bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges in accelerating net-zero transitions: insights from transport electrification in Germany and California
Authors: Rogge Karoline S , Goedeking Nicholas 
Published: February 2024

Abstract
Addressing the climate crisis necessitates accelerating transitions towards climate-neutral systems of production and consumption, with electrification emerging as a crucial decarbonisation strategy. The acceleration of such net-zero transitions across multiple systems faces significant resistance and contestation. In this paper, we propose an extended list of challenges unique to the acceleration phase of socio-technical transitions: we introduce ‘expansion and contestation’, ‘justice’, and ‘international dynamics’ as additional challenge types to complement the already acknowledged challenge types of ‘whole systems change’, ‘interaction between multiple systems’, ‘decline and resistance’, ‘consumers and social practices’, and ‘governance’. We apply this extended analytical framework to the electrification of private-passenger vehicles and investigate the unfolding transition to e-mobility with evidence from 35 expert interviews in Germany and California. We uncover over 50 real-world challenges associated with these net-zero transitions at the beginning of the acceleration phase. Most challenges fall within the categories of ‘expansion and contestation’ and ‘governance’. While Germany and California share many real-world challenges, we also find significant variation between both jurisdictions, which we attribute to differences in their automotive incumbency, transition governance approaches, and institutional contexts. We discuss implications for future research, arguing for greater attention to the dual politics of acceleration during net-zero transitions: political conflict not only centres around the decline of old industries and future losses, but also around the expansion of the new system and associated future gains.
Solvable non-Hermitian skin effects and real-space exceptional points: non-Hermitian generalized Bloch theorem
Authors: Zhang Xintong , Song Xiaoxiao , Zhang Shubo , Zhang Tengfei , Liao Yuanjie , Cai Xinyi , Li Jing 
Published: February 2024

Abstract
Non-Hermitian systems can exhibit extraordinary boundary behaviors, known as the non-Hermitian skin effects, where all the eigenstates are localized exponentially at one side of lattice model. To give a full understanding and control of non-Hermitian skin effects, we have developed the non-Hermitian generalized Bloch theorem to provide the analytical expression for all solvable eigenvalues and eigenstates, in which translation symmetry is broken due to the open boundary condition. By introducing the Vieta’s theorem for any polynomial equation with arbitrary degree, our approach is widely applicable for one-dimensional non-Hermitian tight-binding models. With the non-Hermitian generalized Bloch theorem, we can analyze the condition of existence or non-existence of the non-Hermitian skin effects at a mathematically rigorous level. Additionally, the non-Hermitian generalized Bloch theorem allows us to explore the real-space exceptional points. We also establish the connection between our approach and the generalized Brillouin zone method. To illustrate our main results, we examine two concrete examples including the Su–Schrieffer–Heeger chain model with long-range couplings, and the ladder model with non-reciprocal interaction. Our non-Hermitian generalized Bloch theorem provides an efficient way to analytically study various non-Hermitian phenomena in more general cases.
Applicability of normalized resistance rate model for predicting fatigue life and resistance evolution in composite conductive inks
Authors: Li Qiushi , Pierron Olivier , Antoniou Antonia 
Published: February 2024

Abstract
The electrical resistance of metal-polymer conductive inks increases as they undergo cyclic loading, posing a major challenge to their reliability as interconnect materials for flexible electronic devices. To characterize an ink’s fatigue performance, extensive electro-mechanical testing is usually performed. Phenomenological models that can accurately predict the resistance increase with cyclic loading can save time and be useful in flexible conductor design against fatigue failure. One such model was recently developed for only one composite ink type. The model is based on experiments monitoring resistance under monotonic stretch data and multiple experiments measuring the rate of increase of the resistance under different strain amplitudes and mean strains. The current work examines whether such resistance rate model could be generalized to apply for more types of composite inks. Two composite inks with different binder material, metal flake sizes and shapes, and substrate material were experimentally tested under monotonic and cyclic loading. It was found that the two new inks are also more sensitive to strain amplitude than mean strain. The resistance rate model accurately predicts early/catastrophic failure (<1000 cycles) in all inks and conservatively estimates high fatigue life for low strain amplitudes. A protocol detailing the procedures for applying the resistance model to new inks is outlined.
Trends and advances in silk based 3D printing/bioprinting towards cartilage tissue engineering and regeneration
Authors: Singh Yogendra Pratap , Bandyopadhyay Ashutosh , Dey Souradeep , Bhardwaj Nandana , Mandal Biman B 
Published: February 2024

