bluuebunny/crossref_metadata_2025 huggingface dataset:
Framings in Indigenous futures thinking: barriers, opportunities, and innovations
Authors: Cheok Jessica , van Velden Julia , Fulton Elizabeth A. , Gordon Iain J. , Lyons Ilisapeci , Peterson Garry D. , Wren Liz , Hill Rosemary
Published: January 2025

Human societies face existential challenges on multiple fronts: climate change, biodiversity loss, altered biogeochemical flows, social unrest and injustices. Innovative solutions are needed to shift current trajectories towards a sustainable and just future. Futures thinking enables people to explore and articulate alternative futures and find pathways towards their desired futures. Indigenous people have the potential to make significant contributions to futures thinking because of their distinctive perspectives: the viewpoint of already living in a post-apocalyptic world in the context of colonisation, unique knowledges, worldviews, and perspectives on time, as well as significant contributions to safeguarding biological and cultural diversity. A body of literature is emerging where Indigenous peoples contribute to and lead futures thinking approaches; however, this literature is diffuse and highly diverse in its approaches and terminology. Thus, we take an innovation-seeking and systematic approach to (1) identify patterns and processes in futures thinking with, for, and by Indigenous people; (2) highlight innovative approaches; (3) bring together diverse and sector-specific terminology; and (4) foreground emerging strengths and weaknesses. We identified four framings of Indigenous futures thinking: Adaptation oriented, Participatory, Culturally grounded, and Indigenising. Factors contributing to innovation include strong involvement of Indigenous people in the research team, co-design, and authorship, using Indigenous methodologies, cultural protocols, and explicitly employing decolonisation and trauma-informed approaches. We spotlight the challenges of conducting an exhaustive literature review in an emerging field with inconsistent terminology (e.g., capturing regions where Indigeneity is contested). We also create a living glossary of terms to aid other researchers and communities in using and refining the suite of methods identified here, with the aim of stimulating further innovations in this field.
Ulam-hyres stability analysis and fractional operator implications on the Covid-19 virus dynamics with long-term vaccination effects
Authors: Farman Muhammad , Jamil Saba , Hincal Evren , Baleanu Dumitru , Sambas Aceng , Nisar Kottakkaran Sooppy
Published: January 2025

The COVID-19 pandemic has necessitated the development of highly efficient mathematical models to manage its spread, particularly concerning vaccination strategies. Traditional models, however, often fail to account for memory effects observed in real-world scenarios, which can be effectively captured using fractional derivatives. This paper introduces a novel COVID-19 model incorporating fractional-order derivatives to reflect better the dependence of the pandemic’s growth on historical events. By approximating the non-locality of fractional derivatives through a generalized Mittag-Leffler kernel, the model effectively captures long-term vaccination effects. To enhance the accuracy of numerical results, the model also integrates the concept of a two-step Lagrange polynomial. The local asymptotic stability of the disease-free equilibrium point is examined through sensitivity and qualitative analyses, particularly using the basic reproduction number,

$$ R_0 $$

R
0

. The proposed scheme is rigorously validated through fixed point theory, ensuring the model is evidence-based. A case study conducted in Saudi Arabia demonstrates the effectiveness of the proposed model, yielding successful verification through real-world numerical analysis. The results indicate that incorporating fractional derivatives leads to a more robust model, particularly in assessing the long-term impact of vaccination on the COVID-19 epidemic. The findings underscore the significant role of vaccination in reducing

$$ R_0 $$

R
0

and achieving a disease-free state. This work highlights the potential of fractional operators in epidemiological modeling, providing crucial insights into strategies for preventing the transmission of COVID-19 and similar diseases.
From latest buzzword to conceptual framework: Unraveling the complexities of democratic resilience
Authors: Walz Kevin , Merten Lion , Rosenthal Matthias , Niedringhaus Jana , Helgest Johannes
Published: January 2025

Resilience makes its debut in an increasing number of research areas, most recently also in democracy research. Even though progress has been made in conceptualizing democratic resilience, the concept still appears to be rather diffuse and underdeveloped. We address these shortcomings by (re-)conceptualizing democratic resilience through the lens of Gerring and Christensons’s criteria of conceptual goodness with a special focus on resonance, internal coherence, external differentiation, and theoretical utility. We argue that democratic resilience is best understood as a capacity that stems from various resources at different system levels. Drawing on these resources, the resilience capacity provides the democratic system with certain abilities that enable democratic actors to apply concrete strategies to deal with stressors. In doing so, the resilience capacity ultimately operates as a moderator in the stressors-processing that make certain outcomes more or less likely. We contribute to the existing literature by systematically strengthening the concept of democratic resilience and distinguishing it from neighbouring concepts like consolidation. We conclude with a brief outlook on how the developed conceptualization of democratic resilience could contribute to systemizing and advancing empirical research on the decline and survival of democracies in the future.
Stathmin 1 expression in neuroendocrine and proliferating prostate cancer
Authors: Shi Yingli , Yeh Yunshin A. , Cheng Siyuan , Gu Xin , Yang Shu , Li Lin , Khater Nazih P. , Kasper Susan , Yu Xiuping
Published: January 2025

