bluuebunny/crossref_metadata_2025_split huggingface dataset:
Controlled Synthesis of Carbon-Supported Pt-Based Electrocatalysts for Proton Exchange Membrane Fuel Cells
Authors: Liu Huiyuan , Zhao Jian , Li Xianguo 
Published: September 2022

AbstractProton exchange membrane fuel cells are playing an increasing role in postpandemic economic recovery and climate action plans. However, their performance, cost, and durability are significantly related to Pt-based electrocatalysts, hampering their large-scale commercial application. Hence, considerable efforts have been devoted to improving the activity and durability of Pt-based electrocatalysts by controlled synthesis in recent years as an effective method for decreasing Pt use, and consequently, the cost. Therefore, this review article focuses on the synthesis processes of carbon-supported Pt-based electrocatalysts, which significantly affect the nanoparticle size, shape, and dispersion on supports and thus the activity and durability of the prepared electrocatalysts. The reviewed processes include (i) the functionalization of a commercial carbon support for enhanced catalyst–support interaction and additional catalytic effects, (ii) the methods for loading Pt-based electrocatalysts onto a carbon support that impact the manufacturing costs of electrocatalysts, (iii) the preparation of spherical and nonspherical Pt-based electrocatalysts (polyhedrons, nanocages, nanoframes, one- and two-dimensional nanostructures), and (iv) the postsynthesis treatments of supported electrocatalysts. The influences of the supports, key experimental parameters, and postsynthesis treatments on Pt-based electrocatalysts are scrutinized in detail. Future research directions are outlined, including (i) the full exploitation of the potential functionalization of commercial carbon supports, (ii) scaled-up one-pot synthesis of carbon-supported Pt-based electrocatalysts, and (iii) simplification of postsynthesis treatments. One-pot synthesis in aqueous instead of organic reaction systems and the minimal use of organic ligands are preferred to simplify the synthesis and postsynthesis treatment processes and to promote the mass production of commercial carbon-supported Pt-based electrocatalysts.Graphical AbstractThis review focuses on the synthesis process of Pt-based electrocatalysts/C to develop aqueous one-pot synthesis at large-scale production for PEMFC stack application.
“I’m Glad That I Was Given a Second Chance to Live”: the Buffering Impact of Turning Points in the Lives of Young People with Foster Care Experience
Authors: Taussig Heather N. , Roberts Louise , Scourfield Jonathan , Franz Colette 
Published: September 2022

Abstract
Young people with a history of out-of-home care placement are at risk for a host of adverse outcomes, yet many demonstrate resilience by young adulthood. One mechanism by which well-being may be achieved is through a turning point (TP). This study had two key questions: (1) What do TPs look like for care-experienced young adults? (2) Does having a TP buffer the impact of early adversity on young adult well-being? Participants (N = 166) were interviewed in pre-adolescence and again in young adulthood. Baseline measures of adversity (ACEs) and life satisfaction were associated with young adult life satisfaction. In young adulthood, participants were asked an open-ended question about having a TP and four fifths of participants stated that they had a TP. Although having a TP was unrelated to demographic factors, living situation histories, or type of maltreatment, a multiple regression predicting young adult life satisfaction found a significant interaction between having a TP and ACEs, over and above baseline control variables. In probing the interaction, there was no association between ACEs and life satisfaction for those with a TP; for those without a TP, however, there was a negative association between ACEs and life satisfaction. In conclusion, having a TP in adolescence seemed to buffer the impact of early adversity on later well-being among young adults with a history of out-of-home care. The nature of the TPs varied, but having any TP seemed to lead to maturation and realizations which may serve as protective factors while navigating the transition to adulthood.
Investigating the effects of electrochemical discharge machining (ECDM) on the dimensional accuracy and surface integrity of the PDMS microchannel
Authors: Torabi Arsalan , Razfar Mohammad Reza 
Published: September 2022

