bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural resource dependence, policy and institutions for environmental sustainability and African welfare
Authors: Mpuure Desmond Mbe‐Nyire , Mengba Jennifer Dokbila 
Published: September 2023

AbstractIn developing countries, particularly in Africa, dependence on natural resources poses a threat to development, leading to poor health, reduced productivity, and increased poverty among nations. This raises significant concerns for the prospects and welfare of Africa, given the rising environmental pollution. However, the literature on the mitigating effect of policies and institutions for environmental sustainability (PIES) on resource‐dependent countries in Africa is scarce. As a result, this study explores the effects of natural resource dependence and the mediating effect of PIES on under‐five mortality and human development in Africa. This novel hypothesis may contribute to the divergent differences in African welfare. Using a panel of 30 resource‐dependent countries spanning 2005 to 2021 and employing the two‐step dynamic generalized method of moments, the study provides evidence in support of the novel hypothesis. The findings show that dependence on natural resources can be either a blessing or a curse for African countries, depending on the degree to which environmental sustainability is embraced. Furthermore, a heterogeneous analysis demonstrates significant support for countries with high policies and institutions for environmental sustainability in mitigating the negative impacts of natural resource dependence on welfare. The study concludes that dependence on natural resources without environmental sustainability cannot guarantee a balance between the well‐being of the economy and the environment. Therefore, environmental management should not be politically motivated so as to sustainably improve human well‐ being in Africa.
Polyvinyl Pyrrolidone Induced “Confinement Effect” on PbI2 and the Improvement on Crystallization and Thermal Stability of Perovskite
Authors: Yu Xi , Fang Zhenxing , Lin Siyuan , Wu Shuyue , Fang Mei , Xie Haipeng , Kong Deming , Zhou Conghua 
Published: September 2023

AbstractPolyvinyl pyrrolidone is blended in PbI2 with varied concentration, so as to study the coarsening dynamics of perovskite during the two‐step growth method. It is observed that polyvinyl pyrrolidone hinders the crystallization of PbI2 and helps to form a more amorphous PbI2 matrix, which then improves perovskite crystallization. As the blending concentration increases from 0 to 2 mM, average crystallite/grain size of perovskite increases from 40.29 nm/0.79 µm to 84.35 nm/1.02 µm while surface fluctuation decreases slightly from 25.64 to 23.96 nm. The observations are caused by the “confinement effect” brought by polyvinyl pyrrolidone on PbI2. Elevating blending concentration of polyvinyl pyrrolidone results in smaller PbI2 crystallites and more amorphous PbI2 matrix, thus reducing the diffusion/reaction barrier between PbI2 and organic salt and favoring perovskite crystallization. As blending concentration increases from 0 to 2 mM, the device efficiency rises from 19.76 (± 0.60) % to 20.50 (± 0.89) %, with the optimized value up to 22.05%, which is further improved to 24.48% after n‐Octylammonium iodide (OAI)‐basing surface modification. The study enlarges the scope of “confinement effect” brought by polymer molecules, which is beneficial for efficient and stable perovskite solar cell fabrication.
3D‐Printed Biomimetic Structural Colors
Authors: Bi Ran , Li Xiaohong , Ou Xingcheng , Huang Jiaqi , Huang Dantong , Chen Guoliang , Sheng Yu , Hong Wei , Wang Yan , Hu Weijie , Guo Shuang‐Zhuang 
Published: September 2023

AbstractResolution control and expansibility have always been challenges to the fabrication of structural color materials. Here, a facile strategy to print cholesteric liquid crystal elastomers (CLCEs) into complex structural color patterns with variable resolution and enhanced expansibility is reported. A volatile solvent is introduced into the synthesized CLC oligomers, modifying its rheological properties and allowing direct‐ink‐writing (DIW) under mild conditions. The combination of printing shear flow and anisotropic deswelling of ink drives the CLC molecules into an ordered cholesteric arrangement. The authors meticulously investigate the influence of printing parameters to achieve resolution control over a wide range, allowing for the printing of multi‐sized 1D or 2D patterns with constant quality. Furthermore, such solvent‐cast direct‐ink‐writing (DIW) strategy is highly expandable and can be integrated easily into the DIW of bionic robots. Multi‐responsive bionic butterfly and flower are printed with biomimetic in both locomotion and coloration. Such designs dramatically reduced the processing difficulty of precise full‐color printing and expanded the capability of structural color materials to collaborate with other systems.
Energy‐efficient organic photoelectric synaptic transistors with environment‐friendly CuInSe2 quantum dots for broadband neuromorphic computing
Authors: Zhang Junyao , Guo Ziyi , Sun Tongrui , Guo Pu , Liu Xu , Gao Huaiyu , Dai Shilei , Xiong Lize , Huang Jia 
Published: September 2023