Prostate cancer (PCa) is the second leading cause of cancer-related mortality among men in the United States. While PCa initially responds to androgen deprivation therapy, a significant portion progresses to castration-resistant PCa. Approximately 20–25% of these cases acquire aggressive neuroendocrine (NE) features, ultimately leading to neuroendocrine prostate cancer (NEPC). In this study, we investigated the expression of stathmin 1 (STMN1) across PCa subtypes using bioinformatics, western blotting, and immunohistochemical staining analyses in human and murine models. We found that elevated STMN1 expression correlated with high Gleason Scores, increased cell proliferation, and poor clinical outcomes in PCa patients. Notably, STMN1 expression was significantly higher in NEPC compared to prostate adenocarcinoma, suggesting its role in NEPC progression. Findings from TRAMP tumors, a murine NEPC model, further supported these results. In conclusion, STMN1 expression is elevated in advanced PCa, particularly in NEPC, suggesting its involvement in the progression of aggressive forms of PCa. While STMN1 shows potential as a diagnostic and prognostic marker for aggressive PCa, further studies are necessary to establish its clinical utility.
Targeting protein synthesis pathways in MYC-amplified medulloblastoma
Authors: Kumar Devendra , Kanchan Ranjana , Chaturvedi Nagendra K.
Published: January 2025

MYC is one of the most deregulated oncogenic transcription factors in human cancers. MYC amplification/or overexpression is most common in Group 3 medulloblastoma and is positively associated with poor prognosis. MYC is known to regulate the transcription of major components of protein synthesis (translation) machinery, leading to promoted rates of protein synthesis and tumorigenesis. MTOR signaling-driven deregulated protein synthesis is widespread in various cancers, including medulloblastoma, which can promote the stabilization of MYC. Indeed, our previous studies demonstrate that the key components of protein synthesis machinery, including mTOR signaling and MYC targets, are overexpressed and activated in MYC-amplified medulloblastoma, confirming MYC-dependent addiction of enhanced protein synthesis in medulloblastoma. Further, targeting this enhanced protein synthesis pathway with combined inhibition of MYC transcription and mTOR translation by small-molecule inhibitors, demonstrates preclinical synergistic anti-tumor potential against MYC-driven medulloblastoma in vitro and in vivo. Thus, inhibiting enhanced protein synthesis by targeting the MYC indirectly and mTOR pathways together may present a highly appropriate strategy for treating MYC-driven medulloblastoma and other MYC-addicted cancers. Evidence strongly proposes that MYC/mTOR-driven tumorigenic signaling can predominantly control the translational machinery to elicit cooperative effects on increased cell proliferation, cell cycle progression, and genome dysregulation as a mechanism of cancer initiation. Several small molecule inhibitors of targeting MYC indirectly and mTOR signaling have been developed and used clinically with immunosuppressants and chemotherapy in multiple cancers. Only a few of them have been investigated as treatments for medulloblastoma and other pediatric tumors. This review explores concurrent targeting of MYC and mTOR signaling against MYC-driven medulloblastoma. Based on existing evidence, targeting of MYC and mTOR pathways together produces functional synergy that could be the basis for effective therapies against medulloblastoma.
When conventional approach in toxicity assays falls short for nanomedicines: a case study with nanoemulsions
Authors: Nikolić Ines , Đoković Jelena , Mehn Dora , Guerrini Giuditta , Savić Snežana , Jordan Olivier , Borchard Gerrit
Published: January 2025

The aim of this study was to assess the critical quality attributes of parenteral nanoemulsion formulations by measuring several physicochemical parameters and linking them to their in vitro performance, illustrating how simplistic and routinely used approaches are insufficient for understanding a potential nanomedicine. Physicochemical characterization should encompass size and size distribution through at least two orthogonal techniques, such as dynamic light scattering (DLS) and electron microscopy, with added value from analytical ultracentrifugation. In vitro toxicity assessment was performed using three different assays to determine mitochondrial activity (WST-1), membrane integrity (lactate dehydrogenase release (LDH) assay), and cell viability (propidium iodide (PI) staining). Special focus was placed on estimating appropriate incubation times for relevant results in biological investigations. All formulations had an average diameter of around 100 nm. Conclusions regarding in vitro safety were assay-dependent: LDH and PI-based assays showed good correlation, while the WST-1 assay indicated that the non-PEGylated formulation altered mitochondrial activity more significantly compared to the PEGylated ones. The study underlined that the selection of appropriate cytotoxicity assays should be based on the possible mechanism of cellular perturbation. Alternatively, different aspects of cellular toxicity should be tested. Additionally, there is a need for well-designed controls to overcome nanoparticle scattering effects and avoid potentially false high toxicity results, which was demonstrated. Combining orthogonal, well-designed physicochemical and biological assays in a standardized manner as an initial step in the reliable preclinical characterization of nanomedicines is suggested. This represents a key aspect of new methodologies in nanomedicine characterization.

