bluuebunny/crossref_metadata_2025_split huggingface dataset:
Light‐Driven Spatiotemporal Pickering Emulsion Droplet Manipulation Enabled by Plasmonic Hybrid Microgels
Authors: Guan Xin , Cheng Guangyao , Ho Yi‐Ping , Binks Bernard P. , Ngai To 
Published: July 2023

AbstractThe past decades have witnessed the development of various stimuli‐responsive materials with tailored functionalities, enabling droplet manipulation through external force fields. Among different strategies, light exhibits excellent flexibility for contactless control of droplets, particularly in three‐dimensional space. Here, we present a facile synthesis of plasmonic hybrid microgels based on the electrostatic heterocoagulation between cationic microgels and anionic Au nanoparticles. The hybrid microgels are effective stabilizers of oil‐in‐water Pickering emulsions. In addition, the laser irradiation on Au nanoparticles creats a “cascade effect” to thermally responsive microgels, which triggers a change in microgel wettability, resulting in microgel desorption and emulsion destabilization. More importantly, the localized heating generated by a focused laser induces the generation of a vapor bubble inside oil droplets, leading to the formation of a novel air‐in‐oil‐in‐water (A/O/W) emulsion. These A/O/W droplets are able to mimic natural microswimmers in an aqueous environment by tracking the motion of a laser spot, thus achieving on‐demand droplet merging and chemical communication between isolated droplets. Such proposed systems are expected to extend the applications of microgel‐stabilized Pickering emulsions for substance transport, programmed release and controlled catalytic reactions.
Neighboring Platinum Atomic Sites Activate Platinum–Cobalt Nanoclusters as High‐Performance ORR/OER/HER Electrocatalysts
Authors: Chen Wenxia , Zhu Xingwang , Wei Wei , Chen Haoran , Dong Tianhao , Wang Rui , Liu Meng , (Ken) Ostrikov Kostya , Peng Peng , Zang Shuang‐Quan 
Published: July 2023

AbstractThe rational design of efficient and multifunctional electrocatalysts for energy conversion devices is one of the major challenges for clean and renewable energy transition. Herein, the local electronic structure of cobalt–platinum nanoclusters is regulated by adjacent platinum atomic site encapsulated in N‐doped hollow carbon nanotubes (PtSA–PtCo NCs/N–CNTs) by pyrolysis of melamine‐orientation‐induced zeolite imidazole metal–organic frameworks (ZIF‐67) with thimbleful platinum doping. The introduction of melamine can reactivate adjacent carbon atoms and initiate the oriented growth of nitrogen‐doped carbon nanotubes. The systematic analysis suggests the significant role of thimbleful neighboring low‐coordinated Pt─N2 in altering the localized electronic structure of PtCo nanoclusters. The optimized PtSA–PtCo NCs/N–CNTs‐900 exhibit excellent hydrogen evolution reaction (HER)/oxygen evolution reaction (OER)/oxygen reduction reaction (ORR)/ catalytic performance reaching the current density of 10 mA cm−2 in 1 m KOH under the low 47 (HER) and 252 mV (OER) overpotentials, and a high half‐wave potential of 0.86 and 0.89 V (ORR) in 0.1 m KOH and 0.1 m HClO4, respectively. Remarkably, the PtSA–PtCo NC/N–CNT‐900 also presents outstanding catalytic performances toward water splitting and rechargeable Zn–air batteries. The theoretical calculations reveal that optimal regulation of the electronic structure of PtCo nanoclusters by thimbleful neighboring Pt atomic reduces the reaction energy barrier in electrochemical process, facilitating the ORR/OER/HER performance.
Recent Progress of Transition Metal Compounds as Electrocatalysts for Electrocatalytic Water Splitting
Authors: Yu Yongren , Wang Tiantian , Zhang Yue , You Junhua , Hu Fang , Zhang Hangzhou 
Published: July 2023