AbstractPhotoelectric synaptic device is a promising candidate component in brain‐inspired high‐efficiency neuromorphic computing systems. Implementing neuromorphic computing with broad bandwidth is, however, challenging owing to the difficulty in realizing broadband characteristics with available photoelectric synaptic devices. Herein, taking advantage of the type‐II heterostructure formed between environmentally friendly CuInSe2 quantum dots and organic semiconductor, broadband photoelectric synaptic transistors (BPSTs) that can convert light signals ranging from ultraviolet (UV) to near‐infrared (NIR) into post‐synaptic currents are demonstrated. Essential synaptic functions, such as pair‐pulse facilitation, the modulation of memory level, long‐term potentiation/depression transition, dynamic filtering, and learning‐experience behavior, are well emulated. More significantly, benefitting from broadband responses, information processing functions, including arithmetic computing and pattern recognition can also be simulated in a broadband spectral range from UV to NIR. Furthermore, the BPSTs exhibit obvious synaptic responses even at an ultralow operating voltage of −0.1 mV with an ultralow energy consumption of 75 aJ per event, and show their potential in flexible electronics. This study presents a pathway toward the future construction of brain‐inspired neural networks for high‐bandwidth neuromorphic computing utilizing energy‐efficient broadband photoelectric devices.
Developing and validating an Next Generation Science Standards‐aligned construct map for chemical bonding from the energy and force perspective
Authors: Kaldaras Leonora , Akaeze Hope O. , Krajcik Joseph 
Published: September 2023

AbstractChemical bonding is central to explaining many phenomena. Research in chemical education and the Framework for K–12 Science Education (the Framework) argue for new approaches to learning chemical bonding grounded in (1) using ideas of the balance of electric forces and energy minimization to explain bond formation, (2) using learning progressions (LPs) grounded in these ideas to support learning, and (3) engaging students in 3D learning reflected in integrating the three dimensions of scientific knowledge to make sense of phenomena. The dimensions include disciplinary core ideas, scientific and engineering practices, and crosscutting concepts. While the Framework describes the theoretical basis of 3D learning, empirical evidence for the development and validation of LPs for 3D learning is limited. This work addresses that issue for the topic of chemical bonding. We develop and validate a 3D construct map for chemical bonding grounded in the idea of balance of electric forces and energy minimization. A construct map represents a finer‐grained LP spanning a shorter period and focusing on specific aspects of a larger‐scale LP. An NGSS‐aligned validated 3D LP has never been reported for the topic of chemical bonding. The LP is based on data from 9th grade Mid‐Western and Western students who used the NGSS‐aligned curriculum. Multiple validity evidence sources, including interview and item response theory analysis using an assessment tool developed to probe the 3D construct map levels, were used. We demonstrate the feasibility of using the assessment tool for assigning levels to individuals and groups of learners, which is essential for the practical applicability of the 3D construct map and provides teachers with information on how to promote learning. We hope that the 3D LP presented here will serve as a guide to develop instructional and assessment approaches for chemical bonding grounded in the fundamental scientific principles and aligned to NGSS.
Optimizing contrast protocol for bone‐subtraction CT angiography of intracranial arteries in normal dogs using 160‐slice CT
Authors: An Soyon , Hwang Gunha , Kim Rakhoon , Cha Jihye , Lee Hee Chun , Hwang Tae‐Sung 
Published: September 2023