Graphical abstract
Regional Brain Analysis and Machine Learning Techniques for Classifying Familiar and Unfamiliar Faces Using EEG
Authors: Bardak F. Kebire , Temurtaş Feyzullah
Published: January 2025

Among the processes critical for human social interactions are perception, memorization, and bonding, and the ability to recognize familiar and unfamiliar faces is one of the most essential aspects of the human brain. This is a valuable communication skill, as well as remembering people and interpersonal interactions to recognize the faces of the people. Given the importance of these aspects of cognitive functioning, the present research seeks to establish the neural basis for recognizing familiar and unfamiliar faces from EEG data through a regional brain perspective and simple neural networks. The EEG data used in this research were gathered from typically developed subjects, and the features were derived using discrete wavelet transform (DWT). These features were then employed for the classification of the network using three different algorithms, which include k-nearest neighbors (KNN), support vector machines (SVM), and probabilistic neural networks (PNN). KNN was seen to have the highest classification accuracy than the other classifiers; the accuracy was considered for different brain regions and all the channels. The temporal and occipital lobes were found to be involved in face recognition, and the patterns of activation differed between familiar and unfamiliar faces. This work contributes to the literature by describing how face recognition is implemented in the brain, which areas of the brain are most important, and by comparing machine learning techniques for classifying the EEG signal. These findings are helpful for the current literature. They can help to inform future research into the neural structure of face recognition and what this might mean for prosopagnosia and similar conditions.
Plant Cell Wall-Like Soft Materials: Micro- and Nanoengineering, Properties, and Applications
Authors: Koshani Roya , Pitcher Mica L. , Yu Jingyi , Mahajan Christine L. , Kim Seong H. , Sheikhi Amir
Published: January 2025

Plant cell wall (CW)-like soft materials, referred to as artificial CWs, are composites of assembled polymers containing micro-/nanoparticles or fibers/fibrils that are designed to mimic the composition, structure, and mechanics of plant CWs. CW-like materials have recently emerged to test hypotheses pertaining to the intricate structure–property relationships of native plant CWs or to fabricate functional materials. Here, research on plant CWs and CW-like materials is reviewed by distilling key studies on biomimetic composites primarily composed of plant polysaccharides, including cellulose, pectin, and hemicellulose, as well as organic polymers like lignin. Micro- and nanofabrication of plant CW-like composites, characterization techniques, and in silico studies are reviewed, with a brief overview of current and potential applications. Micro-/nanofabrication approaches include bacterial growth and impregnation, layer-by-layer assembly, film casting, 3-dimensional templating microcapsules, and particle coating. Various characterization techniques are necessary for the comprehensive mechanical, chemical, morphological, and structural analyses of plant CWs and CW-like materials. CW-like materials demonstrate versatility in real-life applications, including biomass conversion, pulp and paper, food science, construction, catalysis, and reaction engineering. This review seeks to facilitate the rational design and thorough characterization of plant CW-mimetic materials, with the goal of advancing the development of innovative soft materials and elucidating the complex structure–property relationships inherent in native CWs.
Himitsu Bako of NO2 Mixtures: Characterization of NO2 Reference Material Using FTIR Spectroscopy in Middle Infrared Region
Authors: Kim Mi Eon , Berezkin Kirill , Saturno Jorge , Werwein Viktor , Li Gang , Domanskaya Alexandra
Published: January 2025

In this work, we investigate how much information a conventional infrared spectroscopic technique (FTIR) can yield for NO2 reference materials in the range of concentrations between 100 to 2500 μmol/mol. The amount fraction of 100 μmol/mol corresponds to the actual maximum for NO2 emissions by modern Euro 6 vehicles and is suitable for Portable Emissions Measurement Systems (PEMS) calibration. A set of measurements of four reference mixtures was performed. For the analysis, we developed an efficient and simple algorithm, based on the integration of rovibrational bands, yielding the molar fractions of NO2 (including dimer) and several impurities, such as N2O and HNO3. It resembles a Japanese puzzle box, Himitsu Bako, since different mixture components should be addressed in a certain order to unravel a complete composition. The algorithm was successfully applied to the recorded spectra. For example, the uncertainties for low NO2 amount fractions were shown to be limited essentially by the quality of reference spectroscopic data for the monomer (HITRAN database in the current work), and not by the measurement procedure. Shortcomings, further development, and improvements of the experimental set-up as well as of the evaluation algorithm are addressed.
Adjudicating Climate Protest as a Tool of Modern Republicanism
Authors: Kuznetsov Dmitrii
Published: January 2025

Through the prism of republican theory, the paper discusses the nature of environmental protests and the judiciary’s responses to the related cases. The text argues that climate protesters act not solely to realise their freedom of assembly but also to understand their obligations to the environment and the community of citizens. An argumentation grounded in their belief that they were obliged to protest against climate change and even commit certain unlawful acts due to the state of necessity could give their defence more strength, on the one hand, and inspire the courts to be more active in forcing governments to act on the climate cause, on the other hand. The paper consists of two sections, with the first discussing theoretical approaches to environmental citizenship, the alleged duty to protest against climate change, and their relationships with republicanism. The second section scrutinises case law from selected domestic and international courts dealing with climate protests. Specifically, it analyses the justifications for the right to protest against climate change presented in the submissions of applicants or defendants before the courts and the reasoning employed by the courts.
Effects of Stockpiling on Topsoil Biogeochemistry for Semiarid Mine Reclamation
Authors: Ledesma Jessica , Neilson Julia W. , Maier Raina M. , Babst-Kostecka Alicja , Rasmussen Craig
Published: January 2025