Abstract
Cartilage repair remains a significant clinical challenge in orthopedics due to its limited self- regeneration potential and often progresses to osteoarthritis which reduces the quality of life. 3D printing/bioprinting has received vast attention in biofabrication of functional tissue substitutes due to its ability to develop complex structures such as zonally structured cartilage and osteochondral tissue as per patient specifications with precise biomimetic control. Towards a suitable bioink development for 3D printing/bioprinting, silk fibroin has garnered much attention due to its advantageous characteristics such as shear thinning behavior, cytocompatibility, good printability, structural fidelity, affordability, and ease of availability and processing. This review attempts to provide an overview of current trends/strategies and recent advancements in utilizing silk-based bioinks/biomaterial-inks for cartilage bioprinting. Herein, the development of silk-based bioinks/biomaterial-inks, its components and the associated challenges, along with different bioprinting techniques have been elaborated and reviewed. Furthermore, the applications of silk-based bioinks/biomaterial-inks in cartilage repair followed by challenges and future directions are discussed towards its clinical translations and production of next-generation biological implants.
Research and development of a new combination of piezo-thermoelectric energy harvester systems from roadways
Authors: Randriantsoa Ando Ny Aina , Fakra Damien Ali Hamada , Rakotondrajaona Luc , Benelmir Riad 
Published: February 2024

Abstract
Due to the problems associated with fossil fuels, scientists and governments are investigating alternative energy sources. In recent decades, there has been an increase in interest in initiatives involving the collection of clean, limitless energy. This paper focuses on two renewable energy harvesting combination technologies: mechanical vibration utilizing piezoelectric technology and thermal sources utilizing thermoelectric technology. Existing scientific literature proposes various techniques for producing and modeling each system individually. This study proposes a novel piezo-thermoelectric pavement model with piezo-thermoelectric coupling. Due to the lack of typical experimentation in the scientific literature, a new laboratory experimental prototype proposes to reproduce artificially and simultaneously heat harvesting on the artificial road surface and mechanical vibration caused by passing vehicles. Testing the laboratory-developed prototype has determined the efficacy of the piezo-thermoelectric coupling electronic model. This study demonstrated that a hybrid piezo-thermoelectric system is more suitable for road pavement applications than a piezo-thermoelectric coupling system. A hybrid combination system can continue to produce energy even if one of the energy sources is unavailable or malfunctioning, whereas a coupling combination system cannot. In laboratory testing, the combined piezo-thermoelectric harvester proposed could generate up to 1.75 μW without optimizing the materials or power generation. This innovative study demonstrates the feasibility and applicability of combining thermoelectric and piezoelectric technology to harvest energy from road surfaces.
Powering of IOTs through single jersey wearable tribo-electric nano generator
Authors: Amir Muhammad , Butt Rizwan Aslam , Naqvi Shenela , Hasany Syed Farhan 
Published: February 2024

