bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated image registration of cerebral digital subtraction angiography
Authors: Hellebrekers Vincent J. W. , van Walsum Theo , Smal Ihor , Cornelissen Sandra A. P. , van Zwam Wim H. , van der Lugt Aad , van der Sluijs Matthijs , Su Ruisheng
Published: July 2023

Purpose

Our aim is to automatically align digital subtraction angiography (DSA) series, recorded before and after endovascular thrombectomy. Such alignment may enable quantification of procedural success.

Methods

Firstly, we examine the inherent limitations for image registration, caused by the projective characteristics of DSA imaging, in a representative set of image pairs from thrombectomy procedures. Secondly, we develop and assess various image registration methods (SIFT, ORB). We assess these methods using manually annotated point correspondences for thrombectomy image pairs.

Results

Linear transformations that account for scale differences are effective in aligning DSA sequences. Two anatomical landmarks can be reliably identified for registration using a U-net. Point-based registration using SIFT and ORB proves to be most effective for DSA registration and are applicable to recordings for all patient sub-types. Image-based techniques are less effective and did not refine the results of the best point-based registration method.

Conclusion

We developed and assessed an automated image registration approach for cerebral DSA sequences, recorded before and after endovascular thrombectomy. Accurate results were obtained for approximately 85% of our image pairs.
Moore on Degrees of Responsibility
Authors: Kaiserman Alex
Published: July 2023

In his latest book Mechanical Choices, Michael Moore provides an explication and defence of the idea that responsibility comes in degrees. His account takes as its point of departure the view that free action and free will consist in the holding of certain counterfactuals. In this paper, I argue that Moore’s view faces several familiar counterexamples, all of which serve to motivate Harry Frankfurt’s classic insight that whether and to what extent one is responsible for one’s action has more to do with what actually caused that action than with what one could or couldn’t have done instead. I then go on to sketch an alternative approach to degrees of responsibility that takes seriously this insight. I’ll argue that Moore ought to be sympathetic to this approach, inasmuch as it combines two familiar Moorean ideas: the idea that causal contribution comes in degrees, and the idea that acting freely is compatible with, and indeed entails, the fact that one’s action was caused by prior states of affairs.
Ideas from the Frontline: Improvement Opportunities in Federally Qualified Health Centers
Authors: Jung Olivia S. , Begum Fahima , Dorbu Andrea , Singer Sara J. , Satterstrom Patricia
Published: July 2023

Background

Engaging frontline clinicians and staff in quality improvement is a promising bottom-up approach to transforming primary care practices. This may be especially true in federally qualified health centers (FQHCs) and similar safety-net settings where large-scale, top-down transformation efforts are often associated with declining worker morale and increasing burnout. Innovation contests, which decentralize problem-solving, can be used to involve frontline workers in idea generation and selection.

Objective

We aimed to describe the ideas that frontline clinicians and staff suggested via organizational innovation contests in a national sample of 54 FQHCs.

Interventions

Innovation contests solicited ideas for improving care from all frontline workers—regardless of professional expertise, job title, and organizational tenure and excluding those in senior management—and offered opportunities to vote on ideas.

Participants

A total of 1,417 frontline workers across all participating FQHCs generated 2,271 improvement opportunities.

Approaches

We performed a content analysis and organized the ideas into codes (e.g., standardization, workplace perks, new service, staff relationships, community development) and categories (e.g., operations, employees, patients).

Key Results

Ideas from frontline workers in participating FQHCs called attention to standardization (n = 386, 17%), staffing (n = 244, 11%), patient experience (n = 223, 10%), staff training (n = 145, 6%), workplace perks (n = 142, 6%), compensation (n = 101, 5%), new service (n = 92, 4%), management-staff relationships (n = 82, 4%), and others. Voting results suggested that staffing resources, standardization, and patient communication were key issues among workers.

Conclusions

Innovation contests generated numerous ideas for improvement from the frontline. It is likely that the issues described in this study have become even more salient today, as the COVID-19 pandemic has had devastating impacts on work environments and health/social needs of patients living in low-resourced communities. Continued work is needed to promote learning and information exchange about opportunities to improve and transform practices between policymakers, managers, and providers and staff at the frontlines.
Cybersuicide: Online-Assisted Suicide
Authors: Moir Courtney-Louise , Tzani Calli , Ioannou Maria , Lester David , Synnott John , Williams Thomas James Vaughan
Published: July 2023