Stockpiling and storage of topsoil for use in reclamation and revegetation are common practices for many mining operations. However, stockpiling can lead to significant changes in topsoil physical and biogeochemical properties that may be detrimental to reclamation. The objective of this research was to assess the effect of long-term stockpiling on soil biogeochemical properties in a semiarid region. We hypothesized that soil properties would change systematically with depth reflecting a shift to anaerobic conditions and resulting in a general decrease in soil health. To address this hypothesis, boreholes > 20-m deep were drilled into a 14-year-old topsoil stockpile at a copper mine in Arizona and samples collected every ~ 75 cm. Samples were analyzed for soil DNA biomass, texture, general agronomic properties, mineral composition, oxalate and dithionite extraction of active mineral phases, and total elemental composition. Depth profiles revealed non-systematic changes in biogeochemical variables with depth, including variation in soil DNA biomass, organic matter (OM), extractable nitrate (NO3-N) and ammonium (NH4-N) nitrogen, plant-available manganese (Mn) and iron (Fe), and oxalate-extractable Mn and Fe. Differences in biogeochemical properties were associated with zones of variable redox state mediated by OM content and layer depth. Anaerobic zones were observed at depths greater than 4 m where OM > 1%, and aerobic zones were observed at depths up to 15 m where OM < 1%. This study demonstrates the importance of stockpile composition on biogeochemical processes during storage and contributes to improved understanding of topsoil management as a resource for reclamation of degraded mine lands in semiarid environments.
Automatic synthesis of insects bioacoustics using machine learning: a systematic review
Authors: Kyalo Henry , Tonnang Henri , Egonyu James , Olukuru John , Tanga Chrysantus , Senagi Kennedy
Published: January 2025

The application of machine learning has received increasing attention in the synthesis of insect sounds to preserve biodiversity. This study reviewed current literature on the application of these techniques in the automatic synthesis of insect bioacoustic and their applications in insects as food and feed, improving pest management, and as well as managing pollinators. To achieve this, the study used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to identify, screen, and include the final articles used in this review, based on criteria such as papers addressing machine learning in insect acoustics, biodiversity, ecology conservation, etc. This study revealed that most of the researchers used secondary data and the microphone was the common tool used to record sound signals. Sound signals were mainly pre-processed using techniques such as denoising, segmentation, and windowing. Sound signal classification algorithms were categorized mainly as shallow and deep machine learning algorithms. In the shallow machine learning algorithms, the most common method of feature extraction was the Mel-Frequency Cepstral Coefficient (MFCC) and the Support Vector Machine (SVM) was the most commonly used algorithm. In deep learning, spectrogram image features were widely extracted and the Convolutional Neural Network (CNN) was mostly used to synthesize the spectral features. This paper also reviewed recent developments in insect bioacoustics signals processing, applications, and future directions. Generally, machine learning algorithms can be applied and deployed successfully to different insects’ automatic synthesis problems to improve the production of insects (as food and/or feed), and improve/preserve diversity and life on Earth.
Waging warfare against states: the deployment of artificial intelligence in cyber espionage
Authors: Rosli Wan Rosalili Wan
Published: January 2025

Cyber espionage has significantly been viewed as a risk towards nation-states, especially in the area of security and protection of Critical National Infrastructures. The race against digitisation has also raised concerns about how emerging technologies are defining how cyber activities are linked to waging warfare between States. Real-world crimes have since found a place in cyberspace, and with high connectivity, has exposed various actors to various risks and vulnerabilities, including cyber espionage. Cyber espionage has always been a national security issue as it does not only target States but also affects public–private networks, corporations and individuals. The challenge of crimes committed within the cyber realm is how the nature of cybercrimes distorts the dichotomy of state responsibility in responding to cyber threats and vulnerabilities. Furthermore, the veil of anonymity and emerging technologies such as artificial intelligence have further provided opportunities for a larger scale impact on the state for such crime. The imminent threat of cyber espionage is impacting the economic and political interactions between nation-states and changing the nature of modern conflict. Due to these implications, this paper will discuss the current legal landscape governing cyber espionage and the impact of the use of artificial intelligence in the commission of such crimes.
MORKO: A Multi-objective Runge–Kutta Optimizer for Multi-domain Optimization Problems
Authors: Kalita Kanak , Jangir Pradeep , Pandya Sundaram B. , Alzahrani Ahmed Ibrahim , Alblehai Fahad , Abualigah Laith , Ezugwu Absalom E.
Published: January 2025

