bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Evaluation and Durability Analysis of NiFeCoOx Catalysts for Alkaline Water Electrolysis in Anion Exchange Membrane Electrolyzers
Authors: Ahmed Khaja Wahab , Fowler Michael
Published: May 2024

This study examines the catalytic activity of NiFeCoOx catalysts for anion exchange membrane (AEM) water electrolysis. The catalysts were synthesized with a Ni to Co ratio of 2:1 and Fe content ranges from 2.5 to 12.5 wt%. The catalysts were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. The catalytic activity of the NiFeCoOx catalysts was evaluated through linear sweep voltammetry (LSV) and chronoamperometry (CA) experiments for the oxygen evolution reaction (OER). The catalyst with 5% Fe content exhibited the highest catalytic activity, achieving an overpotential of 228 mV at a current density of 10 mA cm−2. Long-term catalyst testing for the OER at 50 mA cm−2 showed stable electrolysis operation for 100 h. The catalyst was further analyzed in an AEM water electrolyzer in a single-cell test, and the NiFeCoOx catalyst with 5% Fe at the anode demonstrated the highest current densities of 1516 mA cm−2 and 1620 mA cm−2 at 55 °C and 70 °C at 2.1 V. The maximum current density of 1880 mA cm−2 was achieved at 2.2 V and 70 °C. The Nyquist plot analysis of electrolysis at 55 °C showed that the NiFeCoOx catalyst with 5% Fe had lower activation resistance compared with the other Fe loadings, indicating enhanced performance. The durability test was performed for 8 h, showing stable AEM water electrolysis with minimum degradation. An overall cell efficiency of 70.5% was achieved for the operation carried out at a higher current density of 0.8 A cm−2.
A Naked-Eye Colorimetric Ratio Method for the Selective and Sensitive Detection of L-Cys Based on a Silver Nanoflakes–Chromium (III) Ion System
Authors: Zhang Xi , Zhang Yunyi , Gu Yuwei , Zhou Junyu , Li Ming , Qi Jian
Published: May 2024

As a necessary sulfhydryl amino acid, L-cysteine (L-Cys) maintains many physiological functions in the biological system. However, abnormal L-Cys levels can cause a variety of diseases. In our work, a highly sensitive and selective assay has been developed for sensing L-Cys using the morphological transformation of silver-based materials induced by Cr3+. In this sensing system, Cr3+ could etch the silver nanoflakes into silver nanoparticles, accompanied by a change in absorbance, which decreases at 395 nm, creates a new peak at 538 nm, and keeps increasing the absorbance with the addition of Cr3+ concentration. Meanwhile, under the naked eye, the solution color changes from bright yellow to dark purple. Because of the strong affinity between L-Cys and Cr3+, L-Cys could inhibit the induction of Cr3+ on silver-based materials, thereby preventing changes in the configuration, absorption spectrum, and color of silver-based materials. Taking advantage of this point, we can quantitatively detect the concentration of L-Cys. A linear relationship between the absorbance ratio (A538 nm/A395 nm) and L-Cys concentration was found in the range of 0.1–0.9 μM, and the detection limit was 41.2 nM. The strategy was applied to measure L-Cys spiked in beer and urine samples, with recovery from 93.80 to 104.03% and 93.33% to 107.14% and RSD from 0.89 to 2.40% and 1.80% to 6.78%, respectively. This detection strategy demonstrates excellent selectivity and sensitivity, which makes it a practical and effective method for the detection of L-Cys in real samples.
Ultrasound Diagnosis and Near-Infrared Spectroscopy in the Study of Encephalopathy in Neonates Born under Asphyxia: Narrative Review
Authors: Lavrentev Simeon N. , Petrova Anastasia S. , Serova Olga F. , Vishnyakova Polina , Kondratev Maxim V. , Gryzunova Anastasia S. , Zakharova Nina I. , Zubkov Victor V. , Silachev Denis N.
Published: May 2024