Suicide is a major public health problem around the world, with an estimated 800,000 deaths from suicide each year. Research suggests that the ever-growing use of the Internet is contributing to and facilitating suicide. A thematic analysis was conducted on the final communications of three individuals aged between 18 and 21 to obtain an understanding of why people commit suicide online, how the Internet is involved, and how individuals who are online can influence a person’s choice of life or death. The analysis found that all three suicides were encouraged and baited by their audience, often as the audience doubted the legitimacy of the events, which resulted in pride issues for the victim. The issue of excitement from the audience was also present in all three cases, suggesting that online communications feel more like entertainment than real life. Other themes include social disorders, hesitation, manipulation, and attention seeking behaviour related to low self-esteem. The finding showed that those who die online by suicide have moments of hesitation, which are relevant for suicide-prevention strategies. The limitations of this study in terms of generalisability are discussed, and recommendations for the future of public awareness projects and research are given.
CXCR5 Regulates Neuronal Polarity Development and Migration in the Embryonic Stage via F-Actin Homeostasis and Results in Epilepsy-Related Behavior
Authors: Zhang Zhijuan , Zhang Hui , Antonic-Baker Ana , Kwan Patrick , Yan Yin , Ma Yuanlin
Published: July 2023

Epilepsy is a common, chronic neurological disorder that has been associated with impaired neurodevelopment and immunity. The chemokine receptor CXCR5 is involved in seizures via an unknown mechanism. Here, we first determined the expression pattern and distribution of the CXCR5 gene in the mouse brain during different stages of development and the brain tissue of patients with epilepsy. Subsequently, we found that the knockdown of CXCR5 increased the susceptibility of mice to pentylenetetrazol- and kainic acid-induced seizures, whereas CXCR5 overexpression had the opposite effect. CXCR5 knockdown in mouse embryos via viral vector electrotransfer negatively influenced the motility and multipolar-to-bipolar transition of migratory neurons. Using a human-derived induced an in vitro multipotential stem cell neurodevelopmental model, we determined that CXCR5 regulates neuronal migration and polarization by stabilizing the actin cytoskeleton during various stages of neurodevelopment. Electrophysiological experiments demonstrated that the knockdown of CXCR5 induced neuronal hyperexcitability, resulting in an increased number of seizures. Finally, our results suggested that CXCR5 deficiency triggers seizure-related electrical activity through a previously unknown mechanism, namely, the disruption of neuronal polarity.
A discussion of stability analysis for systems of differential equations with multiple and distributed delays
Authors: Dassios Ioannis , Liu Muyang , Milano Federico
Published: July 2023

In this article, we consider a class of systems of multiple delay differential equations (MDDEs). We first define a characteristic matrix equation that can be used to analyze the stability of the equilibrium of a system of MDDEs. Then we construct a matrix based on the coefficients of the characteristic matrix equation and use the spectrum of this matrix to derive necessary and sufficient conditions for the system to be stable. Next we discuss a comparison of the stability equivalency between a system of delay differential equations (DDEs) to the system of MDDEs and relate our results to distributed delay systems (DDSs). Numerical examples are given to justify our theory.
Novel Imaging Technologies for Accurate Assessment of Cardiac Allograft Performance
Authors: Higuita Manuela Lopera , Jain Rohil , Osho Asishana A. , Rabi S. Alireza , Pruett Timothy L. , 3rd Pierson Richard N. , Iaizzo Paul A. , Tessier Shannon N.
Published: July 2023

Purpose of the Review

The current lack of objective and quantitative assessment techniques to determine cardiac graft relative viability results in risk-averse decision-making, which negatively impact the utilization of cardiac grafts. The purpose of this review is to highlight the current deficiencies in cardiac allograft assessment before focusing on novel cardiac assessment techniques that exploit conventional and emerging imaging modalities, including ultrasound, magnetic resonance, and spectroscopy.

Recent Findings

Extensive work is ongoing by the scientific community to identify improved objective metrics and tools for cardiac graft assessment, with the goal to safely increasing the number and proportion of hearts accepted for transplantation.

This review briefly discusses the in situ and ex vivo tools currently available for clinical organ assessment, before focusing on the individual capabilities of ultrasound, magnetic resonance, and spectroscopy to provide insightful, non-invasive information regarding cardiac graft functional and metabolic status that may be used to predict outcome after transplantation.
Operational Challenges and Economics in Future Voltage Control Services
Authors: Davi-Arderius Daniel , Troncia Matteo , Peiró Juan Julián
Published: July 2023

Purpose of Review

Decarbonizing the power system entails the need to update voltage control strategies, traditionally based on synchronous generators, and energy flows from transmission to distribution grid level. We analyze the voltage control strategies implemented up to now, considering both the technical and economic views.

Recent Findings

We study how the transmission and distribution grid operators in Spain, Croatia, and Thailand improved their voltage control strategies to exploit potentials from power electronics from wind and photovoltaic generation. Moreover, we analyze economic fundamentals and market design issues related with the implementation of these new strategies, essential to set efficient economic incentives for their successful implementation.