In the current landscape, there is a rapid increase in the creation of new algorithms designed for specialized problem scenarios. The performance of these algorithms in unfamiliar or practical settings often remains untested. This paper presents a new development, the multi-objective Runge–Kutta optimizer (MORKO), which is built upon the principles of elitist non-dominated sorting and crowding distance. The goal is to achieve superior efficiency, diversity, and robustness in solutions. MORKO effectiveness is further enhanced by incorporating various strategies that maintain a balance between diversity and execution efficiency. This approach not only directs the search toward optimal regions but also ensures that the process does not become stagnant. The efficiency of MORKO is compared against renowned algorithms like the multi-objective marine predicator algorithm (MOMPA), multi-objective gradient-based optimizer (MOGBO), multi-objective evolutionary algorithm based on decomposition (MOEA/D), and non-dominated sorting genetic algorithm (NSGA-II) on several test benchmarks such as ZDT, DTLZ, constraint (CONSTR, TNK, SRN, BNH, OSY and KITA) and real-world engineering design (brushless DC wheel motor, safety isolating transformer, helical spring, two-bar truss, welded beam, disk brake, tool spindle and cantilever beam) problems. We used unique, non-overlapping performance metrics for this comparison and suggested a fresh correlation analysis technique for exploration. The MORKO algorithm outcomes were rigorously tested and confirmed using the non-parametric statistical evaluations. The MORKO algorithm proves to excel in deriving comprehensive and varied solutions for many tests and practical challenges, owing to its multifaceted features. Looking ahead, MORKO has potential applications in complex engineering and management tasks.
Data-driven multifidelity surrogate models for rocket engines injector design
Authors: Zapata Usandivaras Jose Felix , Bauerheim Michael , Cuenot Bénédicte , Urbano Annafederica
Published: January 2025

Surrogate models of turbulent diffusive flames could play a strategic role in the design of liquid rocket engine combustion chambers. The present article introduces a method to obtain data-driven surrogate models for coaxial injectors, by leveraging an inductive transfer learning strategy over a U-Net with available multifidelity Large Eddy Simulations (LES) data. The resulting models preserve reasonable accuracy while reducing the offline computational cost of data-generation. First, a database of about 100 low-fidelity LES simulations of shear-coaxial injectors, operating with gaseous oxygen and gaseous methane as propellants, has been created. The design of experiments explores three variables: the chamber radius, the recess-length of the oxidizer post, and the mixture ratio. Subsequently, U-Nets were trained upon this dataset to provide reasonable approximations of the temporal-averaged two-dimensional flow field. Despite the fact that neural networks are efficient non-linear data emulators, in purely data-driven approaches their quality is directly impacted by the precision of the data they are trained upon. Thus, a high-fidelity (HF) dataset has been created, made of about 10 simulations, to a much greater cost per sample. The amalgamation of low and HF data during the the transfer-learning process enables the improvement of the surrogate model’s fidelity without excessive additional cost.
Retrospective Evaluation of Anesthesia in Patients Undergoing Surgery after the February 6, 2023 Earthquake in Turkey
Authors: Erkilic Ezgi , Kurtay Mehlika , Yılmaz Gülay , Demirörs Ahmet , Baltacı Esra Mahmut , Sözsahibi Düşüm , Efe Ali Furkan , Gümüş Tülin , Kanbak Orhan , Güleç Handan , Özcan Ayça Dumanlı , Öztürk Levent
Published: January 2025

Throughout human history, numerous natural disasters, particularly earthquakes, have caused significant destruction to civilizations. On February 6, 2023, 2 major earthquakes struck Turkey. The first occurred at 04:17 local time with a magnitude of 7.7 (37.288N-37.043E) centered in Pazarcık, and the second at 13:24 with a magnitude of 7.6 (38.089N-37.239E) centered in Elbistan. Both earthquakes affected a vast area encompassing 11 cities. These 2 devastating earthquakes resulted in the destruction and damage of many buildings, affecting over 14 million people. More than 40 000 people lost their lives, and thousands were injured and left homeless. Turkey, a country frequently affected by earthquakes due to its geographical location, experienced 2 consecutive major earthquakes on the same day, marking a tragic event in its history.
Suboptimal household investment and information-processing frictions: Evidence from 529 college savings plans
Authors: Li James J. , Mitchell Olivia S. , Zhu Christina
Published: January 2025

We use the 529 college savings plan setting to investigate whether and why households make suboptimal choices to invest in local assets. We estimate that 67% of open accounts between 2010 and 2020 were located suboptimally due to the plans’ tax inefficiencies and high expenses. Over the accounts’ projected lifetimes, such investments yielded expected losses of 8% on average or $15.6 billion in 2020 alone. We then investigate why suboptimal investment is so prevalent. Consistent with households’ lack of understanding of state-level tax benefits, we find that a meaningful proportion of households does not account for the potential tax benefits and costs of local versus nonlocal 529 investment. Household financial literacy and plan disclosure complexity appear to explain suboptimal investment patterns, which further supports the role of information-processing frictions. Our study presents novel evidence on individuals’ preferences for local assets and how information-processing frictions shape their investment decisions, reducing their financial well-being.
Living with psychosis in West and Southeast Africa: SUCCEED Africa’s four-country situation analysis
Authors: Omobowale Olubukola , Greenley Rachel , Ryan Grace , Ogunmola Olusegun , Dzapasi Lloyd , Jimmy Abraham , Sefasi Anthony , Olusanmi Mayowa , Esliker Rebecca , Koroma Alhaji , Afolayan Adeola , Tamambang Rita , Munetsi Epiphania , Mambulasa Janet , Kakuma Ritsuko , Chibanda Dixon , Omigbodun Olayinka , Eaton Julian
Published: January 2025

As part of the formative work of the SUCCEED Africa consortium, we followed a participatory process to identify existing gaps and resources needed for the development and implementation of a rights-based intervention for people with lived experience of psychosis in Malawi, Nigeria, Sierra Leone and Zimbabwe.