Brain injury resulting from adverse events during pregnancy and delivery is the leading cause of neonatal morbidity and disability. Surviving neonates often suffer long-term motor, sensory, and cognitive impairments. Birth asphyxia is among the most common causes of neonatal encephalopathy. The integration of ultrasound, including Doppler ultrasound, and near-infrared spectroscopy (NIRS) offers a promising approach to understanding the pathology and diagnosis of encephalopathy in this special patient population. Ultrasound diagnosis can be very helpful for the assessment of structural abnormalities associated with neonatal encephalopathy such as alterations in brain structures (intraventricular hemorrhage, infarcts, hydrocephalus, white matter injury) and evaluation of morphologic changes. Doppler sonography is the most valuable method as it provides information about blood flow patterns and outcome prediction. NIRS provides valuable insight into the functional aspects of brain activity by measuring tissue oxygenation and blood flow. The combination of ultrasonography and NIRS may produce complementary information on structural and functional aspects of the brain. This review summarizes the current state of research, discusses advantages and limitations, and explores future directions to improve applicability and efficacy.
Predictive Value of Inflammatory Markers NLR, PLR, APRI, SII, and Liver Function Tests in Systemic Inflammatory Response Syndrome Detection in Full-Term Newborns
Authors: Pantea Manuela , Iacob Daniela , Dima Mirabela , Prodan Mihaela , Belei Oana , Negrean Rodica Anamaria , Ilie Adrian Cosmin
Published: May 2024

Systemic Inflammatory Response Syndrome (SIRS) is associated with significant morbidity and mortality in full-term newborns. This study aimed to evaluate the predictive value of the Neutrophil-to-Lymphocyte Ratio (NLR), Derived Neutrophil-to-Lymphocyte Ratio (dNLR), Platelet-to-Lymphocyte Ratio (PLR), Neutrophil, Lymphocyte, and Platelet Ratio (NLPR), AST-to-Platelet Ratio Index (APRI), and Systemic Immune–Inflammation Index (SII) in identifying the risk for SIRS development in full-term newborns. Conducted between January 2023 and January 2024, this observational cohort study compared full-term newborns diagnosed with SIRS with newborns without SIRS, measuring the inflammatory markers within the first day of life and three days post-birth. The study included 229 newborns, 81 with SIRS and 148 controls without SIRS. Statistically significant differences were observed in NLR (3.81 vs. 2.20, p < 0.0001), PLR (68.12 vs. 52.30, p < 0.0001), and liver enzymes (AST 40.96 U/L vs. 31.58 U/L, ALT 34.66 U/L vs. 22.46 U/L, both p < 0.0001) between the groups. The NLPR demonstrated substantial diagnostic value, with a sensitivity of 78.36% and specificity of 83.52% at 72 h (p < 0.0001). Regression analysis highlighted that the NLPR and SII were strongly predictive of SIRS, with the NLPR showing over three-times higher SIRS risk (HR 3.29, p < 0.0001) and SII indicating nearly 3.5 times the risk (HR 3.47, p < 0.0001). The NLPR, APRI, and SII showed similar prediction values to CRP levels measured on the first and third days of life (HR 3.16). Inflammatory markers like NLR, PLR, and systemic indices such as NLPR and SII, alongside liver function tests, are significant predictors of SIRS in full-term newborns. These findings support the integration of these markers into routine neonatal care, allowing for early identification and potentially improved management of newborns at risk for SIRS, thereby enhancing clinical outcomes.
Pulsed Electro Decoration of Carbon Nanotubes with FexZn1−xS
Authors: Bjelajac Andjelika , Florea Ileana , Zamfir Mihai , Tusseau-Nenez Sandrine , Cojocaru Costel Sorin
Published: May 2024

A wide ranging scientific interest in developing new and simple preparation methods for highly catalytic bimetallic sulfides provided our motivation to explore the possibility of using the pulsed electrodeposition technique for the decoration of a carbon nanotubes forest. The carbon nanotubes were obtained using the hot-filament chemical vapor deposition technique. A non-thermal plasma treatment enabled the controlled creation of defects on the carbon nanotubes’ surface. These defects served as anchoring sites for the subsequent deposition of Fe and Zn nanoparticles using the pulsed electrodeposition technique. Our findings showed that only in the case of Fe deposition prior to Zn provided the formation of FeZn bimetallic-based nanoparticles, with Zn present mainly on the outer surface of the Fe core. To induce sulfurization, a thermal treatment in sulfur vapor was conducted at 500 °C, and the obtained heterostructure consisted of Fe0.3Zn0.7S as the main phase, with the minor presence of ZnS and S residues, which was deduced from the XRD results. This study provides thorough imaging of the process, presenting for each preparation step SEM/HR-TEM findings, coupled with EDS chemical analyses. The samples were tested for photocatalytic degradation of methyl blue dye to demonstrate the photoactive behavior of the heterostructure.
Indoor Scene Classification through Dual-Stream Deep Learning: A Framework for Improved Scene Understanding in Robotics
Authors: Khan Sultan Daud , Othman Kamal M.
Published: May 2024