AbstractHydrogen has enormous commercial potential as a secondary energy source because of its high calorific value, clean combustion byproducts, and multiple production methods. Electrocatalytic water splitting is a viable alternative to the conventional methane steam reforming technique, as it operates under mild conditions, produces high‐quality hydrogen, and has a sustainable production process that requires less energy. Electrocatalysts composed of precious metals like Pt, Au, Ru, and Ag are commonly used in the investigation of hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Nevertheless, their limited availability and expensive cost restrict practical use. In contrast, electrocatalysts that do not contain precious metals are readily available, cost‐effective, environmentally friendly, and possess electrocatalytic performance equal to that of noble metals. However, considerable research effort must be devoted to create cost‐effective and high‐performing catalysts. This article provides a comprehensive examination of the reaction mechanism involved in electrocatalytic water splitting in both acidic and basic environments. Additionally, recent breakthroughs in catalysts for both the hydrogen evolution and oxygen evolution reactions are also discussed. The structure‐activity relationship of the catalyst was deep‐going discussed, together with the prospects of current obstacles and potential for electrocatalytic water splitting, aiming at provide valuable perspectives for the advancement of economical and efficient electrocatalysts on an industrial scale.
Energy Application of Graphene Based Membrane: Hydrogen Separation
Authors: Sohail Ahmad Muhammad , Inomata Yusuke , Kida Tetsuya 
Published: July 2023

AbstractHydrogen gas (H2) is a viable energy carrier that has the potential to replace the traditional fossil fuels and contribute to achieving zero net emissions, making it an attractive option for a hydrogen‐based society. However, current H2 purification technologies are often limited by high energy consumption, and as a result, there is a growing demand for alternative techniques that offer higher H2 purity and energy efficiency. Membrane separation has emerged as a promising approach for obtaining high‐purity H2 gas with low energy consumption. Nevertheless, despite years of development, commercial polymeric membranes have limited performance, prompting researchers to explore alternative materials. In this context, carbon‐based membranes, specifically graphene‐based nanomaterials, have gained significant attention as potential membrane materials due to their unique properties. In this review, we provide a comprehensive overview of carbon‐based membranes for H2 gas separation, fabrication of the membrane, and its characterization, including their advantages and limitations. We also explore the current technological challenges and suggest insights into future research directions, highlighting potential ways to improve graphene‐based membranes performance for H2 separations.
Zeolite addition in microalgae Chlorella sp. for treatment of bacteria contaminated vinasse
Authors: Budianto Gregorius Prima Indra , Wibowo Yari Mukti , Hadiyanto Hadiyanto , Widayat Widayat 
Published: July 2023

AbstractChlorella pyrenoidosa has been grown in artificial vinasse digestate. The method being used is intended to gather data on kinetic parameters that govern the performance of C. pyrenoidosa cultivated in a medium containing bacterial components. This condition was developed by introducing 1000 μL of Bacillus cereus to the medium (5 ppm of vinasse: 15 ppm of NaHCO3 = 3:2), which was subsequently mixed with C. pyrenoidosa culture at a 1:1 v/v ratio. The cultivation was carried out in batch mode for 15 days. The photosynthesis process of C. pyrenoidosa was conducted in 14 h and supported by 2 mL L−1 Guillard, which was given every 5 days. The study additionally investigated how different amounts of Zeolite (30, 60, and 90 gL−1) affected the kinetic parameters of microalgae grown in artificial vinasse digestate. This study demonstrated that the utilization of artificial vinasse digestate as a growing medium for C. pyrenoidosa resulted in growth limitation symptoms of microalgae, as a consequence of unfavorable interaction between C. pyrenoidosa and bacteria that already existed in the medium. This is indicated by low values of growth kinetics parameters, including specific growth rate (0.0259 d−1) and biomass productivity (0.51774 gL−1d−1) as compared to the reactor without bacteria in the medium. Therefore, adding a certain quantity of Zeolite to the reactor is a promising alternative for mitigating the negative effects of bacterial presence. With the addition of 90 g L−1 of Zeolite to the reactor, the specific growth rate of C. pyrenoidosa increases by 71%, indicating an appropriate growth. In addition, the total yield of PHB formation and the Melanoidin degradation efficacy of this reactor improved by 70% and 98%, respectively.
Mesalazine granules promote disease clearance in patients with mild‐to‐moderate ulcerative colitis
Authors: Kruis Wolfgang , Meszaros Silke , Wehrum Sarah , Mueller Ralph , Greinwald Roland , Nacak Tanju 
Published: July 2023