AbstractBackgroundBone‐subtraction computed tomography angiography (CTA) (BSCTA) is a new technique designed to overcome the limitation of three‐dimensional CTA, where the vessels surrounded by bone and calcification can be obscured. An optimal contrast CT protocol for intracranial artery visualization with BSCTA has yet to be established in dogs.ObjectivesThe purpose of this study was to determine the optimal contrast protocol of CTA for visualizing intracranial artery using an automatic bone‐subtraction technique in dogs.MethodsBrain CTA was performed four times for each of nine healthy beagle dogs to cover all the contrast protocols: two different contrast iodine concentrations (300 and 370 mgI/mL) and two different contrast media injection rates (2 and 4 mL/s). Bone removal post‐processing was performed automatically by subtracting the non‐enhanced CT data from the contrast CT data using a dedicated workstation. The bone‐subtracted intracranial vessels were analysed for quantitative and qualitative evaluation.ResultsQuantitative evaluation showed significantly higher CT attenuation values for the group with a 370 mgI/mL iodine content at a rate of 4 mL/s than the two groups with a 300 mgI/mL iodine content at the rates of 2 and 4 mL/s (p < 0.001). Qualitative assessment revealed significantly higher mean scores for the 370 mgI/mL groups than the 300 mgI/mL groups and significantly higher mean scores for the 4 mL/s groups than the 2 mL/s groups (p < 0.05).ConclusionsThe optimal contrast protocol for BSCTA suggests that high iodine material concentration and high injection rate should be used for strong arterial attenuation and great visualization of the intracranial arterial structure in dogs.
Encephalomyocarditis virus in a capybara (Hydrochoerus hydrochaeris)
Authors: Hill Andrew Gordon , Mackie John Thomas 
Published: September 2023

AbstractEncephalomyocarditis virus is responsible for epizootics and sporadic mortalities worldwide, particularly in zoos, and in non‐rodent species is characterised by sudden death due to acute myocarditis. Rodents are considered the reservoir host and show variable manifestations ranging from clinically asymptomatic infection to paralysis or death. We present a capybara (Hydrochoerus hydrochaeris) that exhibited lethargy, ataxia, nasal discharge and bradyarrhythmias over 5 days before death. Encephalomyocarditis virus infection was confirmed by histopathology, which showed non‐suppurative myocarditis with necrosis and polymerase chain reaction, and occurred despite recent vaccination.
Performance evaluation of hybrid constructed wetlands for nitrogen removal and statistical approaches
Authors: Kumar Suresh , Sangwan Vikramaditya , Kumar Munish , Shweta Shweta , Shivani Shivani , Kumar Manoj , Deswal Surinder 
Published: September 2023

AbstractNitrogen pollution in water bodies has become a pressing environmental and public health issue worldwide, demanding the implementation of effective nitrogen removal strategies. This research paper delves into the performance evaluation of hybrid constructed wetlands (HCWs) as a sustainable and innovative approach for nitrogen removal, employing a comprehensive year‐long dataset gathered from a practical setup. The study collected data under diverse operating conditions to investigate the effectiveness of HCWs in removing nitrogen. Results revealed that HCWs achieved nitrogen removal efficiencies ranging from 28% to 65%, influenced by temperature and hydraulic retention time. Optimal removal occurred at an average temperature of 28°C and a 4‐day hydraulic retention time. Notably, performance declined during colder periods, with temperatures below 15°C. The study also aims to predict nitrogen removal by three modeling techniques, that is, artificial neural networks (ANNs), support vector machines Pearson VII kernel function (SVM PUK), and multiple linear regression (MLR). Prediction has been done considering temperature (TEMP), hydraulic loading rate (HLR), initial concentration of chemical oxygen demand (COD) (CODin), initial concentration of total nitrogen (TNin), initial concentration of total phosphorous (TPin), and initial concentration of turbidity (TBin) as input parameters, whereas reduction of total nitrogen (RED TN) is regarded as output parameter. The performance of the soft computing techniques has been compared in terms of coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The analysis revealed that the performance of the SVM (PUK) model (R2: 0.572, RMSE: 0.0359, MAE: 0.0294) for the prediction of TN reduction is superior followed by MLR (R2: 0.562, RMSE: 0.0365, MAE: 0.0294) and ANN (R2: 0.597, RMSE: 0.0377, MAE: 0.0301). The present study concludes that the treated effluent by the HCWs, using water hyacinth and water lettuce, is of fair quality, thus having potential application for the treatment of rice mill wastewater in warmer climates. Further, machine learning approaches employed in estimating the total nitrogen reduction by HCWs technology have shown promising applicability and utilization in such studies.Practitioner Points

