bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expanding health insurance for the elderly of the Philippines
Authors: Abrigo Michael R.M. , Halliday Timothy J. , Molina Teresa 
Published: September 2021

SummaryThis paper evaluates a Filipino policy that expanded health insurance coverage of its senior citizens, aged 60 and older, in 2014. We employ an instrumental variables estimator in which the first stage is a difference‐in‐differences specification that exploits the age discontinuity at age 60, along with data from before and after the policy. First stage results show the expansion increased insurance coverage by approximately 16 percentage points. The compliers, those induced by the policy to obtain insurance, were disproportionately female and largely from the middle of the socioeconomic distribution. Second stage regressions indicate that out‐of‐pocket medical expenditures more than doubled among the compliers. We argue that this is most likely driven by an outward shift in the medical demand curve.
Strain rate effects on thermoplastic composites with mechanical interlocking
Authors: Kothari Anmol , Choi Hongseok , Zhao Huijuan , Joseph Paul , Li Gang 
Published: September 2021

AbstractFiber reinforced thermoplastic composites are limited due to poor interfacial bonding between the nonpolar/nonreactive polymer matrix and fiber surface. Recently, a concept of controlled mechanical interlocking between fiber and matrix surface was proposed to improve the interfacial bonding in fiber reinforced thermoplastic composites. Study results show promising performance of the approach under static loading conditions. In this work, we study the effect of strain rate on the interfacial bonding behavior under dynamic loading conditions. A parametric study of the strain rate effect is performed for which different surface microarchitectures of a glass/polypropylene composite system are considered. A three network model is implemented for modeling mechanical behavior of polymer, which is calibrated using a set of stress–strain curves experimentally obtained at various strain rates. The strength calculations address both polymer fracture and detachment of the polymer matrix from the anchoring sites. The results show that under the strain rates ranging from 2 × 10−4/s to 2 × 10−1/s, even without any interfacial friction or adhesion, the interfacial shear strength could achieve close to 70% of the theoretical strength of perfect matrix‐fiber bonding. It is observed that, while strain rate has appreciable effects on the fiber/matrix interfacial strength and can cause change of failure mode in some cases; its influence also depends on the geometry of the anchoring sites. Moreover, there is an optimal geometric configuration at which maximum failure strength is achieved. Graphic charts showing the dependency of interfacial strength on the strain rate and geometric configuration parameters are obtained.
Machine Learning Accelerated, High Throughput, Multi‐Objective Optimization of Multiprincipal Element Alloys
Authors: Guo Tian , Wu Lianping , Li Teng 
Published: September 2021

AbstractMultiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional properties unprecedented in traditional alloys. However, identifying an MPEA with desired properties from a huge compositional space via a cost‐effective design remains a grand challenge. To address this challenge, the authors present a highly efficient design strategy of MPEAs through a coherent integration of molecular dynamics (MD) simulation, machine learning (ML) algorithms, and genetic algorithm (GA). The ML model can be effectively trained from 54 MD simulations to predict the stiffness and critical resolved shear stress (CRSS) of CoNiCrFeMn alloys with a relative error of 2.77% and 2.17%, respectively, with a 12 600‐fold reduction of computation time. Furthermore, by combining the highly efficient ML model and a multi‐objective GA, one can predict 100 optimal compositions of CoNiCrFeMn alloys with simultaneous high stiffness and CRSS, as verified by 100 000 ML‐accelerated predictions. The highly efficient and precise design strategy can be readily adapted to identify MPEAs of other principal elements and thus substantially accelerate the discovery of other high‐performance MPEA materials.
Men Who Have Sex with Men
Authors: Pachauri Saroj , Pachauri Ash , Mittal Komal 
Published: September 2021

AbstractMen who have sex with men (MSM) are men who engage in sexual activity with members of the same sex, regardless of how they identify themselves. In India, same-sex behavior and relations tend to be much more fluid. These men may identify as gay, homosexual, bisexual, heterosexual, or may dispense with sexual identity altogether.
The Way Forward
Authors: Pachauri Saroj , Pachauri Ash , Mittal Komal 
Published: September 2021

AbstractThe field of self-care interventions is new, fast moving, and multi-disciplinary. There is a need to explore the way ahead in advancing the field so that self-care forms an integral part of health programs. In order to move this agenda forward, a comprehensive strategy is needed. This includes training health professionals on SRHR self-care interventions; providing education to potential clients; making self-care technologies available and accessible to potential users; promoting the use of digital and online resources to accelerate self-care; and providing research-based evidence for the formulation of policies and programs.
Relevance of Candidatus Nitrotoga for nitrite oxidation in technical nitrogen removal systems
Authors: Spieck Eva , Wegen Simone , Keuter Sabine 
Published: September 2021