AbstractBackgroundOver the past decade, treatment targets for ulcerative colitis (UC) have become more stringent, incorporating multiple parameters. Recently, the concept of ‘disease clearance’—defined as combined clinical, endoscopic, and histological remission—has been proposed as an ultimate endpoint in treating UC.ObjectiveTo determine the rates of disease clearance in patients with mild‐to‐moderate UC treated with different doses of mesalazine granules as induction therapy.MethodsIn a post hoc analysis, data were pooled from four randomised, active‐controlled, phase 3 clinical trials in patients with mild‐to‐moderate UC receiving 8‐week induction therapy with mesalazine granules at daily doses of 1.5, 3.0 or 4.5 g. Rates of clinical, endoscopic, and histological remission were determined using stringent criteria and used to calculate rates of the composite endpoints of clinical plus endoscopic remission, endoscopic plus histological remission, and disease clearance (clinical plus endoscopic plus histological remission).ResultsA total of 860 patients were included in the analysis. Among the total population, 20.0% achieved disease clearance with mesalazine granules: 13.1% in patients receiving 1.5 g mesalazine granules/day, 21.8% in those receiving 3.0 g/day and 18.9% in those receiving 4.5 g/day. Among patients with moderate UC, 16.8% achieved disease clearance: 7.1% with 1.5 g/day, 18.8% with 3.0 g/day and 16.2% with 4.5 g/day.ConclusionDisease clearance, proposed to be predictive of improved long‐term outcomes, can be achieved in a clinically meaningful proportion of mild‐to‐moderate UC patients treated with mesalazine granules. A daily dose of 3.0 g appears optimal to reach this target.
Multiple infections of zoonotic pathogens in wild Brandt's voles (Lasiopodomys brandtii)
Authors: Guo Yongman , Li Zhengrun , Dong Shike , Si Xiaoyan , Ta Na , Liang Hanwei , Xu Lei 
Published: July 2023

AbstractBackgroundThe frequent interactions of rodents with humans make them a common source of zoonotic infections. Brandt's vole is the dominant rodent species of the typical steppe in Inner Mongolia, and it is also an important pest in grassland.Objectives:To obtain an initial unbiased measure of the microbial diversity and abundance in the blood and intestinal tracts and to detect the pathogens carried by wild Brandt's voles in Hulun Buir, Inner Mongolia.MethodsTwenty wild adult Brandt's voles were trapped using live cages, and 12 intestinal samples were collected for metagenomic analysis and 8 blood samples were collected for meta‐transcriptomic analysis. We compared the sequencing data with pathogenic microbiota databases to analyse the phylogenetic characteristics of zoonotic pathogens carried by wild voles.ResultsA total of 122 phyla, 79 classes, 168 orders, 382 families and 1693 genera of bacteria and a total of 32 families of DNA and RNA viruses in Brandt's voles were characterized. We found that each sample carried more than 10 pathogens, whereas some pathogens that were low in abundance were still at risk of transmission to humans.ConclusionThis study improves our understanding of the viral and bacterial diversity in wild Brandt's voles and highlights the multiple viral and bacterial pathogens carried by this rodent. These findings may serve as a basis for developing strategies targeting rodent population control in Hulun Buir and provide a better approach to the surveillance of pathogenic microorganisms in wildlife.
Light Fixtures Position Detection Using a Camera
Authors: Leischner Vojtěch 
Published: July 2023

AbstractInterdisciplinary research combines computer vision with stage light design to automatically detect light fixtures’ positions to create light animations. Multiple programmable light fixtures are often used in theaters, the event industry, and interactive installations. When creating complex animations such as a wave traveling from one side to the other through multiple light fixtures array, all lights’ positions must be known beforehand. Traditionally the position of the light is marked in the technical plan. However, technicians make mistakes during the installation and sometimes install the light in a different position. In such a case, time-consuming troubleshooting is needed to determine which light is misplaced and either correct the position in the software or manually move the light to the correct position. Our system saves time during installation and produces a light id and position pairs that users can use in various lighting control software. As a result, users can improvise and change the light positions more intuitively without needing a technical plan. Our system saves installation costs and enables rapid prototyping of light shows to create previously impossible organic designs. We verified the system in a controlled experiment and measured the influence of camera resolution on accuracy.
Assessing GAN-Based Generative Modeling on Skin Lesions Images
Authors: Carrasco Limeros Sandra , Majchrowska Sylwia , Zoubi Mohamad Khir , Rosén Anna , Suvilehto Juulia , Sjöblom Lisa , Kjellberg Magnus 
Published: July 2023

