent on carbonization conditions. CSFs obtained at low temperatures do not exhibit significant catalytic reactivity, while their enzyme‐like catalysis performance is greatly activated after high‐temperature treatment. Such a phenomenon is mainly ascribed to the increase of graphitization degree and graphitic nitrogen and the emergence of disordered graphitic structures during the formation of turbostratic carbon. In addition, inspired by the excellent photothermal conversion efficiency, and temperature‐dependent catalytic behavior of CSFs, near‐infrared light can be used to remotely control their enzyme‐like activities. More importantly, as‐prepared robust silk‐derived nanosheets can be applied to photothermal‐catalytic cancer therapy and sensing. It is believed that such a smart artificial enzyme system will throw up exciting new opportunities for the chemical industry and biotechnology.
Angular Trapping of Spherical Janus Particles
Authors: Gao Xiaoqing , Wang Yali , He Xuehao , Xu Mengjun , Zhu Jintao , Hu Xiaodong , Hu Xiaotang , Li Hongbin , Hu Chunguang 
Published: September 2020

AbstractDeveloping angular trapping methods, which enable optical tweezers to rotate a micronsized bead, is of great importance for studies of biomacromolecules in a wide range of torque‐generation processes. Here a novel controlled angular trapping method based on model composite Janus particles is reported, which consist of two hemispheres made of polystyrene and poly(methyl methacrylate). Through computational and experimental studies, the feasibility to control the rotation of a Janus particle in a linearly polarized laser trap is demonstrated. The results show that the Janus particle aligned its two hemispheres interface parallel to the laser propagation direction and polarization direction. The rotational state of the particle can be directly visualized by using a camera. The rotation of the Janus particle in the laser trap can be fully controlled in real time by controlling the laser polarization direction. The newly developed angular trapping technique has the great advantage of easy implementation and real‐time controllability. Considering the easy chemical preparation of Janus particles and implementation of the angular trapping, this novel method has the potential of becoming a general angular trapping method. It is anticipated that this new method will significantly broaden the availability of angular trapping in the biophysics community.
Easily solving dynamic programming problems in Haskell by memoization of hylomorphisms
Authors: Llorens David , Vilar Juan Miguel 
Published: September 2020

SummaryDynamic programming is a well‐known algorithmic technique that solves problems by a combination of dividing a problem into subproblems and using memoization to avoid an exponential growth of the costs. We show how to implement dynamic programming in Haskell using a variation of hylomorphisms that includes memoization. Our implementation uses polymorphism so the same function can return the best score or the solution to the problem based on the type of the returned value.
Teacher learning in communities of practice: The affordances of co‐planning for novice and veteran teachers' learning
Authors: Eshchar‐Netz Livat , Vedder‐Weiss Dana 
Published: September 2020

AbstractCollaborative reflective inquiry in teacher communities of practice (CoP) supports their professional situated learning. However, the CoP model entails at least three limitations and challenges for teacher learning: novice teachers can seldom act as legitimate peripheral participants since they are obliged to do the same work that veterans do; veterans' learning is neglected since they are expected to teach the novices; and power dynamics between veterans and novices may constrain the group's reflective inquiry and, consequently, its learning. In this case‐study, we explore the dynamics between veteran and novice science teachers in a purposefully sampled case of three teachers engaged in collaborative planning in a professional development community. We examine the implications of these dynamics for the group's reflective inquiry, using linguistic ethnographic micro‐analytic methods to analyze audio‐ and video‐recordings of the planning session. The findings demonstrate how in a collaborative planning context, legitimate peripheral participation is afforded, thereby mitigating face threats and supporting learning for both novice and veteran teachers. The study highlights the unique affordances of collaborative planning for science teachers' reflective inquiry, advancing our understanding of the social dimension of teacher learning. This study contributes to the fields of teacher learning in CoPs and teacher planning.
Soil hydraulic properties estimation from one‐dimensional infiltration experiments using characteristic time concept
Authors: Rahmati Mehdi , Vanderborght Jan , Šimůnek Jirka , Vrugt Jasper A. , Moret‐Fernández David , Latorre Borja , Lassabatere Laurent , Vereecken Harry 
Published: September 2020