Indoor scene classification plays a pivotal role in enabling social robots to seamlessly adapt to their environments, facilitating effective navigation and interaction within diverse indoor scenes. By accurately characterizing indoor scenes, robots can autonomously tailor their behaviors, making informed decisions to accomplish specific tasks. Traditional methods relying on manually crafted features encounter difficulties when characterizing complex indoor scenes. On the other hand, deep learning models address the shortcomings of traditional methods by autonomously learning hierarchical features from raw images. Despite the success of deep learning models, existing models still struggle to effectively characterize complex indoor scenes. This is because there is high degree of intra-class variability and inter-class similarity within indoor environments. To address this problem, we propose a dual-stream framework that harnesses both global contextual information and local features for enhanced recognition. The global stream captures high-level features and relationships across the scene. The local stream employs a fully convolutional network to extract fine-grained local information. The proposed dual-stream architecture effectively distinguishes scenes that share similar global contexts but contain different localized objects. We evaluate the performance of the proposed framework on a publicly available benchmark indoor scene dataset. From the experimental results, we demonstrate the effectiveness of the proposed framework.
A Rather Unusual ”Pearl”: Biological Observations of the Hidden Pearlfish Carapus acus (Brünnich, 1768) and Its First Report from Apulian Waters (Salento Peninsula, Southern Italy)
Authors: Martines Alessandra , Solca Michele , Trainito Egidio , Piraino Stefano , Furfaro Giulia
Published: May 2024

The Salento peninsula in southern Italy (Mediterranean Sea) is a strip of land between the Adriatic and the Ionian Seas, both characterized by local regimes of currents, different geological and physical backgrounds, and quite diversified fauna. In this area, specimens of the sea cucumber Holothuria tubulosa (Brünnich, 1768) (Echinodermata) were collected at four stations in the spring and autumn of 2020 to investigate a possible symbiotic association with the inquiline fish Carapus acus (Brünnich, 1768). Among the collected holothurians, five pearlfish specimens were found in the body cavity of four H. tubulosa collected at 10 m of depth, in autumn, at “Grotta Verde” in Marina di Andrano, Lecce (Ionian Sea). More than half of the sea cucumbers from the latter station hosted the symbiont, suggesting the presence of a shallow population of C. acus inhabiting this coastal area. Furthermore, morphometric analysis carried out on the collected fish helped to shed light on the population dynamics characterizing this neglected species. This is the first report of C. acus from Apulian waters, allowing us to unite previously disjoined areas and providing essential baseline knowledge for planning future in-depth analysis of this difficult-to-study fish in a geographical area that is strategic in terms of the conservation of Mediterranean biodiversity. Furthermore, the range of preferred host species is extended, as C. acus was previously known to prefer other sea cucumber species such as Parastichopus regalis (Cuvier, 1817) instead of H. tubulosa. Finally, the finding of C. acus in a single station and in only one season is not trivial and delivers baseline useful information for future conservation purposes.
Designing Home Automation Routines Using an LLM-Based Chatbot
Authors: Giudici Mathyas , Padalino Luca , Paolino Giovanni , Paratici Ilaria , Pascu Alexandru Ionut , Garzotto Franca
Published: May 2024