AbstractWe explored unconditional and conditional Generative Adversarial Networks (GANs) in centralized and decentralized settings. The centralized setting imitates studies on large but highly unbalanced skin lesion dataset, while the decentralized one simulates a more realistic hospital scenario with three institutions. We evaluated models’ performance in terms of fidelity, diversity, speed of training, and predictive ability of classifiers trained on the generated synthetic data. In addition, we provided explainability focused on both global and local features. Calculated distance between real images and their projections in the latent space proved the authenticity of generated samples, which is one of the main concerns in this type of applications. The code for studies is publicly available (https://github.com/aidotse/stylegan2-ada-pytorch).
Ukrainian Version of the Copresence Scale
Authors: Naydonova Lyubov , Pochwatko Grzegorz , Naydonov Mykhaylo , Świdrak Justyna 
Published: July 2023

AbstractMillions of Ukrainians are fleeing the war to the EU countries; in particular, Poland has accepted more than three million refugees, among whom are mostly women and children. Some of them continue to work remotely in Ukraine and communicate with friends and relatives at a distance through technology-mediated ways. The aim of our study was to observe the role of perceived copresence during social contacts, both of professional and private character, and validate the Ukrainian version of the copresence scale among Ukrainian migrants. We collected 221 responses in an online and face-to-face study from Ukraine migrants. Analyses revealed that the Ukrainian Perceived Copresence scale has one factor and appropriate internal consistency. Perspectives of future research are proposed.
A Method for Co-designing Immersive VR Environments with Users Excluded from the Main Technological Discourse
Authors: Kopeć Wiesław , Jaskulska Anna , Karpowicz Barbara , Pochwatko Grzegorz , Kornacka Monika , Skorupska Kinga 
Published: July 2023

AbstractWith the advent of new interfaces and modes of interaction related to virtual, augmented and mixed reality (VR, AR, MR) or voice user interfaces (VUI) a need to explore new approaches to foster rapid software prototyping and development emerges. Drawing from our experiences in human, cooperative, and collaborative aspects of software engineering, based on IT-empowerment and participatory design with older and younger adults, we propose and examine some methods, practices and tools for co-designing software for the immersive extended reality continuum (XR), including VR, AR or VUI. In a series of empirical and field studies we examined various experimental setups for stakeholders’ participation within and across different steps and phases of the software development process for immersive extended reality environments (IERE). In this article we provide an overview of selected methods, practices and tools, that we found best support communication, collaboration, and cooperation among stakeholders, especially the members of vulnerable groups who are often excluded from the main technological discourse and need more empowerment.
Improving the Usability of Requests for Consent to Use Cookies
Authors: Lapin Kristina , Volungevičiūtė Laima 
Published: July 2023

AbstractAn HTTP cookie (hereinafter cookie) is a piece of information that maintains a state in a stateless HTTP protocol. Recently established privacy and security regulation imposes an obligation on the service provider to obtain the user’s consent to use cookies. This paper is aimed at studying usability guidelines of requests for consent to use cookies (hereinafter consent requests). The consent requests have usability issues that make it difficult for the users to choose the right privacy and security options. A study of privacy and security regulation is aimed at extracting design requirements. Manipulative designs also known as dark patterns are explored and applied to assess consent requests of two of the most popular Lithuanian news portals. An evaluation revealed the presence of dark patterns in consent requests as well as violation of privacy and security requirements. As a result, usability guidelines on the design of cookie consent requests are developed.
NARX Recurrent Neural Network Model of the Graphene-Based Electronic Skin Sensors with Hysteretic Behaviour
Authors: Możaryn Jakub 
Published: July 2023