In 2021, we conducted a desk review of published and grey literature on psychosis in the four SUCCEED countries. Using an adapted version of the PRIME situation analysis template, data were extracted across the five domains of the WHO Community-Based Rehabilitation (CBR) Matrix: health, education, livelihoods, social and empowerment. This was supplemented with insights from personal communications with key stakeholders and the lived and professional experiences of team members.

Findings indicate that people with lived experience of psychosis have limited access to services and opportunities across the five CBR domains. Participation in social, religious, empowerment and political activities is restricted due to stigma and a lack of advocacy.

People with lived experience of psychosis in SUCCEED countries are not generally able to access support in line with essential components of CBR. There is a need for their greater inclusion in policy and advocacy activities.
The flow field due to a sphere moving in a viscous, density-stratified fluid
Authors: Patibandla Ramana , Roy Anubhab , Subramanian Ganesh
Published: January 2025

In this paper, we study the disturbance velocity and density fields induced by a sphere translating vertically in a viscous density-stratified ambient. Specifically, we consider the limit of a vanishingly small Reynolds number

$(Re = \rho U a/\mu \ll 1)$

, a small but finite viscous Richardson number

$(Ri_v = \gamma a^3g/\mu U\ll 1)$

and large Péclet number

$(Pe = Ua/D\gg 1)$

. Here,

$a$

is the sphere's radius,

$U$

its translational velocity,

$\rho$

an appropriate reference density within the framework of the Boussinesq approximation,

$\mu$

the ambient viscosity,

$\gamma$

the absolute value of the background density gradient, g is acceleration due to gravity and

$D$

the diffusivity of the stratifying agent. For the scenario where buoyancy forces first become comparable to viscous forces at large distances, corresponding to the Stokes-stratification regime defined by

$Re \ll Ri_v^{1/3} \ll 1$

for

$Pe \gg 1$

, important flow features have been identified by Varanasi & Subramanian (J. Fluid Mech., vol. 949, 2022, A29) – these include a vertically oriented reverse jet, and a horizontal axisymmetric wake, on scales larger than the primary (stratification) screening length of

${O}(aRi_v^{-1/3})$

. Here, we study the reverse-jet region in more detail, and show that it is only the central portion of a columnar structure with multiple annular cells concentric about the rear stagnation streamline. In the absence of diffusion, corresponding to

$Pe = \infty$

$( \beta _\infty = Ri_v^{1/3}Pe^{-1} = 0)$

, this columnar structure extends to downstream infinity with the number of annular cells diverging in this limit. We provide expressions for the boundary of the structure, and the number of cells within, as a function of the downstream distance. For small but finite

$\beta _\infty$

, two length scales emerge in addition to the primary screening length – a secondary screening length of

${O}(aRi_v^{-1/2}Pe^{1/2})$

where diffusion starts to smear out density variations across cells, leading to exponentially decaying density and velocity fields; and a tertiary screening length,

$l_t \sim {O}(aRi_v^{-1/2}Pe^{1/2}[\zeta + \frac {13}{4}\ln {\zeta } + ({13^2}/{4^2})({\ln \zeta }/{\zeta })])$

with

$\zeta = \frac {1}{2}\ln ({\sqrt {{\rm \pi} }Ri_v^{-1}Pe^3}/{2160})$

, beyond which the columnar structure ceases to exist. The latter causes a transition from a vertical to a predominantly horizontal flow, with the downstream disturbance fields reverting from an exponential to an eventual algebraic decay, analogous to that prevalent at large distances upstream.
The fast radio burst population energy distribution
Authors: Arcus Wayne R. , James Clancy , Ekers Ron , Macquart Jean-Pierre , Sadler Elaine , Wayth Randall B. , Bannister Keith , Deller Adam T. , Flynn Chris , Glowacki Marcin , Gordon Alexa , Marnoch Lachlan , Ryder Stuart , Shannon Ryan M.
Published: January 2025

We examine the energy distribution of the fast radio burst (FRB) population using a well-defined sample of 63 FRBs from the Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, 28 of which are localised to a host galaxy. We apply the luminosity-volume (

$V/V_{\mathrm{max}}$

) test to examine the distribution of these transient sources, accounting for cosmological and instrumental effects, and determine the energy distribution for the sampled population over the redshift range

$0.01 \lesssim z \lesssim 1.02$

. We find the distribution between

$10^{23}$

and

$10^{26}$

J Hz

$^{-1}$

to be consistent with both a pure power-law with differential slope

$\gamma=-1.96 \pm 0.15$

, and a Schechter function with

$\gamma = -1.82 \pm 0.12$

and downturn energy

$E_\mathrm{max} \sim 6.3 \, \times 10^{25}$

J Hz

$^{-1}$

. We identify systematic effects which currently limit our ability to probe the luminosity function outside this range and give a prescription for their treatment. Finally, we find that with the current dataset, we are unable to distinguish between the evolutionary and spectral models considered in this work.
C/O ratios in self-gravitating protoplanetary discs with dust evolution
Authors: Molyarova Tamara , Vorobyov Eduard , Akimkin Vitaly
Published: January 2025

