bluuebunny/crossref_metadata_2025_split huggingface dataset:
The application strategy of liposomes in organ targeting therapy
Authors: Xun Zengyu , Li Tianqi , Xue Xue 
Published: April 2024

AbstractLiposomes—microscopic phospholipid bubbles with bilayered membrane structure—have been a focal point in drug delivery research for the past 30 years. Current liposomes possess a blend of biocompatibility, drug loading efficiency, prolonged circulation and targeted delivery. Tailored liposomes, varying in size, charge, lipid composition, and ratio, have been developed to address diseases in specific organs, thereby enhancing drug circulation, accumulation at lesion sites, intracellular delivery, and treatment efficacy for various organ‐specific diseases. For further successful development of this field, this review summarized liposomal strategies for targeting different organs in series of major human diseases, including widely studied cardiovascular diseases, liver and spleen immune diseases, chronic or acute kidney injury, neurodegenerative diseases, and organ‐specific tumors. It highlights recent advances of liposome‐mediated therapeutic agent delivery for disease intervention and organ rehabilitation, offering practical guidelines for designing organ‐targeted liposomes.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Biology‐Inspired Nanomaterials > Lipid‐Based Structures
Comparative transcriptome analysis reveals the redirection of metabolic flux from cell growth to astaxanthin biosynthesis in Yarrowia lipolytica
Authors: Wang Dan‐Ni , Yu Chen‐Xi , Feng Jie , Wei Liu‐Jing , Chen Jun , Liu Zhijie , Ouyang Liming , Zhang Lixin , Liu Feng , Hua Qiang 
Published: April 2024

AbstractEngineering Yarrowia lipolytica to produce astaxanthin provides a promising route. Here, Y. lipolytica M2 producing a titer of 181 mg/L astaxanthin was isolated by iterative atmospheric and room‐temperature plasma mutagenesis and diphenylamine‐mediated screening. Interestingly, a negative correlation was observed between cell biomass and astaxanthin production. To reveal the underlying mechanism, RNA‐seq analysis of transcriptional changes was performed in high producer M2 and reference strain M1, and a total of 1379 differentially expressed genes were obtained. Data analysis revealed that carbon flux was elevated through lipid metabolism, acetyl‐CoA and mevalonate supply, but restrained through central carbon metabolism in strain M2. Moreover, upregulation of other pathways such as ATP‐binding cassette transporter and thiamine pyrophosphate possibly provided more cofactors for carotenoid hydroxylase and relieved cell membrane stress caused by astaxanthin insertion. These results suggest that balancing cell growth and astaxanthin production may be important to promote efficient biosynthesis of astaxanthin in Y. lipolytica.
Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
Authors: Koszczał Grzegorz , Dobrosolski Jan , Matuszek Mariusz , Czarnul Paweł 
Published: April 2024

AbstractIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were able to find non-default GPU power cap settings within the range of 160–200 W to improve the difference between percentage energy gain and performance loss by over 15.0%, EDP (Abbreviations and terms used are described in main text.) by over 17.3%, EDS with k = 1.5 by over 2.2%, EDS with k = 2.0 by over 7.5% and pure energy by over 25%, compared to the default power cap setting of 260 W per GPU. These findings demonstrate the potential of today’s CPU+GPU systems for configuration improvement in the context of performance-energy consumption metrics.
GPPRMon: GPU Runtime Memory Performance and Power Monitoring Tool
Authors: Topçu Burak , Öz Işıl 
Published: April 2024

AbstractGraphics Processing Units (GPUs) perform highly efficient parallel execution for high-performance computation and embedded system domains. While performance concerns drive the main optimization efforts, power issues become important for energy-efficient GPU executions. While performance profilers and architectural simulators offer statistics about the target execution, they either present only performance metrics in a coarse kernel function level or lack visualization support that enables performance bottleneck analysis or performance-power consumption comparison. Evaluating both performance and power consumption dynamically at runtime and across GPU memory components enables a comprehensive tradeoff analysis for GPU architects and software developers. This paper presents a novel memory performance and power monitoring tool for GPU programs, GPPRMon, which performs a systematic metric collection and offers useful visualization views to track power and performance optimizations. Our simulation-based framework dynamically collects microarchitectural metrics by monitoring individual instructions and reports achieved performance and power consumption information at runtime. Our visualization interface presents spatial and temporal views of the execution. While the first demonstrates the performance and power metrics across GPU memory components, the latter shows the corresponding information at the instruction granularity in a timeline. Our case study reveals the potential usages of our tool in bottleneck identification and power consumption for a memory-intensive graph workload.
Towards Resource-Efficient DNN Deployment for Traffic Object Recognition: From Edge to Fog
Authors: Stojanovic Dragan , Sentic Stefan , Stojanovic Natalija 
Published: April 2024