Hybrid constructed wetlands (HCWs) are effective in removing nitrogen from wastewater.
The performance of HCWs in nitrogen removal can vary due to physical, chemical, and biological processes.
The performance of the HCWs highly depends on temperature and hydraulic retention time.
Artificial neural networks (ANNs) and support vector machines (SVMs) provided better predictions of nitrogen removal with high accuracy and low root mean square error.
Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022
Authors: Zhang Cheng , Sjarif Nilam Nur Amir , Ibrahim Roslina 
Published: September 2023

AbstractAccurately predicting the prices of financial time series is essential and challenging for the financial sector. Owing to recent advancements in deep learning techniques, deep learning models are gradually replacing traditional statistical and machine learning models as the first choice for price forecasting tasks. This shift in model selection has led to a notable rise in research related to applying deep learning models to price forecasting, resulting in a rapid accumulation of new knowledge. Therefore, we conducted a literature review of relevant studies over the past 3 years with a view to aiding researchers and practitioners in the field. This review delves deeply into deep learning‐based forecasting models, presenting information on model architectures, practical applications, and their respective advantages and disadvantages. In particular, detailed information is provided on advanced models for price forecasting, such as Transformers, generative adversarial networks (GANs), graph neural networks (GNNs), and deep quantum neural networks (DQNNs). The present contribution also includes potential directions for future research, such as examining the effectiveness of deep learning models with complex structures for price forecasting, extending from point prediction to interval prediction using deep learning models, scrutinizing the reliability and validity of decomposition ensembles, and exploring the influence of data volume on model performance.This article is categorized under:
Technologies > Prediction
Technologies > Artificial Intelligence
Resetting the Future: World 50.0
Authors: Landesz Tamás , Varghese Sangeeth , Sargsyan Karine 
Published: September 2023

AbstractThe pandemic has presented an opportunity to reflect, reimagine, and reset the world. The ancient Greeks referred to time using two different concepts: “chronos” and “kairos.” Whereas the former refers to traditional time measured by a ticking clock, the latter refers to “deep time,” when everything is possible. This book is a journey to create a community for building a better future. The WORLD 50.0 movement is working toward building a better, more inclusive, and sustainable future. Concurrently, initiatives like the United Planet (UP), Futurian, and Regenopolis are working toward a bluer, greener future by catalyzing actions needed to realize that future. The book shares the dreams of the world's top scientists, thinkers, and innovators who are continuously working on inventing the future, including transitioning to become a multi-planetary species, brain-human interfaces combined with exoskeletons, and nanomedicine reforming health care. The aim of the WORLD 50.0 movement is to build a better future together faster by crowdsourcing inputs on a global scale and engaging and scaling a community of contributors.
Future of Leadership
Authors: Landesz Tamás 
Published: September 2023

AbstractThe current pandemic and the accelerating future require a new type of leadership to emerge. The Young Global Leaders of the World Economic Forum (WEF) interviewed in this book envision an emerging era of humanity and empathy as we transition towards a more digital existence where global institutions will be significantly redesigned. Future leaders shall be role models, representing a new set of values that inspire new generations to lead with heart, compassion, emotional intelligence, care, education and kindness. Authentic leadership traits such as adaptability, collaboration, creativity, emotional intelligence, entrepreneurship, ethics, resilience, self-awareness and social awareness will be crucial for future-generation leaders. Eight traits responsible for the development of early leadership abilities of Young Global Leaders included evolutionary traits, early exposure to significant responsibility, high expectations, enabling environments, important crucible moments and the pursuit of passion. The concept of leadership is changing, and the right mix of authenticity and Machiavellianism is necessary to make an impact in an increasingly complex world.
Postdigital Participation in Education: A Postscript
Authors: Macgilchrist Felicitas , Weich Andreas 
Published: September 2023