Elemental abundances, particularly the C/O ratio, are seen as a way to connect the composition of planetary atmospheres with planet formation scenario and the disc chemical environment. We model the chemical composition of gas and ices in a self-gravitating disc on timescales of 0.5 Myr since its formation to study the evolution of C/O ratio due to dust dynamics and growth and phase transitions of the volatile species. We use the thin-disc hydrodynamic code FEOSAD, which includes disc self-gravity, thermal balance, dust evolution, and turbulent diffusion, and treats dust as a dynamically different and evolving component interacting with the gas. It also describes freeze-out, sublimation, and advection of four most abundant volatile species: H

$_2$

O, CO

$_2$

, CH

$_4$

, and CO. We demonstrate the effect of gas and dust substructures such as spirals and rings on the distribution of volatiles and C/O ratios, including the formation of multiple snowlines of one species, and point out the anticorrelation between dust-to-gas ratio and total C/O ratio emerging due to the contribution of oxygen-rich ice mantles. We identify time and spatial locations where two distinct trigger mechanisms for planet formation are operating and differentiate them by C/O ratio range: wide range of the C/O ratios of

$0-1.4$

for streaming instability, and a much narrower range

$0.3-0.6$

for gravitational instability (with the initial value of 0.34). This conclusion is corroborated by observations, showing that transiting exoplanets, which possibly experienced migration through a variety of disc conditions, have significantly larger spread of C/O in comparison with directly imaged exoplanets likely formed in gravitationally unstable outer disk regions. We show that the ice-phase

$\textrm{C/O}\approx$

0.2–0.3 between the CO, CO

$_2$

, and CH

$_4$

snowlines corresponds to the composition of the Solar system comets, that represent primordial planetesimals.
Intergenerational trends in body size among Moscow’s young adults: socio-demographic influences of the 20th century
Authors: Khafizova Ainur A. , Negasheva Marina A. , Movsesian Alla A.
Published: January 2025

This study aimed to investigate the influence of socio-demographic and epidemiological factors on the secular changes in body size indicators (height, weight, and BMI) among young adults aged 17–22 years in Moscow from the early 20th century to the present. Published average anthropometric data from screening surveys conducted from 1880/1925–26 to 2020–21 were analysed (4,823 males and 5,952 females), along with demographic data from the Federal State Statistics Service of the Russian Federation. Findings revealed consistent anthropometric trends and strong associations between secular changes in body size of Moscow youth and socio-demographic indicators such as population size, life expectancy, and infant mortality rates. An increase in height and weight was noted against the backdrop of urbanisation, increased life expectancy, and reduced infant mortality. These results indicate that the urbanisation process and the transformation of the epidemiological landscape in 20th-century Russia – marked by enhancements in public health, modernisation of the healthcare system, and medical advancements – have had a significant impact on changes in body size across generations. Notably, from the mid-20th century onwards, with the exception of the final decade, conditions favourable to growth and development were established, culminating in a significant increase in definitive anthropometric parameters across successive generations. The findings underscore the imperative for policymakers to bolster investments in urban development, healthcare, and education. Such strategic investments are essential for sustaining and amplifying the positive physical development trends witnessed.
Fiscal decentralization and energy intensity: evidence from a quasi-natural experiment of VAT revenue-sharing reform in China
Authors: Pang Yumeng , Wang Mengmeng
Published: January 2025

The impact of fiscal decentralization on energy intensity has been a long-standing subject of interest and debate. However, to date, there has been a notable absence of studies delving into the effects of fiscal decentralization on energy intensity from the vantage point of tax sharing. This investigation explores the effects of China’s value-added tax (VAT) revenue-sharing reform on energy intensity using prefecture-level city data from 2006 to 2020. Results show a correlation between an increased proportion of VAT revenue sharing and higher regional energy intensity. Heightened competition among local governments amplifies this impact, while environmental regulations and technological innovation mitigate it. Our findings contribute to a more scientifically grounded formulation of the revenue-sharing ratio between central and local governments, aiming to reduce local energy intensity.
An approach towards mobile robot recovery due to vision sensor failure in vSLAM systems using ROS
Authors: Mulubika Chibaye , Schreve Kristiaan
Published: January 2025

This paper proposes a mobile robot recovery mechanism for low-cost robotic systems due to vision sensor failure in vSLAM systems. The approach takes advantage of ROS architecture and adopts the Shannon Nyquist sampling theory to selectively sample path parameters that will be used for back travel in case of vision sensor failure. As opposed to point clouds normally used to store vSLAM data, this paper proposes to store and use lightweight variables namely distance between sampled points, velocity combinations, i.e., linear and angular velocity, sampled period, and yaw angle values to describe the robot path and reduce the memory space required to store these variables. In this study, low-cost robotic systems typically using cameras aided by proprioceptive sensors such as IMU during vSLAM activities are investigated. A demonstration is made on how the ROS architecture can be used in a scenario where vision sensing is adversely affected, resulting in mapping failure. Additionally, a recommendation is made for adoption of the approach for vSLAM platforms implemented on both ROS1 and ROS2. Furthermore, a proposal is made to add an additional layer to vSLAM systems that will be exclusively used for back travel in case of vision loss during vSLAM activities resulting in mapping failure.
Local scale carbon stock measurements, including deep soil layers, in a terra firme forest in northwestern Amazon
Authors: Duque Alvaro , Gómez-Correa Luisa F. , Barona-Colmenares Andrés Alberto , Castaño Nicolás , Davies Stuart , Zuleta Daniel , Muller-Landau Helene C.
Published: January 2025