AbstractThe electronic skin described in the article comprises screen-printed graphene-based sensors, intended to be used for robotic applications. The precise mathematical model allowing the touch pressure estimation is required during its calibration. The article describes the recurrent neural network model for graphene-based electronic skin calibration, in which parameters are not homogeneous, and the touch force characteristics have visible hysteretic behaviour. The presented method provides a simple alternative to the models known in the literature.
Collaborative Robotics. Safety and Ethical Considerations
Authors: Różańska-Walczuk Monika 
Published: July 2023

AbstractEvery year, collaborative robots get closer to humans and cooperation with them takes place not only in industrial spaces, where specialized employees work with them, but also people who do not have knowledge in the field of engineering and robotics. Therefore, great attention is paid to safety in the cooperation of robots and humans. In addition, the aspect of ethics and their ethical behavior towards a human co-worker, companion or petitioner is more and more often taken into account. Knowledge of potential safety hazards is important to secure safety early in robots’ design and development process. Therefore security is one of main issues raised in the article. The most important safety standards from the point of view of collaborative robotics are presented. In the article described example of cobots acting increasingly role as members of our society. Access to them is becoming more and more common - they are household members, waiters or airport staff. Presented in the paper issue of ethics in reference to robots and AI are becoming increasingly significant impact on human. It deals with topics of physical and ethical safety in cooperation between humans and robots. Reference has been made to the safety standards. Due to proximity of technology in humans lives, access to them, and even dependence on them, that issue was particularly emphasized by the author. The paper is source of references to considerations of human safety in robotized environments and ethics in robotics applications.
AI4U: Modular Framework for AI Application Design
Authors: Wołoszyn Kamil , Turchan K. , Rąpała M. , Piotrowski K. 
Published: July 2023

AbstractThis paper presents the concepts of a universal, modular framework that shall enable rapid development of AI applications. The goal of the conceptual tool is the versatility in terms of changing the environment, as well as integration of different types of sensors to perform a specific task. The framework follows the Sens4U approach that will facilitate the entire process of building the AI applications and simplify the testing process.
AI in Prostate MRI Analysis: A Short, Subjective Review of Potential, Status, Urgent Challenges, and Future Directions
Authors: Jóźwiak Rafał , Mykhalevych Ihor , Gorbenko Iryna , Sobecki Piotr , Mitura Jakub , Lorenc Tomasz , Tupikowski Krzysztof 
Published: July 2023

AbstractArtificial intelligence (AI) in prostate MRI analysis shows great promise and impressive performance. A large number of studies present the usefulness of AI models in tasks such as prostate segmentation, lesion detection, and the classification and stratification of a cancer’s aggressiveness. This article presents a subjective critical review of AI in prostate MRI analysis. It discusses both the technology’s current state and its most recent advances, as well as its challenges. The article then presents opportunities in the context of ongoing research, which possesses the potential to reduce bias and to be applied in clinical settings.
Performance of Deep CNN and Radiologists in Prostate Cancer Classification: A Comparative Pilot Study
Authors: Sobecki Piotr , Jóźwiak Rafał , Mykhalevych Ihor 
Published: July 2023

AbstractIn recent years multiple deep-learning solutions have emerged that aim to assist radiologists in prostate cancer (PCa) diagnosis. Most of the studies however do not compare the diagnostic accuracy of the developed models to that of radiology specialists but simply report the model performance on the reference datasets. This makes it hard to infer the potential benefits and applicability of proposed methods in diagnostic workflows. In this paper, we investigate the effects of using pre-trained models in the differentiation of clinically significant PCa (csPCa) on mpMRI and report the results of conducted multi-reader multi-case pilot study involving human experts. The study aims to compare the performance of deep learning models with six radiologists varying in diagnostic experience. A subset of the ProstateX Challenge dataset counting 32 prostate lesions was used to evaluate the diagnostic accuracy of models and human raters using ROC analysis. Deep neural networks were found to achieve comparable performance to experienced readers in the diagnosis of csPCa. Results confirm the potential of deep neural networks in enhancing the cognitive abilities of radiologists in PCa assessment.