We discuss recent innovative projects and solutions implemented in some countries that show promising and relevant potential from the implemented renewable-based voltage control strategies. However, we highlight that there are very few empirical analyses in real conditions, which are essential to implement improved and efficient voltage control strategies.
Influence of train speed and its mitigation measures in the short- and long-term performance of a ballastless transition zone
Authors: Ramos Ana , Calçada Rui , Correia António Gomes
Published: July 2023

The ballastless track is nowadays the most popular railway system due to the required low number of maintenance operations and costs, despite the high investment. The gradual change from ballasted to ballastless tracks has been occurring in Asia, but also in Europe, increasing the number of transition zones. The transition zones are a special area of the railway networks where there is an accelerated process of track degradation, which is a major concern of the railway infrastructure managers. Thus, the accurate prediction of the short- and long-term performance of ballastless tracks in transition zones is an important topic in the current paradigm of building/rehabilitating high-speed lines. This work purposes the development of an advanced 3D model to study the global performance of a ballastless track in an embankment–tunnel transition zone considering the influence of the train speed (220, 360, 500, and 600 km/h). Moreover, a mitigation measure is also adopted to reduce the stress and displacements levels of the track in the transition. A resilient mat placed in the tunnel and embankment aims to soften the transition. The behaviour of the track with the resilient mat is evaluated considering the influence of the train speed, with special attention regarding the critical speed. The used methodology is a novel and hybrid approach that allows including short-term and long-term performance, through the development of a powerful 3D model combined with the implementation of a calibrated empirical permanent deformation model.
Hierarchical graph neural network with subgraph perturbations for key gene cluster discovery in cancer staging
Authors: Hou Wenju , Wang Yan , Zhao Ziqi , Cong Yizhi , Pang Wei , Tian Yuan
Published: July 2023

Analyzing highly individual-specific genomic data to understand genetic interactions in cancer development is still challenging, with significant implications for the discovery of individual biomarkers as well as personalized medicine. With the rapid development of deep learning, graph neural networks (GNNs) have been employed to analyze a wide range of biomolecular networks. However, many neural networks are limited to black box models, which are only capable of making predictions, and they are often challenged to provide reliable biological and clinical insights. In this research, for sample-specific networks, a novel end-to-end hierarchical graph neural network with interpretable modules is proposed, which learns structural features at multiple scales and incorporates a soft mask layer in extracting subgraphs that contribute to classification. The perturbations caused by the input graphs' deductions are used to evaluate key gene clusters, and the samples are then grouped into classes to produce both sample- and stage-level explanations. Experiments on four gene expression datasets from The Cancer Genome Atlas (TCGA) show that the proposed model not only rivals the advanced GNN methods in cancer staging but also identifies key gene clusters that have a great impact on classification confidence, providing potential targets for personalized medicine.
Feature gene selection based on fuzzy neighborhood joint entropy
Authors: Wang Yan , Sun Minjie , Long Linbo , Liu Jinhui , Ren Yifan
Published: July 2023

This paper addresses the feature selection problem for gene expression profiles. Feature selection based on fuzzy neighborhood rough sets is very important in gene expression profiles. The process of extracting key features in gene expression profiles may have two disadvantages: (1) it may generate many redundant features, thus reducing the classification accuracy, and (2) it may ignore some information. To address the above problems, this paper proposes a fuzzy neighborhood joint entropy model based on feature selection; this model adopts the nonnegative principle of fuzzy neighborhood joint entropy to evaluate the importance of a candidate feature gene. Based on the fuzzy neighborhood joint entropy model, this paper proposes a new feature gene selection algorithm: the fuzzy neighborhood joint entropy (FNJE) algorithm. In the model, first, fuzzy neighborhood particles and fuzzy decision-making are combined with the uncertainty measure of joint entropy to construct a fuzzy neighborhood joint entropy model. Second, the importance degree of a feature is introduced as the measurement standard of candidate feature genes to evaluate the importance of each feature. Third, the algorithm uses the importance of candidate features in selecting features to reduce the redundancy of the selected features and improve the classification accuracy. In this paper, based on the UCI and gene datasets, we conduct a series of experiments. The experimental results show that the proposed algorithm can select fewer feature genes and achieve higher classification accuracy. Compared with the other four algorithms, our proposed algorithm can improve the accuracy by 0.4$$\%$$
%
$$-$$
-
10.42$$\%$$
%
and 1.16$$\%$$
%
$$-$$
-
15.18$$\%$$
%
and can reach maximum accuracy values of 90.52$$\%$$
%
and 87.02$$\%$$
%
with the linear-SVM and KNN classifiers, respectively.
Attention-deep reinforcement learning jointly beamforming based on tensor decomposition for RIS-assisted V2X mmWave massive MIMO system
Authors: Zhou Xiaoping , Chen Xinyue , Tong Le , Wang Yang
Published: July 2023