AbstractThe paper focuses on the challenges associated with deploying deep neural networks (DNNs) for the recognition of traffic objects using the camera of Android smartphones. The main objective of this research is to achieve resource-awareness, enabling efficient utilization of computational resources while maintaining high recognition accuracy. To achieve this, a methodology is proposed that leverages the Edge-to-Fog paradigm to distribute the inference workload across multiple tiers of the distributed system architecture. The evaluation was conducted using a dataset comprising real-world traffic scenarios and diverse traffic objects. The main findings of this research highlight the feasibility of deploying DNNs for traffic object recognition on resource-constrained Android smartphones. The proposed Edge-to-Fog methodology demonstrated improvements in terms of both recognition accuracy and resource utilization, and viability of both edge-only and edge-fog based approaches. Moreover, the experimental results showcased the adaptability of the system to dynamic traffic scenarios, thus ensuring real-time recognition performance even in challenging environments.
The Implementation of Battery Charging Strategy for IoT Nodes
Authors: Rajković Petar , Aleksić Dejan , Janković Dragan 
Published: April 2024

AbstractThe Internet of Things (IoT) nodes dedicated to off-grid usage must fully rely on their battery power for continuous operation. In that sense battery charging process design is one of the focal points for the complete system design. Nowadays, battery charging, for such devices, usually relies on solar power which is not, unfortunately, the source of constant energy. Both environmental and constructive elements could easily make a negative impact on the charging process and reduce the amount of collected energy. Furthermore, if the IoT nodes are in hazardous areas, they are less accessible, and the value of effective battery management is even higher. The requirements for the battery charging process implementation are considered as opposite – on one hand, the requirement is to run charging with the lowest possible frequency and not up to 100%, and on the other hand, the battery should always have enough energy to maintain regular operation. In this research, we present the structure of the custom-developed IoT node based on the ECS32 system-on-a-chip dedicated to operating in remote industrial areas, and with an accent of its battery charging routine. The current routine is based on a standard thresholds approach and improved by including consumption estimates for the predefined periods. This paper presents the first results and should pave the ground for further upgrades. In addition, the comparison with state-of-the-art charging approaches is presented, as the guidelines for future work.
subMFL: Compatible subModel Generation for Federated Learning in Device Heterogeneous Environment
Authors: Oz Zeyneddin , Soygul Oz Ceylan , Malekjafarian Abdollah , Afraz Nima , Golpayegani Fatemeh 
Published: April 2024

AbstractFederated Learning (FL) is commonly used in systems with distributed and heterogeneous devices with access to varying amounts of data and diverse computing and storage capacities. FL training process enables such devices to update the weights of a shared model locally using their local data and then a trusted central server combines all of those models to generate a global model. In this way, a global model is generated while the data remains local to devices to preserve privacy. However, training large models such as Deep Neural Networks (DNNs) on resource-constrained devices can take a prohibitively long time and consume a large amount of energy. In the current process, the low-capacity devices are excluded from the training process, although they might have access to unseen data. To overcome this challenge, we propose a model compression approach that enables heterogeneous devices with varying computing capacities to participate in the FL process. In our approach, the server shares a dense model with all devices to train it: Afterwards, the trained model is gradually compressed to obtain submodels with varying levels of sparsity to be used as suitable initial global models for resource-constrained devices that were not capable of train the first dense model. This results in an increased participation rate of resource-constrained devices while the transferred weights from the previous round of training are preserved. Our validation experiments show that despite reaching about 50% global sparsity, generated submodels maintain their accuracy while can be shared to increase participation by around 50%.
Towards a Simulation as a Service Platform for the Cloud-to-Things Continuum
Authors: Valdez Wilson , Baniata Hamza , Markus Andras , Kertesz Attila 
Published: April 2024

AbstractIn the past years, we have seen an unprecedented pace of technological development in smart applications. Smart Systems incorporate securely connected sensors, actuators, and data processing resources to provide digital services. They provide a wide range of smart applications using emerging technologies that address governmental or industrial processes or citizen life in smart cities, and many of them have been affected by the COVID-19 pandemic which involved a general lack of trust. Integrating Blockchain-based data management into smart systems can enhance the performance, trust, and privacy of their applications, which are getting more and more crucial. In this paper, we propose a vision for a unified Simulation as a Service platform, which will be able to model and investigate Blockchain-based smart systems exploiting IoT, Fog, and Cloud Computing infrastructures.
Cormas: The Software for Participatory Modelling and Its Application for Managing Natural Resources in Senegal
Authors: Zaitsev Oleksandr , Vendel François , Delay Etienne 
Published: April 2024