AbstractIn this study, the electrochemical discharge machining (ECDM) process was used to fabricate a microchannel on polydimethylsiloxane (PDMS), which is able to fabricate channels on the non-conductive materials at low cost and acceptable material removal rate (MRR). One of the main advantages of this method, in addition to much less time and cost, is the possibility of achieving high depths (up to 1000 μm). For this purpose, the effect of electrolyte concentration, rotational speed, feed rate, and machining voltage on the surface quality and surface roughness was investigated in the PDMS micromachining. It was found that the ECDM is capable of fabricating the channels with the surface quality similar to lithography. Also, with increasing the machining voltage and electrolyte concentration, the MRR increases and the possibility of mechanical contact between tool and workpiece decreases. Increasing the machining voltage and also the electrolyte concentration changes the machining regime from contact machining to electrochemical machining. Increasing the machining voltage from 38 to 42 V increases the channel cross-section by nearly 40%. Also, the surface roughness increases by 36% with increasing the voltage from 38 to 42 V. Changing the rotational speed from 0 to 10,000 rpm, due to the reduction in the thickness of gas film, reduces the side sparks and concentration of the sparks on the bottom of the tool, which reduces the surface roughness. The Response Surface Method was used to achieve a mathematical model between inputs and outputs. The model represented a Quadratic Equation to predict the outputs.
Characterization of low density polyethylene greenhouse films during the composting of rose residues
Authors: Alvarez-Vega C. , Streitwieser D. Almeida , Álvarez-Barreto J. , Leon-Reyes A. 
Published: September 2022

AbstractThis study presents an evaluation of a potential alternative to plastic degradation in the form of organic composting. It stems from the urgent need of finding solutions to the plastic residues and focuses on the compost-based degradation of greenhouse film covers in an important rose exporter company in Ecuador. Thus, this study analyzes the physical, chemical, and biological changes of rose wastes composting, and also evaluates the stability of new and aged agricultural plastic under these conditions. Interestingly, results of compost characterization show a slow degradation rate of organic matter and total organic carbon, along with a significant increase in pH and rise of bacterial populations. However, the results demonstrate that despite these findings, composting conditions had no significant influence on plastic degradation, and while deterioration of aged plastic samples was reported in some tests, it may be the result of environmental conditions and a prolonged exposure to solar radiation. Importantly, these factors could facilitate the adhesion of microorganisms and promote plastic biodegradation. Hence, it is encouraged for future studies to analyze the ecotoxicity of plastics in the compost, as well as isolate, identify, and evaluate the possible biodegradative potential of these microorganisms as an alternative to plastic waste management.
Over 60,000 km in a year: remotely collecting large-volume high-quality data from a logistics truck
Authors: Berger Christian , Karsolia Arpit , Giaimo Federico , Benderius Ola 
Published: September 2022

AbstractAfter the first successful large-scale demonstration of eleven self-driving vehicles at the DARPA Urban Challenge in 2007, research results from the competing teams found their way into advanced driver systems (ADAS) that support typical driving tasks like adaptive cruise control and semi-automated parking. However, as of today, SAE Level 4 vehicles are not commercially available yet, which would allow the driver to be inattentive for longer periods. Hence, SAE Level 3, which represents partial automation yet continuously monitored by a human operator, may provide a step towards a viable SAE Level 4 product especially for commercial freight logistics. However, large amounts of data from such freight operations is needed to study the unique challenges in such use cases. In this paper, we present the system and software architecture of an end-to-end data logging solution, which is capable of recording large volumes of high-quality data. The system is installed in a commercial truck that is in daily operation by a logistics company and hence, the recorded data is only accessible remotely (i.e., over-the-air). We report about the fail-safe system design, initial findings from over one year of operation, as well as our lessons learned. During its first year of operation, the truck was used for 210 days by the logistics company, out of which 193 days were logged resulting in more than 4.5 TB of data from five cameras, two GNSS–IMU sensors, and six on-board vehicle controller area networks (CAN) busses. We demonstrate the value of the proposed end-to-end approach for traffic and driver behavior research by analyzing the uploaded data in the cloud to spot critical events such as unexpected harsh braking maneuvers caused by lane merging operations.
A facile method for synthesis rGO/Ag nanocomposite and its uses for enhancing photocatalytic degradation of Congo red dye
Authors: Ali Mohamed H. H. , Goher Mohamed E. , Al-Afify Afify D. G. , El-Sayed Siliem M. 
Published: September 2022