Abstract
A simple, lightweight, and easy to develop Single Jersey Wearable Tribo-Electric Nano Generators (SJ-WTENG) were constructed using Cotton and Acrylic fabrics (Triboelectric series materials). Fabrics were also coated with Maghemite (γ-Fe2O3) nanoparticles (13 nm) to increase the electrical conductance of the samples. Compression and Vertical contact-separation modes were adopted for studying the performance of the developed samples. Along with a Single WTENG sample, the outputs of two samples connected in series were also measured. To study the effect of developed Maghemite (γ-Fe2O3) nanoparticle coating, non-coated fabrics WTENGs were also constructed and tested. The maximum voltage reached with the Maghemite (γ-Fe2O3) nanoparticle-coated SJ-WTENG samples was a time-varying signal of 7.68 volts peak to peak volts with an approximate frequency of 50.5 Hertz. A shotky diode-based full bridge rectifier was used to get the DC voltage. The rectified DC signal was observed to be 5 volts which was enough to light up an LED with a threshold voltage of 1.7 volts DC as well as charge 3.7 volts, 3.6Ah Li-ion battery pack. Results confirmed that the application of Maghemite (γ-Fe2O3) nanoparticles was useful in augmenting the output of the proposed SJ-WTENG design. The proposed system can be used to power the battery powered IOT (Internet of Things) devices, widely used in medical and body sensor network applications.
VCSEL-based photonic spiking neural networks for ultrafast detection and tracking
Authors: Robertson Joshua , Kirkland Paul , Di Caterina Gaetano , Hurtado Antonio 
Published: February 2024

Abstract
Inspired by efficient biological spike-based neural networks, we demonstrate for the first time the detection and tracking of target patterns in image and video inputs at high-speed rates with networks of multiple artificial spiking optical neurons. Using photonic systems of in-parallel spiking vertical cavity surface emitting lasers (VCSELs), we demonstrate the implementation of multiple convolutional kernel operators which, in combination with optical spike signalling, enable the detection and tracking of target features in images/video feeds at an ultrafast photonic operation speed of 1 ns per pixel. Alongside a single layer optical spiking neural network (SNN) demonstration, a multi-layer network of photonic (GHz-rate) spike-firing neurons is reported where the photonic system successfully tracks a large complex feature (Handwritten Digit 3). The consecutive photonic layers perform spike-enabled image reduction and convolution operations, and interact with a software-implemented SNN, that learns the feature patterns that best identify the target to provide a high detection efficiency even in the presence of a distractor feature. This work therefore highlights the effectiveness of combining neuromorphic photonic hardware and software SNNs, for efficient learning and ultrafast operation, thanks to the use of spiking light signals, towards tackling complex AI and computer vision problems.
Tailored risk assessment and forecasting in intermittent claudication
Authors: Ravindhran Bharadhwaj , Prosser Jonathon , Lim Arthur , Mishra Bhupesh , Lathan Ross , Hitchman Louise H , Smith George E , Carradice Daniel , Chetter Ian C , Thakker Dhaval , Pymer Sean 
Published: February 2024

Abstract

Background
Guidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in management and therefore outcomes. The development of a precise risk stratification tool is proposed through a machine-learning algorithm that aims to provide personalized outcome predictions for different management strategies.

Methods
Feature selection was performed using the least absolute shrinkage and selection operator method. The model was developed using a bootstrapped sample based on patients with intermittent claudication from a vascular centre to predict chronic limb-threatening ischaemia, two or more revascularization procedures, major adverse cardiovascular events, and major adverse limb events. Algorithm performance was evaluated using the area under the receiver operating characteristic curve. Calibration curves were generated to assess the consistency between predicted and actual outcomes. Decision curve analysis was employed to evaluate the clinical utility. Validation was performed using a similar dataset.

Results
The bootstrapped sample of 10 000 patients was based on 255 patients. The model was validated using a similar sample of 254 patients. The area under the receiver operating characteristic curves for risk of progression to chronic limb-threatening ischaemia at 2 years (0.892), risk of progression to chronic limb-threatening ischaemia at 5 years (0.866), likelihood of major adverse cardiovascular events within 5 years (0.836), likelihood of major adverse limb events within 5 years (0.891), and likelihood of two or more revascularization procedures within 5 years (0.896) demonstrated excellent discrimination. Calibration curves demonstrated good consistency between predicted and actual outcomes and decision curve analysis confirmed clinical utility. Logistic regression yielded slightly lower area under the receiver operating characteristic curves for these outcomes compared with the least absolute shrinkage and selection operator algorithm (0.728, 0.717, 0.746, 0.756, and 0.733 respectively). External calibration curve and decision curve analysis confirmed the reliability and clinical utility of the model, surpassing traditional logistic regression.