AbstractCormas is an agent-based simulation platform developed in the late 90s by the Green research at CIRAD unit to support the management of natural resources and understand the interactions between natural and social dynamics. This platform is well-suited for a participatory simulation approach that empowers local stakeholders by including them in all modelling and knowledge-sharing steps. In this short paper, we present the Cormas platform and discuss its unique features and their importance for the participatory simulation approach. We then present the early results of our ongoing study on managing pastoral resources in the Sahel region, identify the problems faced by local stakeholders, and discuss the potential use of Cormas at the next stage of our study to collectively model and understand the effective ways of managing the shared agro-sylvo-pastoral resources.
Grounding Higher Education Leadership Research in Non-affirmative Education Theory
Authors: Uljens Michael , Elo Janne 
Published: April 2024

AbstractThis chapter argues that higher education leadership research lacks sufficient theoretical underpinning and requires a more comprehensive theoretical framework. We propose that establishing a solid theoretical foundation involves a systematic exploration of three key perspectives: the why, how and what of leadership. First, recognising that leadership in and of educational institutions is relational and contextual, shaped by historical evolution, we advocate for a clarification of universities’ roles and responsibilities from societal, cultural, disciplinary, economic and individual perspectives—the why of higher education curriculum leadership. We argue that education theory provides valuable insights into understanding how the university, as an institutional context, and its tasks relate to these dimensions. Second, considering higher education institutions as knowledge-intensive organisations, leadership’s fundamental role is seen in facilitating the professional and personal development of both staff and students. Consequently, higher education leadership should articulate its position on pedagogical influence across various levels—the how of higher education curriculum leadership. Third, recognising that the primary focus of higher education leadership at different levels is the academic and professional learning of students, it involves providing direct and indirect support for leaders and teachers, as well as shaping the curriculum and organisation of study programmes. These aspects collectively constitute the what of higher education curriculum leadership. In light of these three perspectives, this chapter outlines the theoretical grounding for research on the pedagogical dimension of multi-level higher education leadership within the framework of non-affirmative education theory.
Levels of Pedagogical Leadership in Higher Education: An Overview
Authors: Elo Janne , Uljens Michael 
Published: April 2024

AbstractLeadership in higher education is widely recognised as existing within a network of actors situated at different organisational levels and encompassing a broad variety of tasks and assignments. Leadership interactions are partly pedagogical in character, meaning that their goal is to support, both directly and indirectly, the development of the insights, understandings, and competencies of others. This chapter draws on examples of contemporary research in higher education to provide an overview of how pedagogical leadership can emerge at different leadership levels. We apply the non-affirmative theory of education to enable a conceptual understanding of the pedagogical nature of interactions among higher education leadership at and between all levels of leadership. Drawing from contemporary research concerning higher education leadership, this chapter elucidates the pedagogical dimensions of leadership at various levels in higher education.
Higher Education Curriculum Leadership in the Anthropocene
Authors: Wolff Lili-Ann , Elo Janne , Uljens Michael 
Published: April 2024

AbstractIn a time that many researchers have started to refer to the Anthropocene, the role of higher education (HE), as predominant educational institutions, is most relevant. Humanity faces big challenges with climate change that have become too obvious to be denied, a faster biodiversity loss than ever, growing inequality and poverty problems, and a zoonotic pandemic that has revealed that humans are parts of viral ecosystems. In such a world, the idea of the university and higher education in general is crucial in preparing for the future. This chapter discusses more precisely HE curriculum leadership (HECL) in the Anthropocene. The argumentation explores the topic from a view of Bildung and non-affirmative education. Based on the literature, the study specifically explores if the non-affirmative education theory could be an option to develop HECL in the Anthropocene. The paradoxical situation with an education that promotes freedom for humans, who live on a planet that noticeably limits their activities, is all but easy. Therefore, the HECL challenge includes the promotion of responsible discussions about values and urgent activities now, but also about how to enable the students to live in an unknown future.
Understanding Higher Education Decision-Making and Educational Practice as Interrelated and Historically Framed Phenomena—A Non-affirmative Take
Authors: Välimaa Jussi , Uljens Michael , Elo Janne 
Published: April 2024