To achieve a green and sustainable wireless communication network, the reconfigurable intelligent surface (RIS) technology has emerged as an emerging technology. The RIS-assisted mmWave massive MIMO vehicle-to-everything (V2X) communications can support enhanced V2X applications for connected and automated vehicles. The design of RIS-assisted mmWave V2X communications is though not exempt of challenges as a result of fast time-varying propagation and highly dynamic vehicular networks and topologies. To address some of these challenges, we propose an attention-deep reinforcement learning jointly beamforming based on tensor decomposition for RIS-assisted mmWave massive MIMO system to improving the safety and traffic efficiency of cooperative automated driving. The received signal of the vehicle is decomposed into four-dimensional tensors and study the channel, frequency and time attention (CFTA) algorithm using the low order tensor characteristics of mmWave channels. This algorithm can extract the frequency and time characteristics of the channel, and obtain the millimeter wave characteristic channel between the corresponding base station (BS) and the vehicles. The problem of jointly optimization of beamforming matrix at the BS and the phase shift matrix on the RIS is constructed and solved using deep reinforcement learning (DRL). Unlike traditional alternating optimization methods, the integration of DRL techniques into the optimal design of the system enables the observation of immediate rewards, learning from the environment and improving it to obtain optimal solutions to high-dimensional jointly beamforming optimization problems ultimately. The simulation results show that the proposed algorithm has meaningful performance compared with other methods.
Dual-drive collaboration surrogate-assisted evolutionary algorithm by coupling feature reduction and reconstruction
Authors: Yu Haibo , Gong Yiyun , Kang Li , Sun Chaoli , Zeng Jianchao
Published: July 2023

Surrogate-assisted evolutionary algorithm (SAEA) prevails in the optimization of computationally expensive problems. However, existing SAEAs confront low efficiency in the resolution of high-dimensional problems characterized by multiple local optima and multivariate coupling. To this end, this paper offers a dual-drive collaboration surrogate-assisted evolutionary algorithm (DDCSAEA) by coupling feature reduction and reconstruction, which coordinates two unsupervised feature learning techniques, i.e., principal component analysis and autoencoder, in tandem. DDCSAEA creates a low-dimensional solution space by downscaling the target high-dimensional space via principal component analysis and collects promising candidates in the reduced space by collaborating a surrogate-assisted evolutionary sampling with differential mutation. An autoencoder is used to perform the feature reconstruction on the collected candidates for infill-sampling in the target high-dimensional space to sequentially refine the neighborhood landscapes of the optimal solution. Experimental results reveal that DDCSAEA has stronger convergence performance and optimization efficiency against eight state-of-the-art SAEAs on high-dimensional benchmark problems within 200 dimensions.
A quantitative comparison of devices for in vivo biomechanical characterization of human skin
Authors: Junker Håvar J. , Thumm Bettina , Halvachizadeh Sascha , Mazza Edoardo
Published: July 2023

Non-invasive skin characterization devices are emerging as a valuable tool in clinical skin research. In recent years, the range of available experimental techniques and methods used to determine the biomechanical properties of skin has increased considerably. Although a substantial amount of work has been devoted to assessing the working principle of macroscopic skin characterization devices individually, a rationalization and comparison between them is still lacking. This motivated the present study, which aimed to characterize and compare three commonly used working principles: suction, dynamic shear loading, and indentation. A synthetic model system with tunable mechanical properties was used to assess the three devices, and the results rationalized based on corresponding finite element models. In vivo measurements were performed on healthy volunteers to investigate the capability of differentiating the biomechanical properties of skin at different body locations, and to assess the intra- and inter-rater reliability of each device. The present comparative analysis indicates that the analyzed functional principles perceive the stiffness of human skin differently, with relevant implications for the interpretation of the respective measurement results.
Ants/Nest-Associated Fungi and Their Specialized Metabolites: Taxonomy, Chemistry, and Bioactivity
Authors: Aguilar-Colorado Ángel Sahid , Rivera-Chávez José
Published: July 2023

Microscopic fungi occupy a vast number of habitats, are taxonomically diverse, degrade complex substrates, and have stood out for their capacity to biosynthesize a plethora of specialized metabolites. Such molecules are structurally diverse, and many have applications in fundamental and applied sciences, for example, in medicine, material sciences, food chemistry, textile and pharmaceutical industries, and agronomy, among other fields. However, despite the tremendous biotechnological value of fungi, these organisms are understudied, limiting the knowledge to their taxonomy, chemistry, and some putative applications. Notably, some specific habitats remain unexplored in terms of their mycobiota. Based on these considerations, this review describes the known fungal diversity associated with ants/nests, their metabolic potential, and the possible applications of their specialized metabolites in drug discovery programs focused on developing treatments for human diseases. According to this revision, fungal diversity has been studied by applying conventional methodologies such as isolation and morphological identification of soil fungi from mounds and nest chambers, and indirectly from ants’ cuticles and glands. The subfamilies, genera, taxonomical information, and geographical origin of ants from which filamentous fungi and yeast are commonly isolated are also described. Furthermore, some important information is presented concerning the difference between the ant-associated mycobiota and that in the surroundings, discarding the extrapolation of the chemical and biological information known for soil fungi. Altogether, this review evidenced the lack of information regarding the chemical composition of ant-associated fungi, encouraging research focused on exploring the chemistry biosynthesized from ants’ mycobiota, as well as the elucidation of their allelopathic potential inside the nests.