Abstract
Many biotechnological applications deal with nitrification, one of the main steps of the global nitrogen cycle. The biological oxidation of ammonia to nitrite and further to nitrate is critical to avoid environmental damage and its functioning has to be retained even under adverse conditions. Bacteria performing the second reaction, oxidation of nitrite to nitrate, are fastidious microorganisms that are highly sensitive against disturbances. One important finding with relevance for nitrogen removal systems was the discovery of the mainly cold-adapted Cand. Nitrotoga, whose activity seems to be essential for the recovery of nitrite oxidation in wastewater treatment plants at low temperatures, e.g., during cold seasons. Several new strains of this genus have been recently described and ecophysiologically characterized including genome analyses. With increasing diversity, also mesophilic Cand. Nitrotoga representatives have been detected in activated sludge. This review summarizes the natural distribution and driving forces defining niche separation in artificial nitrification systems. Further critical aspects for the competition with Nitrospira and Nitrobacter are discussed. Knowledge about the physiological capacities and limits of Cand. Nitrotoga can help to define physico-chemical parameters for example in reactor systems that need to be run at low temperatures.

Key points
• Characterization of the psychrotolerant nitrite oxidizer Cand. Nitrotoga
• Comparison of the physiological features of Cand. Nitrotoga with those of other NOB
• Identification of beneficial environmental/operational parameters for proliferation
Modelling and prevention of meshing interference in gear skiving of internal gears
Authors: Hilligardt Andreas , Klose Jan , Gerstenmeyer Michael , Schulze Volker 
Published: September 2021

AbstractGear skiving is a highly productive process for machining of internal gears which are required in large quantity for electric mobility transmissions. Due to the complex kinematics of gear skiving, collisions of the tool and workpiece can occur during the process. Models exist to check for collisions of the tool shank or collisions in the tool run-out. While these models are sufficient for the process design of external gear skiving, at internal gears meshing interferences between tool and workpiece can appear outside the contact plane on the clearance face of the tool. To test for meshing interference requires comprehensive assessment of workpiece, tool and process kinematics. Currently, this is often done by time consuming CAD-simulation. In contrast, this paper presents an automated geometrical model for the analysis of meshing interference. The test for collisions is thereby performed along the whole height of the tool and especially includes constructive clearance angles and eccentric tool positions. The model is developed for user-friendly implementation and practical applications. The model for avoiding meshing interference in gear skiving is validated on two different process applications. In doing so, influences of the tool and process design on the interference situation are investigated, compared and discussed. Furthermore this new approach enables the prevention of meshing interference or tooth tip collisions in the early tool design by adjusting the process kinematics or the tool design itself. The maximal viable tool height can be quantified and recommendations for improving the clearance face situation are suggested.
Minimum friction losses in wind turbine gearboxes
Authors: Pedrero José I. , Martínez-López Débora , Calvo-Irisarri José , Pleguezuelos Miguel , Sánchez Miryam B. , Fernández-Sisón Alfredo 
Published: September 2021

AbstractImproving the mechanical efficiency is not the most important objective in the design of wind turbine gearboxes since the available wind energy is abundant and costless. The most important criteria for dimensioning the gearbox are the fatigue strength—bending and pitting—, noise emission, vibrations, and maintenance requirements. Nevertheless, mechanical losses increase the lubricant temperature and induce thermal stresses, which increases wear and cracking risk. This means that friction losses should be reduced as much as possible, but always regarding the contact and tooth-root stress levels, as well as the other operating parameters which should be kept for ensuring the required operating conditions.In this paper, a study on the variation of the friction losses with the tooth shift coefficients is presented. All the other geometrical parameters—number of teeth, tooth height, pressure angle, helix angle, face width, and center distance—are unalterable, since all of them have been chosen according to more important design requirements. In addition, to keep the contact and tooth-root stress levels, the shift coefficients of the sun, planets and ring are calculated in such a way that the transverse contact ratios are kept, and therefore the critical load points for bending and pitting are also unchanged. The radial clearance is also kept in order to allow the proper evacuation of the lubricant. Finally, all the geometrical constraints (undercut, pointing, root interference, secondary interference, backlash) are also imposed. With all these restrictions, the optimal shift coefficients for all the gears are calculated to minimize the friction losses.
Depressive symptoms in patients with epilepsy and clinically associated features in a single tertiary center
Authors: Vacca Mariacarolina , Fernandes Mariana , Spanetta Matteo , Placidi Fabio , Izzi Francesca , Lombardo Caterina , Mercuri Nicola Biagio , Liguori Claudio 
Published: September 2021