Most studies aiming to quantify carbon stocks in tropical forests have focused on aboveground biomass, omitting carbon in soils and woody debris. Here, we quantified carbon stocks in soils up to 3 m depth, woody debris, and aboveground and belowground tree biomass for the 25-ha Amacayacu Forests Dynamics plot in the northwestern Amazon. Including soils to 3 m depth, total carbon stocks averaged 358.9 ± 24.2 Mg C ha−1, of which soils contributed 53%, biomass 44.2%, and woody debris 2.7%. When only including soils to 0.5 m depth, carbon stocks diminished to 222.1 Mg C ha−1 and biomass became the largest contributor. Among 1-ha subplots, total carbon stocks were correlated with soil carbon stocks at ≥0.5 m depth, belowground biomass of all trees, and aboveground biomass of trees ≥60 cm DBH. Our results support the assumption of biomass as the likely largest carbon source associated with land use change in northwestern Amazonia. However, mining and erosion following land use change could also promote a significant release of carbon from soil, the largest carbon stock. To improve the global carbon balance, we need to better quantify total carbon stocks and dynamics in tropical forests beyond aboveground biomass.
Optimizing distributed practice online
Authors: Rogers John , Nakata Tatsuya , Chiu Ming Ming
Published: January 2025

This study conceptually replicates Cepeda, Coburn, Rohrer, Wixted, Mozer, & Pashler’s (2009, Experiment 1) study on the effects of distributed practice on second language (L2) vocabulary learning to examine its generalizability to a new context and population sample. The secondary focus of the paper is to examine the challenges and affordances of online data collection and participant recruitment sites. Both the original and our study examined the effects of distributed practice on two study sessions to learn L2 vocabulary assessed on a 10-day delayed posttest. Our results showed that the spaced conditions significantly outperformed the massed condition, mirroring the original study’s findings. However, Cepeda et al.’s (2009) participants outscored our participants by 10–20% (in each experimental group) on the posttest. While these findings highlight the benefits of spacing towards learning and memory, they also underscore the challenges researchers may face when conducting experimental research in online environments.
Compact mmWave measurement system for array antennas in a production environment
Authors: Obermaier Martin , Deckert Thomas , Laabs Martin , Plettemeier Dirk
Published: January 2025

Millimeter wave antenna arrays are essential components of modern communication and radar systems. To produce these devices in large quantities, manufacturers require fast and reliable measurement equipment. The measurement equipment needs to ensure the quality, interoperability, and adherence to regulatory norms of the produced devices. In this work, we present an active probe array structure (PAS), which enables fast, compact, and reliable over-the-air (OTA) measurements of radiation characteristics. No relative movement between the antenna under test (AUT) and the active PAS is required, making the system very suitable for cost-effective large-scale characterization and commercial production test scenarios. We demonstrate and discuss how a near-field (NF) OTA measurement performed by this active PAS system can be used to reconstruct the far-field (FF) antenna radiation behavior of AUTs using an NF to FF correlation approach.
Uncertainties About the Role of River and Mangrove Dissolved Inorganic Carbon and Alkalinity Loads in Buffering the Great Barrier Reef Lagoon
Authors: Rosentreter Judith A. , Eyre Bradley D.
Published: January 2025

Terrestrial dissolved inorganic carbon (DIC) and total alkalinity (TAlk) loads have contrasting effects on the pH and carbonate chemistry of the coastal ocean. While TAlk can buffer against ocean acidification, elevated exports of free CO2 can further exacerbate ocean acidification. In this study, we quantify terrestrial DIC and TAlk loads from rivers and mangrove floodplains across six bioregions and varying flow conditions to assess their impact on the buffering capacity of the Great Barrier Reef (GBR) lagoon in Australia. For a mid‐flow year, median terrestrial DIC and TAlk loads ranged from 0.72 to 0.89 Tg C yr−1 and 0.26 to 1.03 Tg C yr−1, respectively. We find that mangrove‐dominated terrestrial inputs only have a small influence on the whole GBR but contribute 12.5% (range: 1.9%–45.7%) of the DIC and 18.7% (range: 2.8%–68.2%) of the TAlk inner shelf inventory. Depending on the approach used to estimate TAlk loads, mangroves have a potential short‐term buffering effect on near‐shore coastal waters due to higher TAlk loads. However, long‐term mangrove TAlk production via pyrite formation complicates this interpretation, highlighting the need for ongoing monitoring to understand the complex interplay between terrestrial inputs and their effect on the GBR carbonate chemistry.