Graphical Abstract
An efficient hybrid approach for optimization using simulated annealing and grasshopper algorithm for IoT applications
Authors: Sajjad Faria , Rashid Muhammad , Zafar Afia , Zafar Kainat , Fida Benish , Arshad Ali , Riaz Saman , Dutta Ashit Kumar , Rodrigues Joel J. P. C.
Published: July 2023

The multi-objective grasshopper optimization algorithm (MOGOA) is a relatively new algorithm inspired by the collective behavior of grasshoppers, which aims to solve multi-objective optimization problems in IoT applications. In order to enhance its performance and improve global convergence speed, the algorithm integrates simulated annealing (SA). Simulated annealing is a metaheuristic algorithm that is commonly used to improve the search capability of optimization algorithms. In the case of MOGOA, simulated annealing is integrated by employing symmetric perturbation to control the movement of grasshoppers. This helps in effectively balancing exploration and exploitation, leading to better convergence and improved performance.

The paper proposes two hybrid algorithms based on MOGOA, which utilize simulated annealing for solving multi-objective optimization problems. One of these hybrid algorithms combines chaotic maps with simulated annealing and MOGOA. The purpose of incorporating simulated annealing and chaotic maps is to address the issue of slow convergence and enhance exploitation by searching high-quality regions identified by MOGOA.

Experimental evaluations were conducted on thirteen different benchmark functions to assess the performance of the proposed algorithms. The results demonstrated that the introduction of simulated annealing significantly improved the convergence of MOGOA. Specifically, the IDG (Inverse Distance Generational distance) values for benchmark functions ZDT1, ZDT2, and ZDT3 were smaller than the IDG values obtained by using MOGOA alone, indicating better performance in terms of convergence. Overall, the proposed algorithms exhibit promise in solving multi-objective optimization problems.
WPO: A Whale Particle Optimization Algorithm
Authors: Huang Ko-Wei , Wu Ze-Xue , Jiang Chang-Long , Huang Zih-Hao , Lee Shih-Hsiung
Published: July 2023

Metaheuristic algorithms are novel optimization algorithms often inspired by nature. In recent years, scholars have proposed various metaheuristic algorithms, such as the genetic algorithm (GA), artificial bee colony, particle swarm optimization (PSO), crow search algorithm, and whale optimization algorithm (WOA), to solve optimization problems. Among these, PSO is the most commonly used. However, different algorithms have different limitations. For example, PSO is prone to premature convergence and falls into a local optimum, whereas GA coding is difficult and uncertain. Therefore, an algorithm that can increase the computing power and particle diversity can address the limitations of existing algorithms. Therefore, this paper proposes a hybrid algorithm, called whale particle optimization (WPO), that combines the advantages of the WOA and PSO to increase particle diversity and can jump out of the local optimum. The performance of the WPO algorithm was evaluated using four optimization problems: function evaluation, image clustering, permutation flow shop scheduling, and data clustering. The test data were selected from real-life situations. The results demonstrate that the proposed algorithm competes well against existing algorithms.
The exploration of remote simulation strategies for the acquisition of psychomotor skills in medicine: a pilot randomized controlled trial
Authors: Guérard-Poirier Natasha , Meloche-Dumas Léamarie , Beniey Michèle , Torres Andrei , Kapralos Bill , Dhane Malek , Mercier Frédéric , Younan Rami , Dubrowski Adam , Patocskai Erica
Published: July 2023

Background

Progress in remote educational strategies was fueled by the advent of the COVID-19 pandemic. This pilot RCT explored the efficacy of a decentralized model of simulation based on principles of observational and peer-to-peer learning for the acquisition of surgical skills.

Methods

Sixty medical students from the University of Montreal learned the running subcuticular suture in four different conditions: (1) Control group (2) Self-learning (3) Peer-learning (4) Peer-learning with expert feedback. The control group learned with error-free videos, while the others, through videos illustrating strategic sub-optimal performances to be identified and discussed by students. Performance on a simulator at the end of the learning period, was assessed by an expert using a global rating scale (GRS) and checklist (CL).

Results

Students engaging in peer-to-peer learning strategies outperformed students who learned alone. The presence of an expert, and passive vs active observational learning strategies did not impact performance.

Conclusion

This study supports the efficacy of a remote learning strategy and demonstrates how collaborative discourse optimizes the students’ acquisition of surgical skills. These remote simulation strategies create the potential for implantation in future medical curriculum design.

Trial Registration: NCT04425499 2020-05-06.
Barriers to programming education in UAE primary schools: a qualitative review from ICT teachers’ perspectives
Authors: Elsawah Wafaa , Hill Christopher
Published: July 2023

Purpose

Demonstrate the importance of programming, discuss the pedagogical philosophy of how programming is taught, identify the barriers to the proper implementation of programming education in United Arab Emirates (UAE) primary schools, and find solutions to overcome these barriers.