AbstractAlthough depressive symptoms are the most common psychiatric comorbidity in epilepsy, they remain underestimated and untreated in a large proportion of patients. The purpose of this study was to evaluate depression severity and related clinical features in people with epilepsy using a well-reliable self-report index of mood, the Beck Depression Inventory-II (BDI-II). One-hundred seventeen adult patients with epilepsy were recruited from a tertiary epilepsy center and completed the BDI-II. A single-item analysis of the 21 questions of the BDI-II was computed and differences between women and men in each depressive symptom were evaluated. Correlation and regression analyses were used to identify clinical features associated with the severity of depression. Results showed gender differences in some items, with women reporting overall higher depression severity than men. The most common symptoms regarded domains of sleeping patterns, tiredness, and loss of energy. Regression evidence suggested that being female, having an epilepsy duration < 10 years, as well as being treated with psychotropic drugs and reporting generalized seizure, were associated with higher depression severity. Despite its cross-sectional nature, this study reinforces the importance of investigating and possibly treating depressive symptoms in adult patients with epilepsy, since they negatively impact well-being, daytime activities, and sleep. Further studies identifying pharmacological and non-pharmacological treatments for depression in epilepsy need to be planned.
The Early Development of Passive Treatment Systems for Mining-Influenced Water: A North American Perspective
Authors: Kleinmann Bob , Skousen Jeff , Wildeman Tom , Hedin Bob , Nairn Bob , Gusek Jim 
Published: September 2021

AbstractThis paper reviews the early history (first 20 years) of passive treatment of mine water, from its beginnings, when it was viewed as a possible way to treat small flows of circumneutral and mildly acidic coal mine drainage, to its use for much larger flows and more contaminated mine water from metal mines. The original concepts of passive treatment have since been modified and used successfully to treat a wide range of mine water quality and quantities, far more than we would have believed possible.
Analytics of high average-utility patterns in the industrial internet of things
Authors: Wu Jimmy Ming-Tai , Li Zhongcui , Srivastava Gautam , Yun Unil , Lin Jerry Chun-Wei 
Published: September 2021

AbstractRecently, revealing more valuable information except for quantity value for a database is an essential research field. High utility itemset mining (HAUIM) was suggested to reveal useful patterns by average-utility measure for pattern analytics and evaluations. HAUIM provides a more fair assessment than generic high utility itemset mining and ignores the influence of the length of itemsets. There are several high-performance HAUIM algorithms proposed to gain knowledge from a disorganized database. However, most existing works do not concern the uncertainty factor, which is one of the characteristics of data gathered from IoT equipment. In this work, an efficient algorithm for HAUIM to handle the uncertainty databases in IoTs is presented. Two upper-bound values are estimated to early diminish the search space for discovering meaningful patterns that greatly solve the limitations of pattern mining in IoTs. Experimental results showed several evaluations of the proposed approach compared to the existing algorithms, and the results are acceptable to state that the designed approach efficiently reveals high average utility itemsets from an uncertain situation.
3D Dense Mapping with the Graph of Keyframe-Based and View-Dependent Local Maps
Authors: Zieliński Krzysztof , Staszak Rafał , Nowaczyk Mikołaj , Belter Dominik 
Published: September 2021

AbstractThis article concerns the problem of a dense mapping system for a robot exploring a new environment. In this scenario, a robot equipped with an RGB-D camera uses RGB and range data to build a consistent model of the environment. Firstly, dense mapping requires the selection of the data representation. Secondly, the dense mapping system has to deal with localization drift which can be corrected when loop closure is detected. In this article, we deal with both of these problems, and we make several technical contributions. We define local maps which use the Normal Distribution Transform (NDT) stored in the 2D structures to represent the local scene with varying 3D resolution. This method directly utilizes the uncertainty model of the range sensor and provides information about the accuracy of the data in the map. We also propose an architecture that utilizes pose and covisibility graphs to correct a global model of the environment after loop closure detection. We show how to integrate the dense local mapping with the pose graph and keyframes management system in the ORB-SLAM2 localization. Finally, we show the advantages of the view-dependent model over the methods that uniformly divide the space to represent objects in the environment.
Tonsillectomy and the incidence of various types of cancer
Authors: Holló Gábor 
Published: September 2021

AbstractA potential connection between tonsillectomy and the development of various cancer types has repeatedly been reported in the scientific literature, but many studies have contradicted these observations. Thus, we have no clear evidence, neither to firmly support nor to refute the above-mentioned connection. Here, I suggest that the main reason for the lack of clearer evidence is that the investigations have so far mainly used incorrect sample groups. I propose that individual differences in the tonsils’ involvement in immune reactions should be taken into account to solve this long-standing puzzle.
Comparative evaluation of contribution-value plots for machine learning understanding
Authors: Collaris Dennis , van Wijk Jarke J. 
Published: September 2021

Abstract
The field of explainable artificial intelligence aims to help experts understand complex machine learning models. One key approach is to show the impact of a feature on the model prediction. This helps experts to verify and validate the predictions the model provides. However, many challenges remain open. For example, due to the subjective nature of interpretability, a strict definition of concepts such as the contribution of a feature remains elusive. Different techniques have varying underlying assumptions, which can cause inconsistent and conflicting views. In this work, we introduce local and global contribution-value plots as a novel approach to visualize feature impact on predictions and the relationship with feature value. We discuss design decisions and show an exemplary visual analytics implementation that provides new insights into the model. We conducted a user study and found the visualizations aid model interpretation by increasing correctness and confidence and reducing the time taken to obtain an insight.