AbstractThe enhancing breakdown of dyes using facile, novel and eco-friendly photocatalyst without remaining any hazards secondary intermediates from the dye species regarded one of the most challenges to the healthy world. A novel facile method was used to synthesize reduced graphene oxide (rGO) with various doping ratios of silver nanoparticles (Ag NPs) and applied as photocatalyst to enhancing removal of Congo red (CR) dye using UV light irradiation from aqueous solution. Some characterization features such as UV-diffuse reflectance spectra, TEM, SEM, FTIR, X-ray diffraction, and EDX were measured to demonstrate the energy gap, morphology, size distribution, crystalline nature, phase structure, and elemental compositions of as-synthesized nanoparticles. The effect of some important factors such as pH of solution, initial CR concertation (Co), amount of rGO@Ag (g) and contact time (t) were studied to detect the optimum adsorption condition. The results indicated that, the maximum CR dye photodegradation is obtained at pH 7, 120 min, 50 mg/L initial CR concentration and 0.4 g/L photocatalyst dosage. The photodegradation data declared that, the higher the Ag doping ratio, the higher the degrading efficiency. Isotherm and kinetic studies showed that Langmuir and Freundlich models and the pseudo-second-order model are well fitting the adsorption process with maximum CR adsorption values ranging between 86.95 and 98.04 mg/L with corresponding R2 > 0.99.
Stochastic Continuous Modeling for Pillar Stress Estimation and Comparison with 2D Numerical, and Analytical Solutions in an Underground Stone Mine
Authors: Monsalve Juan J. , Soni Aman , Karfakis Mario , Hazzard Jim , Ripepi Nino 
Published: September 2022

AbstractPillar collapses are events that due to their severe consequences can be classified as high risk. The design of pillars in underground room-and-pillar operations should migrate to risk-based design approaches. The authors of this work proposed a risk-based pillar design methodology that integrates stochastic discrete element modeling for pillar strength estimation, and stochastic finite volume modeling (FVM) for stress estimation. This paper focuses on the stochastic FVM component for stress estimation. The mining and geomechanical aspects of a case study mine (CSM) are described and pillar stresses are estimated by using three approaches: (1) analytical solutions, (2) 2D finite element modeling, and (3) 3D finite volume modeling. This operation extracts a 30° dipping deposit, which makes current underground stone mine design guidelines inapplicable for this CSM. This work compares results from each stress estimation approach and discusses uses the point estimate method as a simplified stochastic approach to evaluate the effect of rock mass elastic properties variability on pillar stress distribution. Results from this work show that the three estimation approaches lead to different estimations, possibly, due to the wide range of assumptions each estimation approach considers. It was also determined that the horizontal to vertical stress ratio has a significant impact on pillar stress magnitude. Therefore, it is recommended to perform in situ stress measurements, or assume worst-case-scenario values to account and reduce uncertainty due to this parameter. The stochastic stress estimation approach used in this paper provides results that can integrate a risk-based pillar design framework.
Mechanisms to Enhance Resilience and Post-traumatic Growth in Residential Care: a Narrative Review
Authors: Parry Sarah , Cox Nigel , Andriopoulou Panoraia , Oldfield Jeremy , Roscoe Shabana , Palumbo-Haswell Jasmin , Collins Scarlett 
Published: September 2022

AbstractResidential care is primarily considered most appropriate for young people with complex needs, often due to multi-type traumas. Children in care are disproportionately disadvantaged, with children in residential care most vulnerable, which is why it is so important to understand mechanisms that support resilience and post-traumatic growth for this group of young people. This review aimed to advance our understanding of how interventions, reflections upon experience, and constructs of resilience can enhance developing resilience in children’s homes for young people in care. International quantitative and qualitative studies were sought to identify features and mechanisms of care that underpin developing resilience. Following a systematic search of six databases, 25 papers were selected for review, with a total sample of 3198 individuals up to the age of 30 years old who were either receiving residential care (N = 3037) or who were care leavers (N = 161). Themes from the quantitative studies and a narrative synthesis of qualitative studies were developed. Therapeutic mechanisms and processes to support the development of resilience included experiencing love and trust with staff in homes through therapeutic relationships, nurturing self-compassion, promoting self-value and self-belief, positive future thinking, problem-focused coping, school engagement, constructing a positive origin story, and positive visualisations of a stable future. Measures of resilience could more accurately reflect post-traumatic growth and potential for resilience development for this unique group of young people, which in turn could inform intervention design and evaluation. Measures appreciative of intrapersonal, relational, community and environmental factors could be particularly useful for intervention design.
Effects of chronic fluoxetine treatment on anxiety- and depressive-like behaviors in adolescent rodents – systematic review and meta-analysis
Authors: Kryst Joanna , Majcher-Maślanka Iwona , Chocyk Agnieszka 
Published: September 2022

Abstract
Background
Drugs prescribed for psychiatric disorders in adolescence should be studied very extensively since they can affect developing and thus highly plastic brain differently than they affect the adult brain. Therefore, we aimed to summarize animal studies reporting the behavioral consequences of chronic exposure to the most widely prescribed antidepressant drug among adolescents i.e., fluoxetine.