Methodology

The study adopted a qualitative approach. Thirteen ICT teachers, from different schools in the UAE, were interviewed to investigate their perception of the teaching of programming to primary students.

Findings

The good application of programming education in UAE schools is yet to be accomplished. There is a need to reform the teaching of programming in primary schools in the UAE and to raise awareness about it and its importance in the school domain (school principals, teachers, and students).

Implications

One significant implication is that teaching programming should be taken seriously by educational policymakers and school leaders as a core subject that should be taught to all students. The study also contributed to the growing body of literature on the value of programming skills and the role of the appropriate curriculum in developing these skills.

Originality/value

This study provides new insights at both practical and scholarly levels. It can shed light on the field's expansion prospects. The outcomes of this study may assist educational policymakers in better implementing programming education, particularly in primary school. Moreover, it helps teachers better prepare for the problems that primary students may encounter with learning programming in schools.
Time to change the way we think about tuberculosis infection prevention and control in health facilities: insights from recent research
Authors: Yates Tom A. , Karat Aaron S. , Bozzani Fiammetta , McCreesh Nicky , MacGregor Hayley , Beckwith Peter G. , Govender Indira , Colvin Christopher J. , Kielmann Karina , Grant Alison D.
Published: July 2023

In clinical settings where airborne pathogens, such as Mycobacterium tuberculosis, are prevalent, they constitute an important threat to health workers and people accessing healthcare. We report key insights from a 3-year project conducted in primary healthcare clinics in South Africa, alongside other recent tuberculosis infection prevention and control (TB-IPC) research. We discuss the fragmentation of TB-IPC policies and budgets; the characteristics of individuals attending clinics with prevalent pulmonary tuberculosis; clinic congestion and patient flow; clinic design and natural ventilation; and the facility-level determinants of the implementation (or not) of TB-IPC interventions. We present modeling studies that describe the contribution of M. tuberculosis transmission in clinics to the community tuberculosis burden and economic evaluations showing that TB-IPC interventions are highly cost-effective. We argue for a set of changes to TB-IPC, including better coordination of policymaking, clinic decongestion, changes to clinic design and building regulations, and budgeting for enablers to sustain implementation of TB-IPC interventions. Additional research is needed to find the most effective means of improving the implementation of TB-IPC interventions; to develop approaches to screening for prevalent pulmonary tuberculosis that do not rely on symptoms; and to identify groups of patients that can be seen in clinic less frequently.
A Fast and Fair Energy Transition: How Community Legal Action and New Legislation are Shaping the Global Shift to Renewable Energy
Authors: Aba Elodie
Published: July 2023

Legal action by communities affected by climate change against high carbon corporate emitters is on the rise. At the same time, with the acceleration of a transition to a net-zero carbon economy, communities impacted by the implementation and operation of renewable energy projects are increasingly challenging shortcomings in the shift to renewable energy through ‘just transition litigation’. This strategy aims to ensure that respect for human rights is at the heart of the new energy paradigm, and that human rights abuses by the fossil fuel and mining sectors are not replicated. Progressive legislative reforms may also contribute to ensuring a fast and fair transition. This article examines how legal action and legislation may provide communities and rights-holders with pathways to climate justice – and sheds light on the need for a rights-centred approach by corporate actors and governments to the new energy transition.
On high-Taylor-number Taylor vortices
Authors: Deguchi Kengo
Published: July 2023

Axisymmetric steady solutions of Taylor–Couette flow at high Taylor numbers are studied numerically and theoretically. As the axial period of the solution shortens from approximately one gap length, the Nusselt number goes through two peaks before returning to laminar flow. In this process, the asymptotic nature of the solution changes in four stages, as revealed by the asymptotic analysis. When the aspect ratio of the roll cell is approximately unity, the solution has the Nusselt number proportional to the quarter power of the Taylor number, and captures quantitatively the characteristics of the classical turbulence regime. By shortening the axial period the Nusselt number can even reach the experimental value around the onset of the ultimate turbulence regime. However, at higher Taylor numbers, the theoretical predictions eventually underestimate the experimental values. An important consequence of the asymptotic analyses is that the mean angular momentum should become uniform in the core region unless the axial wavelength is too short. The theoretical scaling laws deduced for the steady solutions can be carried over to Rayleigh–Bénard convection.
Propulsion due to thermal streaming
Authors: Floryan J.M. , Panday S. , Aman S.A.
Published: July 2023

We demonstrate that the relative motion of horizontal parallel plates can be generated using patterned heating. This movement is driven by nonlinear thermal streaming associated with a pitchfork bifurcation. The propulsive effect is strongest when all the heating energy is concentrated in a single Fourier mode of the spatial heating pattern; it increases with a decrease in the Prandtl number and increases with the addition of a uniform heating component.
Infinite constant gap length trees in products of thick Cantor sets
Authors: McDonald Alex , Taylor Krystal
Published: July 2023