AbstractThis chapter discusses three historically rooted ideals of decision-making practices in universities (collegiality, democracy and managerialism) from the perspective of non-affirmative theory of education (NAT). Following a discussion on the historical layers of Finnish universities, we analyse how different practices of higher education decision-making are connected to ideas of what a university is and does. Utilising NAT, we reflect on higher education leadership both in terms of its internal character and its object and historical context. The chapter has three starting points. First, we note that contributions to conceptualisations of educational leadership, governance and management need to provide an idea of the object of this leadership—what is being led. Second, we argue that higher education leadership and governance theory needs to say something meaningful about the relation between society and university. Third, we discuss how decision-making is managing the gap between external expectations and conditions and institutional operational culture. We discuss the ways in which both collegiality and democracy recognise each other as free, capable of and responsible for participating in decision-making, either directly or indirectly. From the perspective of NAT, recognition without affirmation creates a space for collaborative reflection and the repositioning of the activities of individuals and organisations. However, the shift from the democratic mode of decision-making to managerialism implies a break with this tradition. Decision-making in Finnish universities in the period after the university law (2009) is characterised by a shift of power from democratically elected bodies into the hands of deans and the rector. Utilising NAT, we discuss how this change influences academics.
On Maintaining Social and Moral Agency beyond Instrumental Managerialism in a Knowledge-Based Economy—A Sociological and Educational Perspective
Authors: Normand Romuald , Uljens Michael , Elo Janne 
Published: April 2024

AbstractThis chapter examines transformations in the epistemic governance of higher education and research on education in Europe, and in how the production of scientific knowledge increasingly is constrained by utilitarian expectations and standards based on policymaking decisions. The chapter explains how new political technologies produce certain modes of representation, cognitive categories, and value judgments that support development of new forms of interaction between researchers, experts, and policymakers. By characterizing transformations of academic capitalism, the chapter examines how academics today are engaged in heterogeneous networks that legitimize new relationships and work conventions. The chapter draws on sociological and education theory in explaining these transformations’ consequences, not only on the generation of academic knowledge, but also on selves and identities within scientific communities. This epistemic governance undermines some moral components and leadership attitudes in an increasingly competitive and instrumental environment.
A generalized Selberg zeta function for flat space cosmologies
Authors: Bagchi Arjun , Keeler Cynthia , Martin Victoria , Poddar Rahul 
Published: April 2024

Abstract
Flat space cosmologies (FSCs) are time dependent solutions of three-dimensional (3D) gravity with a vanishing cosmological constant. They can be constructed from a discrete quotient of empty 3D flat spacetime and are also called shifted-boost orbifolds. Using this quotient structure, we build a new and generalized Selberg zeta function for FSCs, and show that it is directly related to the scalar 1-loop partition function. We then propose an extension of this formalism applicable to more general quotient manifolds $$ \mathcal{M} $$
M
/ℤ, based on representation theory of fields propagating on this background. Our prescription constitutes a novel and expedient method for calculating regularized 1-loop determinants, without resorting to the heat kernel. We compute quasinormal modes in the FSC using the zeroes of a Selberg zeta function, and match them to known results.
QCD corrections to the Golden decay channel of the Higgs boson
Authors: Kaur Mandeep , Mahakhud Maguni , Shivaji Ambresh , Zhao Xiaoran 
Published: April 2024

Abstract
Future colliders aim to provide highly precise experimental measurements of the properties of the Higgs boson. In order to benefit from these precision machines, theoretical errors in the Higgs sector observables have to match at least the experimental uncertainties. The theoretical uncertainties in the Higgs sector observables can be reduced by including missing higher-order terms in their perturbative calculations. In this direction, we compute the mixed QCD-electroweak corrections at $$\mathcal{O}\left({\alpha \alpha }_{s}\right)$$ to the Higgs decay into four charged leptons by considering the golden decay channel, H → e+e−μ+μ−. Due to color conservation, these corrections receive contributions only from the two-loop virtual diagrams. In the complex mass scheme, we find that the mixed QCD-electroweak corrections to the partial decay width, relative to the leading order predictions, are positive and about 0.27% for αs(MZ). Relative to the next-to-leading order electroweak corrections, the mixed QCD-electroweak corrections are found to be approximately 18% for αs(MZ). With respect to the leading order, we observe a flat effect of the mixed QCD-electroweak corrections on the invariant mass distribution of the lepton pairs with fixed QCD coupling. The ϕ distribution, due to the mixed QCD-electroweak corrections, follows a (1 − cos ϕ) dependence.
Using the effective weak mixing angle as an input parameter in SMEFT
Authors: Biekötter Anke , Pecjak Benjamin D. , Smith Tommy 
Published: April 2024

Abstract
We implement electroweak renormalisation schemes involving the effective weak mixing angle to NLO in Standard Model Effective Field Theory (SMEFT). After developing the necessary theoretical machinery, we analyse a select set of electroweak precision observables in such input schemes. An attractive feature is that large corrections from top-quark loops appearing in other schemes are absorbed into the definition of the effective weak mixing angle. On the other hand, the renormalisation condition which achieves this involves a large number of flavour-specific SMEFT couplings between the Z boson and charged leptons, motivating simple flavour assumptions such as minimal flavour violation for practical applications. The results of this paper provide a valuable new component for estimating systematic uncertainties in SMEFT fits by performing analyses in multiple input schemes.