AbstractMany different equations ranging from simple empirical to semi‐analytical solutions of the Richards equation have been proposed for quantitative description of water infiltration into variably saturated soils. The sorptivity, S, and the saturated hydraulic conductivity, Ks, in these equations are typically unknown and have to be estimated from measured data. In this paper, we use so‐called characteristic time (tchar) to design a new method, referred to as the characteristic time method (CTM) that estimates S, and Ks, from one‐dimensional (1D) cumulative infiltration data. We demonstrate the usefulness and power of the CTM by comparing it with a suite of existing methods using synthetic cumulative infiltration data simulated by HYDRUS‐1D for 12 synthetic soils reflecting different USDA textural classes, as well as experimental data selected from the Soil Water Infiltration Global (SWIG) database. Results demonstrate that the inferred values of S and Ks are in excellent agreement with their theoretical values used in the synthetically simulated infiltration experiments with Nash–Sutcliffe criterion close to unity and RMSE values of 0.04 cm h−1/2 and 0.05 cm h−1, respectively. The CTM also showed very high accuracy when applied on synthetic data with added measurement noise, as well as robustness when applied to experimental data. Unlike previously published methods, the CTM does not require knowledge of the time validity of the applied semi‐analytical solution for infiltration and, therefore, is applicable to infiltrations with durations from 5 min to several days. A script written in Python of the CTM method is provided in the supplemental material.
Nano‐sensing and nano‐therapy targeting central players in iron homeostasis
Authors: Wu Linyuan , Li Yan , Gu Ning 
Published: September 2020

AbstractIron plays vital roles in many life activities and it is strictly controlled via elaborate metabolic system. Growing evidence has suggested that the dysfunctional iron homeostasis is implicated to many refractory diseases including cancers and neurodegenerations. Systemic and cellular iron are regulated through different pathways but are meanwhile interconnecting with each other via a few key regulators, whose abnormal expressions are often found to be the root causes of many iron disorders. Nano‐sensing techniques have enabled the detection and monitoring of such central players, which provide rich information for the iron homeostasis profile through multiplexing and flexible designs. In addition to general sensing, nanoprobes are capable of target imaging and precise local access, which are particularly beneficial for revealing the conditions of intra‐/extracellular environments. Nanomaterials have also been applied in some therapies, targeting the aberrant iron metabolism. Various iron uptake pathways have been utilized for target drug delivery and iron level manipulation, while abnormal iron content is notably useful in tumor killing. With brief introduction to the significance of iron homeostasis, this review includes recent works regarding the nanotechnology that has been applied in iron‐related diagnostic and therapeutic applications.This article is categorized under:
Diagnostic Tools > Biosensing
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Diagnostic Tools > in vivo Nanodiagnostics and Imaging
Estimating Migration Impacts of Wildfire: California’s 2017 North Bay Fires
Authors: Sharygin Ethan 
Published: September 2020

AbstractThis chapter examines a cluster of wildfire conflagrations that hit northern California during October 2017, which resulted in significant loss of housing units (6874 residential structures destroyed or damaged). To assess the magnitude of the migration response and network of destinations, a method to estimate migration drawing from a proxy universe of households with students enrolled in public schools was proposed, using data on school exits and re-enrollments from a longitudinal student database. The analysis finds that a small minority of households affected by the fires moved out of the area. Out of nearly 7800 persons displaced by the central fire complex in one city, this study estimated fewer than 1000 changed neighborhoods; of those, fewer than 500 moved out of Sonoma County. These findings are applicable to other wildfires and localized disasters where a substantial portion of housing is lost but public infrastructure in the region remains intact.
Disasters and Demographic Change of ‘Single-Industry’ Towns—Decline and Resilience in Morwell, Australia
Authors: Bird Deanne , Taylor Andrew 
Published: September 2020

Abstract
In 2014, an open-cut coal mine fire burned for 45 days in the small single-industry town of Hazelwood in Victoria (Australia) spreading smoke and ash across the adjacent community of Morwell. This chapter examines the extent to which the mine fire acted as a catalyst for demographic and socio-economic change and considers how, if at all, it impacted Morwell’s resilience to disasters. We report on a range of secondary data analyses augmented with qualitative insights captured in government reports (namely, the Hazelwood Mine Fire Inquiry reports), as well as from related research papers and media articles. We suggest that a succession of structural and demographic changes meant that the town and its residents were accustomed and resilient to relatively large shocks. In this sense, the Morwell and broader Latrobe Valley population banded together around various community-led initiatives to fight for a better future for their community.