We show that products of sufficiently thick Cantor sets generate trees in the plane with constant distance between adjacent vertices. Moreover, we prove that the set of choices for this distance has non-empty interior. We allow our trees to be countably infinite, which further distinguishes this work from previous results on patterns in fractal sets. This builds on the authors’ previous work on graphs and distance sets over products of Cantor sets of sufficient Newhouse thickness.
ON SEPARATE CONTINUITY AND SEPARATE CONVEXITY: A SYNTHETIC TREATMENT FOR FUNCTIONS AND SETS
Authors: UYANIK METIN , KHAN M. ALI
Published: July 2023

This paper relies on nested postulates of separate, linear and arc-continuity of functions to define analogous properties for sets that are weaker than the requirement that the set be open or closed. This allows three novel characterisations of open or closed sets under convexity or separate convexity postulates: the first pertains to separately convex sets, the second to convex sets and the third to arbitrary subsets of a finite-dimensional Euclidean space. By relying on these constructions, we also obtain new results on the relationship between separate and joint continuity of separately quasiconcave, or separately quasiconvex functions. We present examples to show that the sufficient conditions we offer cannot be dispensed with.
ON MONOTONE INCREASING REPRESENTATION FUNCTIONS
Authors: KISS SÁNDOR Z. , SÁNDOR CSABA , YANG QUAN-HUI
Published: July 2023

Let
$k\ge 2$
be an integer and let A be a set of nonnegative integers. The representation function
$R_{A,k}(n)$
for the set A is the number of representations of a nonnegative integer n as the sum of k terms from A. Let
$A(n)$
denote the counting function of A. Bell and Shallit [‘Counterexamples to a conjecture of Dombi in additive number theory’, Acta Math. Hung., to appear] recently gave a counterexample for a conjecture of Dombi and proved that if
$A(n)=o(n^{{(k-2)}/{k}-\epsilon })$
for some
$\epsilon>0$
, then
$R_{\mathbb {N}\setminus A,k}(n)$
is eventually strictly increasing. We improve this result to
$A(n)=O(n^{{(k-2)}/{(k-1)}})$
. We also give an example to show that this bound is best possible.
Ballet in Ukraine: From Uncertainty to Defiance and Independence
Authors: Nikulina Ania
Published: July 2023

This article is dedicated to analyzing existing cultural tensions between nationalism and neo-imperialism through the prism of oral narratives of ballet training in post-Soviet Ukraine. I present and reflect on the results of a three-month-long ethnographic field study, which took place at a primary state-sponsored ballet school in Ukraine—the Kyiv State Choreographic School. My article seeks to investigate the role and position of Ukrainian state-sponsored ballet at a crossroads of political and cultural crisis, when a new identity may rise from the ruins of a previously constructed cultural monolith of Soviet ballet. I explore the complex history and present condition of classical ballet training in Kyiv, Ukraine, and reveal it as both a contested cultural space and an important barrier to political radicalization. I show that ballet training centers of Ukraine successfully resist co-optation by both neo-imperial and nationalist ideologies, forming robust and inclusive dancing communities that in many ways mirror structures of modern Ukrainian society.
Development of knee exoskeleton for capturing energy from human knee motion
Authors: Chen Bing , Tan Jialiang , Shi Chenpu , Zi Bin
Published: July 2023

In this paper, the design and experimental validation of a knee exoskeleton are presented. The exoskeleton can capture the negative work from the wearer’s knee motion while decreasing the muscle activities of the wearer. First, the human knee biomechanics during the normal walking is described. Then, the design of the exoskeleton is presented. The exoskeleton mainly includes a left one-way transmission mechanism, a right one-way transmission mechanism, and a front transmission mechanism. The left and right one-way transmission mechanisms are designed to capture the negative work from the wearer’s knee motion in the stance and swing phases, respectively. The front transmission mechanism is designed to transform the bidirectional rotation of the wearer’s knee joint into the generator unidirectional rotation. Additionally, the modeling and analysis of the energy harvesting of the exoskeleton is described. Finally, walking experiments are performed to validate the effectiveness of the proposed knee exoskeleton. The testing results verify that the developed knee exoskeleton can output a maximum power of 5.68 ± 0.23 W and an average power of 1.45 ± 0.13 W at a speed of 4.5 km/h in a gait cycle. The average rectus femoris and semitendinosus activities of the wearers in a gait cycle are decreased by 3.68% and 3.40%, respectively.
Why Do Issues “Whose Time Has Come” Stick Around? Attention Durability and the Case of Gun Control
Authors: Goss Kristin A. , Lacombe Matthew J.
Published: July 2023