Conclusion
The machine-learning algorithm successfully predicts outcomes for patients with intermittent claudication across various initial treatment strategies, offering potential for improved risk stratification and patient outcomes.
What are We Talking about When We are Talking about ‘Decolonising’ Social Work?
Authors: Garrett Paul Michael 
Published: February 2024

Abstract
The core concern is the ‘decolonial turn’ which is said to be taking place in a number of universities and other institutions. In this context, attempts are being made to unmask the colonial ideologies and common sense rooted in various disciplines including social work. The article examines key terms such as ‘Decolonisation’, ‘Eurocentrism’, ‘Coloniality’ and ‘Decoloniality’. In conclusion, some of the obstacles that may be encountered by those aiming to decolonise social work are discussed and possible ways forward are identified.
VentRa: distinguishing frontotemporal dementia from psychiatric disorders
Authors: Manera Ana L , Dadar Mahsa , Ducharme Simon , Collins D Louis 
Published: February 2024

Abstract
The volume of the lateral ventricles is a reliable and sensitive indicator of brain atrophy and disease progression in behavioural variant frontotemporal dementia. In this study, we validate our previously developed automated tool using ventricular features (known as VentRa) for the classification of behavioural variant frontotemporal dementia versus a mixed cohort of neurodegenerative, vascular and psychiatric disorders from a clinically representative independent dataset. Lateral ventricles were segmented for 1110 subjects—14 behavioural variant frontotemporal dementia, 30 other frontotemporal dementia, 70 Lewy body disease, 898 Alzheimer’s disease, 62 vascular brain injury and 36 primary psychiatric disorder from the publicly accessible National Alzheimer’s Coordinating Center dataset to assess the performance of VentRa. Using ventricular features to discriminate behavioural variant frontotemporal dementia subjects from primary psychiatric disorders, VentRa achieved an accuracy rate of 84%, a sensitivity rate of 71% and a specificity rate of 89%. VentRa was able to identify behavioural variant frontotemporal dementia from a mixed age–matched cohort (i.e. other frontotemporal dementia, Lewy body disease, Alzheimer’s disease, vascular brain injury and primary psychiatric disorders) and to correctly classify other disorders as ‘not compatible with behavioral variant frontotemporal dementia’ with a specificity rate of 83%. The specificity rates against each of the other individual cohorts were 80% for other frontotemporal dementia, 83% for Lewy body disease, 83% for Alzheimer’s disease, 84% for vascular brain injury and 89% for primary psychiatric disorders. VentRa is a robust and generalizable tool with potential usefulness for improving the diagnostic certainty of behavioural variant frontotemporal dementia, particularly for the differential diagnosis with primary psychiatric disorders.
Instruments for racial health equity: a scoping review of structural racism measurement, 2019–2021
Authors: Hing Anna K , Chantarat Tongtan , Fashaw-Walters Shekinah , Hunt Shanda L , Hardeman Rachel R 
Published: February 2024

Abstract
Progress toward racial health equity cannot be made if we cannot measure its fundamental driver: structural racism. As in other epidemiologic studies, the first step is to measure the exposure. But how to measure structural racism is an ongoing debate. To characterize the approaches epidemiologists and other health researchers use to quantitatively measure structural racism, highlight methodological innovations, and identify gaps in the literature, we conducted a scoping review of the peer-reviewed and gray literature published during 2019–2021 to accompany the 2018 published work of Groos et al., in which they surveyed the scope of structural racism measurement up to 2017. We identified several themes from the recent literature: the current predominant focus on measuring anti-Black racism; using residential segregation as well as other segregation-driven measures as proxies of structural racism; measuring structural racism as spatial exposures; increasing calls by epidemiologists and other health researchers to measure structural racism as a multidimensional, multilevel determinant of health and related innovations; the development of policy databases; the utility of simulated counterfactual approaches in the understanding of how structural racism drives racial health inequities; and the lack of measures of antiracism and limited work on later life effects. Our findings sketch out several steps to improve the science related to structural racism measurements, which is key to advancing antiracism policies.
Prevalence of diverse antimicrobial resistance genes and bacteria in sewage treatment plant-derived sludge environment
Authors: Patra Mrinmoy , Pandey Bhavana , Dubey Suresh Kumar 
Published: February 2024