Graphic Abstract
DensePILAE: a feature reuse pseudoinverse learning algorithm for deep stacked autoencoder
Authors: Wang Jue , Guo Ping , Li Yanjun 
Published: September 2021

AbstractAutoencoder has been widely used as a feature learning technique. In many works of autoencoder, the features of the original input are usually extracted layer by layer using multi-layer nonlinear mapping, and only the features of the last layer are used for classification or regression. Therefore, the features of the previous layer aren’t used explicitly. The loss of information and waste of computation is obvious. In addition, faster training and reasoning speed is generally required in the Internet of Things applications. But the stacked autoencoders model is usually trained by the BP algorithm, which has the problem of slow convergence. To solve the above two problems, the paper proposes a dense connection pseudoinverse learning autoencoder (DensePILAE) from reuse perspective. Pseudoinverse learning autoencoder (PILAE) can extract features in the form of analytic solution, without multiple iterations. Therefore, the time cost can be greatly reduced. At the same time, the features of all the previous layers in stacked PILAE are combined as the input of next layer. In this way, the information of all the previous layers not only has no loss, but also can be strengthened and refined, so that better features could be learned. The experimental results in 8 data sets of different domains show that the proposed DensePILAE is effective.
Distributed Energy Systems and Energy Communities Under Negotiation
Authors: Kojonsaari Anna-Riikka , Palm Jenny 
Published: September 2021

AbstractNew decentralized energy-generation technologies have turned economies of scale upside down while becoming more economically viable. At the same time, the increased penetration of information technologies has led to new opportunities to manage infrastructure in a less hierarchical, more flexible way. Together with citizen demands for control over energy, these two converging trends has put energy communities (ECs) on the agenda, potentially advancing the transition towards more sustainable energy systems, despite hindrances encountered on the way. This paper presents a case study of the planning process of a sustainable city district in Sweden, using participatory observations and interviews conducted with included stakeholders. We analyse how the included stakeholders has reasoned about establishing a sustainable energy system in the area, including a microgrid. The discussions on a microgrid comprised two parallel discourses, coexisting but seldomly explicitly confronted. The distribution system operator in the area promoted a distributed energy system (DES) solution, while the property developers opted for a microgrid organized more as a citizen energy community (CEC). We discuss why the CEC proponents so far has lost the battle of creating a community owned smart grid. We conclude that the different models, a DES and a CEC, comprise different values and an increased focus on energy communities could shift the transition pathway towards a more decentralized system involving other prioritise than just economical.
Montmorillonite-anchored magnetite nanocomposite for recovery of ammonium from stormwater and its reuse in adsorption of Sc3+
Authors: Song Jianzhi , Srivastava Varsha , Kohout Tomas , Sillanpää Mika , Sainio Tuomo 
Published: September 2021

AbstractThe treatment of stormwater to remove and recover nutrients has received increasing interest. The objective of this study was to develop a novel adsorbent that is easy to handle, has good adsorption capacity, and is economical to use. A novel nanocomposite of montmorillonite (MT)-anchored magnetite (Fe3O4) was synthesised by co-precipitation as an adsorbent for ammonium. The MT/Fe3O4 nanocomposite had pore sizes (3–13 nm) in the range of narrow mesopores. The dispersion of the anchored Fe3O4 was confirmed by transmission electron microscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy (XPS). The nanocomposite exhibited higher affinity towards ammonium than the original MT. The Langmuir isotherm model was found to be the most suitable model to explain the ammonium adsorption behaviour of the nanocomposite. The maximum adsorption capacity for ammonium was 10.48 mg/g. The adsorption mechanism was a combination of ion exchange and electrostatic interaction. In an authentic stormwater sample, the synthesised adsorbent removed 64.2% of ammonium and reduced the amount of heavy metal contaminants including Mn, Ni, Cu and Zn. Furthermore, the ammonium loading on MT/Fe3O4 during adsorption functionalised the adsorbent surface. Additionally, the spent nanocomposite showed potential for rare earth elements (REEs) adsorption as a secondary application, especially for the selective adsorption of Sc3+. The versatile application of montmorillonite-anchored magnetite nanocomposite makes it a promising adsorbent for water treatment.
Graphic abstract