AbstractThis postscript takes the form of a conversation between the book’s editors, who pull together the discursive strands explored in the book’s chapters in response to three guiding questions: How is the postdigital deployed in the chapters of this book? How do contemporary media constellations shape participation? And who participates how in these contemporary media constellations? Addressing these questions together, as necessitated by the intricate entanglements of the postdigital condition, the editors discuss the complexities around the term “postdigital” and the practices and implications for power relations that both influence and derive from the use of technology in education, in society, in culture, and in politics.
Quarks at the modular S4 cusp
Authors: de Medeiros Varzielas I. , Levy M. , Penedo J. T. , Petcov S. T. 
Published: September 2023

Abstract
We analyse the possibility of describing quark masses, mixing and CP violation in $$ {S}_4^{\prime } $$

S
4
′

modular flavour models without flavons. We focus on the case where the closeness of the modulus to the point of residual $$ {\mathbb{Z}}_3^{ST} $$

ℤ
3
ST

symmetry (the cusp) plays a role in generating quark mass hierarchies and discuss the role modular form normalisations play in such constructions. We find that fitting quark data requires explicit CP breaking, unless a second modulus is introduced.
Purity of monoids and characteristic-free splittings in semigroup rings
Authors: De Stefani Alessandro , Montaño Jonathan , Núñez-Betancourt Luis 
Published: September 2023

AbstractInspired by methods in prime characteristic in commutative algebra, we introduce and study combinatorial invariants of seminormal monoids. We relate such numbers with the singularities and homological invariants of the semigroup ring associated to the monoid. Our results are characteristic independent.
Geometric Characterization of the Eyring–Kramers Formula
Authors: Avelin Benny , Julin Vesa , Viitasaari Lauri 
Published: September 2023

AbstractIn this paper we consider the mean transition time of an over-damped Brownian particle between local minima of a smooth potential. When the minima and saddles are non-degenerate this is in the low noise regime exactly characterized by the so called Eyring–Kramers law and gives the mean transition time as a quantity depending on the curvature of the minima and the saddle. In this paper we find an extension of the Eyring–Kramers law giving an upper bound on the mean transition time when both the minima/saddles are degenerate (flat) while at the same time covering multiple saddles at the same height. Our main contribution is a new sharp characterization of the capacity of two local minima as a ratio of two geometric quantities, i.e., the minimal cut and the geodesic distance.
The acute influence of amateur boxing on dynamic cerebral autoregulation and cerebrovascular reactivity to carbon dioxide
Authors: Wallis W. E. G. , Al-Alem Q. , Lorimer H. , Smail O. J. , Williams G. K. R. , Bond B. 
Published: September 2023

Abstract
Purpose
The purpose of this study was to investigate the acute effect of head impacts, sustained over the course of three rounds of amateur boxing, on indices of cerebrovascular function.

Methods
Eighteen university amateur boxers (six female) completed three experimental trials in a randomised order; (1) three rounds of boxing (BOX), (2) an equivalent bout of pad boxing (where no blows to the head were sustained; PAD), and (3) a time-matched seated control trial (CON). Indices of cerebrovascular function were determined immediately before and 45 min after each trial. Specifically, dynamic cerebral autoregulation (dCA) was determined by considering the relationship between changes in cerebral blood velocity and mean arterial pressure during 5 min of squat-stand manoeuvres at 0.05 and 0.10 Hz. Cerebrovascular reactivity was determined using serial breath holding and hyperventilation attempts.

Results
Participants received an average of 40 ± 16 punches to the head during the BOX trial. Diastolic, mean and systolic dCA phase during squat stand manoeuvres at 0.05 Hz was lower after BOX compared to pre BOX (P ≤ 0.02, effect size (d) ≥ 0.74). No other alterations in dCA outcomes were observed at 0.05 or 0.10 Hz. The number of head impacts received during the BOX trial was associated with the change in systolic phase (r = 0.50, P = 0.03). No differences in cerebrovascular reactivity to breath holding or hyperventilation were observed.

Conclusions
A typical bout of amateur boxing (i.e., three rounds) can subtly alter cerebral pressure-flow dynamics, and the magnitude of this change may be related to head impact exposure.