In any healthy democracy, myriad policy issues compete for the public’s attention. Most remain on the periphery of politics, either because they achieve salience only in narrow communities of interest or because they grab headlines only for brief periods of time. But sometimes issues become what we term “durable attention items”—they capture public attention and sustain it over many years. Why? We focus on one such newly durable issue—gun control in the United States. Using an original dataset of roughly 4,500 letters to the editor over a 40-year period, we demonstrate that this once-episodic issue, long dominated by a narrow constituency of pro-gun advocates, has become a mainstay of mass politics. We show that the gun issue’s growing agenda status is due entirely to pro-regulation people mobilized by a combination of contextual factors, namely regularized mass shootings and efforts to relax gun policy, working in tandem with partisan polarization. Besides offering novel evidence of a fundamental shift in American gun politics, the study contributes to our theoretical understanding of how episodic issues come to command consistent political engagement over the long term.
Effect of zinc and protein content in different barley cultivars: use of controlled release matrices
Authors: Jiménez-Rosado Mercedes , Di Foggia Michele , Rosignoli Serena , Guerrero Antonio , Rombolà Adamo Domenico , Romero Alberto
Published: July 2023

Barley is one of the most consumed cereals, with many different cultivars available worldwide. Like other crops, its yield has been affected by climate change and soil degradation. This work proposes controlled-release protein-based matrices with incorporated zinc to improve barley seed germination and zinc content in the plant. Thus, the main objective of this study was to investigate the use of controlled-release protein-based matrices for massive crops, such as barley. Different barley cultivars of barley were studied: Barke, Golden Promise, Morex, WB-200, WB379, and WB-446. The seeds of each cultivar were also analyzed in order to explain the behavior of plants observed during the growth. To this end, the physico-chemical (FT-IR, Raman spectroscopy, and Zn concentration) and microstructural (SEM) properties of the different seeds were firstly evaluated to establish differences between the studied cultivars. In addition, the use of controlled-release soybean protein-based matrices without zinc (M) or with zinc incorporated (MZ) was evaluated as fertilizers in the different barley cultivars. In this sense, the use of these matrices as a zinc carrier improved seed germination and zinc content in the plants, indicating that the use of matrices improves the amount of zinc assimilated by the crops (up to 30 and 50% with M and MZ, respectively) and allows the proper root growth of all cultivars of barley. In conclusion, this article shows the potential of controlled-release protein-based matrices as substitutes for conventional fertilization.
Capturing the Zeitgeist: Preserving American Music and Culture in the Mashups of DJ Earworm
Authors: Yunek Jeffrey Scott
Published: July 2023

The discussion of narrative in mashups typically involves how a preexisting message is reinterpreted by the incorporation of new musical material. However, many scholars note how DJ Earworm's technique of creating new lyrics through the combination of samples from up to fifty different tracks conveys an original message that is distinct from its borrowed sources. In his various interviews, DJ Earworm elaborates that his mashups are original compositions that act as musical time capsules that capture the zeitgeist of the age. Nevertheless, DJ Earworm only provides brief commentary on the meaning of his mashups and there is no close examination of these narratives in the literature. This raises the question: To what degree do DJ Earworm's mashups reflect cultural issues in American society? By merging Zbikowski's concept of conceptual integration with Almén's theory of musical narrative, this paper will demonstrate how DJ Earworm's mashups show a consistent pattern of having complex narratives with cultural messages that resonate with contemporary issues in American society, including fossil fuel dependence, income inequality, and political and racial division.
HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems
Authors: van der Werf J. A. , Kapelan Z. , Langeveld J. G.
Published: July 2023

Model Predictive Control (MPC) of Urban Drainage Systems (UDS) has been established as a cost‐effective method to reduce pollution. However, the operation of large UDS (containing over 20 actuators) can only be optimized by oversimplifying the UDS dynamics, potentially leading to a decrease in performance and reduction in users' trust, thus inhibiting widespread implementation of MPC procedures. A Heuristic And Predictive Policy (HAPPy) was set up, relying on the dynamic selection of the actuators with the highest impact on the UDS functioning and optimizing those in real‐time. The remaining actuators follow a pre‐set heuristic procedure. The HAPPy procedure was applied to two separate UDS in Rotterdam with the control objective being the minimization of overflow volume in each of the two cases. Results obtained show that the level of impact of the actuators on the UDS functioning changes during an event and can be predicted using a Random Forest algorithm. These predictions can be used to provide near‐global optimal actuator settings resulting in the performance of the HAPPy procedure that is comparable to a full‐MPC control and outperforming heuristic control procedures. The number of actuators selected to obtain near‐global optimal settings depends on the UDS and rainfall characteristics showing an asymptotic real‐time control (RTC) performance as the number of actuators increases. The HAPPy procedure showed different RTC dynamics for medium and large rainfall events, with the former showing a higher level of controllability than the latter. For medium events, a relatively small number of actuators suffices to achieve the potential performance improvement.