Methods
Electronic databases (Medline via Pubmed, Web of Science Core Collection, ScienceDirect) were systematically searched until April 12, 2022, for published, peer-reviewed, controlled trials concerning the effects of chronic fluoxetine administration vs. vehicle on anxiety and depression measures in naïve and stress-exposed adolescent rodents. All of the relevant studies were selected and critically appraised, and a meta-analysis of eligible studies was performed.

Results
A total of 18 studies were included in the meta-analysis. In naïve animals, chronic adolescent fluoxetine administration showed dose-related anxiogenic-like effects, measured as a reduction in time spent in the open arms of the elevated plus maze. No significant effects of chronic adolescent fluoxetine on depression-like behavior were reported in naïve animals, while in stress-exposed rodents chronic adolescent fluoxetine significantly decreased immobility time in the forced swim test compared to vehicle.

Conclusions
These results suggest that although chronic fluoxetine treatment proves positive effects in animal models of depression, it may simultaneously increase anxiety in adolescent animals in a dose-related manner. Although the clinical implications of the data should be interpreted with extreme caution, adolescent patients under fluoxetine treatment should be closely monitored.
Analyzing spatial variations of heart disease and type-2 diabetes: A multi-scale geographically weighted regression approach
Authors: Cui Wencong , Hu Nanzhou , Zhang Shuyang , Li Diya , Martinez Luis , Goldberg Daniel , Güneralp Burak , Zhang Zhe 
Published: September 2022

AbstractHeart disease is the leading cause of death in the United States. A person who has type-2 diabetes is twice as likely to have heart disease than someone who doesn’t have diabetes. Therefore, analyzing factors associated with both diseases and their interrelationships is essential for cardiovascular disease control and public health. In this article, we propose a Multi-scale Geographically Weighted Regression (MGWR) approach to observe spatial variations of environmental and demographic risk factors such as alcohol consumption behavior, lack of physical activity, obesity rate, urbanization rate, and income from 2005 to 2015 in the United States. The MGWR model has applied to eight census divisions of the United States at the county level: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, and Mountain. Results illustrate that there are notable differences in the spatial variation of the risk factors behind these two diseases. In particular, obesity has been a leading factor that associate with diabetes in the east, south-central, and south Atlantic regions of the U.S. On the other hand, smoking and alcohol consumption was the primary concern in the northern part of the U.S., in 2005. In 2015, alcohol consumption levels decreased, but the smoking level remained the same in those regions, which showed a significant impact on diabetes in the neighboring regions. Between 2005 and 2015, lack of physical exercise has become a significant risk factor associated with diabetes in the Northeast and West parts of the U.S. The proposed MGWR produced high goodness to fit (R2) for most of the areas in the United States.
Science for implementation: the roles, experiences, and perceptions of practitioners involved in the Intergovernmental Panel on Climate Change
Authors: North M. A. , Hunter N. B. , Roberts D. C. , Slotow R. 
Published: September 2022

AbstractIn the climate change arena, the assessments of the Intergovernmental Panel on Climate Change (IPCC), while not policy prescriptive, are important for informing international negotiations and the decisions of policy and practice communities. Since 2015, when the Paris Agreement was adopted, there has been an increasing demand for climate action and calls for the inclusion of a broader base of stakeholders in global assessments. We use publicly available information on IPCC authors, and the results of a survey (n = 29) and interviews (n = 17) with authors who apply science in practice (practitioners), to examine their roles, experiences, and challenges in the IPCC’s Fifth Assessment. The results show that while practitioners form only a very small proportion of authors, they contribute real-world experience, including the translation of academic language into meaningful messages for decision-makers. Although familiar with working at the interface of science and practice, study participants described barriers to their participation and shared several recommendations for improving the relevance, uptake, and timeliness of IPCC assessments, and practitioner participation. Our findings indicate that IPCC assessments provide an evidence base to support action on climate change, and due to their skill set, practitioners are often able to make contributions that allow for greater accessibility by decision-makers.
Graphical Abstract
A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-Seq, and Single-Cell RNA-Seq
Authors: Ye Wenbin , Lian Qiwei , Ye Congting , Wu Xiaohui 
Published: September 2022

Abstract
Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3′ untranslated region, tissue-specific, cross-species, and single-cell pA prediction.