Abstract
Antimicrobial resistance (AMR) contamination in the environment is one of the most significant worldwide threats of the 21st century. Since sludge is heavily exposed to diverse contaminants, including pharmaceuticals, the inhabitant bacterial population is expected to exhibit resistance to antimicrobial agents. In this study, sewage treatment plant (STP) sludge samples were analyzed to assess the antibiotic-resistant bacterial population, abundance of AMR genes (ermF, qnrS, Sul1, blaGES, blaCTX-M, and blaNDM), and mobile genetic elements (intl1 and IS26). Out of 16, six bacterial isolates exhibited resistance to 13 antibiotics with a high multiple antibiotic resistance index (MARI) (0.93) and high metal tolerance. Quantitative polymerase chain reaction showed the abundance of target genes ranging from 6.6 × 103 to 6.5 × 108 copies g−1 sludge. The overall outcome reveals that STP sludge comprised varied multidrug-resistant bacterial populations. It will give insights into the functions of heavy metals and biofilm development in the selection and spread of AMR genes and the associated bacteria. Therefore, the application of sludge needs proper screening for AMR and metal contamination prior to its countless applications. This study will contribute immensely to the risk analysis of STP effluents on environmental health, including control of AMR transmission.
In vitro modelling of bacterial pneumonia: a comparative analysis of widely applied complex cell culture models
Authors: Mahieu Laure , Van Moll Laurence , De Vooght Linda , Delputte Peter , Cos Paul 
Published: February 2024

Abstract
Bacterial pneumonia greatly contributes to the disease burden and mortality of lower respiratory tract infections among all age groups and risk profiles. Therefore, laboratory modelling of bacterial pneumonia remains important for elucidating the complex host–pathogen interactions and to determine drug efficacy and toxicity. In vitro cell culture enables for the creation of high-throughput, specific disease models in a tightly controlled environment. Advanced human cell culture models specifically, can bridge the research gap between the classical two-dimensional cell models and animal models. This review provides an overview of the current status of the development of complex cellular in vitro models to study bacterial pneumonia infections, with a focus on air–liquid interface models, spheroid, organoid, and lung-on-a-chip models. For the wide scale, comparative literature search, we selected six clinically highly relevant bacteria (Pseudomonas aeruginosa, Mycoplasma pneumoniae, Haemophilus influenzae, Mycobacterium tuberculosis, Streptococcus pneumoniae, and Staphylococcus aureus). We reviewed the cell lines that are commonly used, as well as trends and discrepancies in the methodology, ranging from cell infection parameters to assay read-outs. We also highlighted the importance of model validation and data transparency in guiding the research field towards more complex infection models.
Leveraging Country Expertise: How Scholars in International Studies Can Support the Asylum Process
Authors: Chapman Hannah S , Schwartz Rachel A 
Published: February 2024

Abstract
Bridging the divide between research and practice has become a growing concern within international studies. One under-explored avenue through which international studies scholars can enhance their “real world” impact is by serving as country conditions experts in asylum cases. This article provides an overview of the asylum process, the role of country conditions experts within it, and how scholars with in-depth country knowledge can leverage their expertise to make a difference, using examples from the United States and the United Kingdom. It also details several key issues one should consider when deciding whether to undertake expert witness work and the challenges and dilemmas it often entails. Finally, we provide actionable ways for international studies scholars to get involved and expand the community of individuals engaged in expert witnessing.