Without any more delay, individuals are urged to adopt more sustainable behaviors to fight climate change. New digital systems mixed with engaging and gamification mechanisms could play an important role in achieving such an objective. In particular, Conversational Agents, like Smart Home Assistants, are a promising tool that encourage sustainable behaviors within household settings. In recent years, large language models (LLMs) have shown great potential in enhancing the capabilities of such assistants, making them more effective in interacting with users. We present the design and implementation of GreenIFTTT, an application empowered by GPT4 to create and control home automation routines. The agent helps users understand which energy consumption optimization routines could be created and applied to make their home appliances more environmentally sustainable. We performed an exploratory study (Italy, December 2023) with N = 13 participants to test our application’s usability and UX. The results suggest that GreenIFTTT is a usable, engaging, easy, and supportive tool, providing insight into new perspectives and usage of LLMs to create more environmentally sustainable home automation.
The Effect of Fabry Disease Therapy on Bone Mineral Density
Authors: Aitken Tess , Tiong Mark K. , Talbot Andrew S. , Ruderman Irene , Nicholls Kathleen M.
Published: May 2024

Fabry disease (FD) is an X-linked lysosomal storage disorder, characterised by the cellular accumulation of globotriaosylceramide due to impaired alpha-galactosidase A enzyme activity. FD may manifest with multisystem pathology, including reduced bone mineral density (BMD). Registry data suggest that the introduction of Fabry-specific therapies (enzyme replacement therapy or chaperone therapy) has led to significant improvements in overall patient outcomes; however, there are limited data on the impact on bone density. The aim of this study was to describe the effect of Fabry-specific therapies on longitudinal changes in bone mineral density (BMD) in FD. We performed a retrospective observational study analysing bone densitometry (DXA) in patients with genetically confirmed FD. Patients were grouped based on the use of Fabry-specific therapies. The between-group longitudinal change in BMD Z-score was analysed using linear mixed effects models. A total of 88 FD patients were analysed (50 untreated; 38 treated). The mean age at first DXA was 38.5 years in the untreated group (84% female) and 43.7 years in the treated group (34% female). There was no significant longitudinal between-group difference in the BMD Z-score at the lumbar spine. However, the Z-score per year at the total hip (β = −0.105, p < 0.001) and femoral neck (β = −0.081, p = 0.001) was significantly lower over time in the treated than the untreated group. This may reflect those receiving therapy having a more severe underlying disease. Nevertheless, this suggests that Fabry-specific therapies do not reverse all disease mechanisms and that the additional management of BMD may be required in this patient population.
Quantum Tunneling and Complex Dynamics in the Suris’s Integrable Map
Authors: Hanada Yasutaka , Shudo Akira
Published: May 2024

Quantum tunneling in a two-dimensional integrable map is studied. The orbits of the map are all confined to the curves specified by the one-dimensional Hamiltonian. It is found that the behavior of tunneling splitting for the integrable map and the associated Hamiltonian system is qualitatively the same, with only a slight difference in magnitude. However, the tunneling tails of the wave functions, obtained by superposing the eigenfunctions that form the doublet, exhibit significant differences. To explore the origin of the difference, we observe the classical dynamics in the complex plane and find that the existence of branch points appearing in the potential function of the integrable map could play the role of yielding non-trivial behavior in the tunneling tail. The result highlights the subtlety of quantum tunneling, which cannot be captured in nature only by the dynamics in the real plane.
Quantum Synchronization and Entanglement of Dissipative Qubits Coupled to a Resonator
Authors: Chepelianskii Alexei D. , Shepelyansky Dima L.
Published: May 2024

In a dissipative regime, we study the properties of several qubits coupled to a driven resonator in the framework of a Jaynes–Cummings model. The time evolution and the steady state of the system are numerically analyzed within the Lindblad master equation, with up to several million components. Two semi-analytical approaches, at weak and strong (semiclassical) dissipations, are developed to describe the steady state of this system and determine its validity by comparing it with the Lindblad equation results. We show that the synchronization of several qubits with the driving phase can be obtained due to their coupling to the resonator. We establish the existence of two different qubit synchronization regimes: In the first one, the semiclassical approach describes well the dynamics of qubits and, thus, their quantum features and entanglement are suppressed by dissipation and the synchronization is essentially classical. In the second one, the entangled steady state of a pair of qubits remains synchronized in the presence of dissipation and decoherence, corresponding to the regime non-existent in classical synchronization.
Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course
Authors: Starks Francheska D. , Reeves Shalaunda M. , Rickert Jonathan , Li Kyle , Couch Brock , Millunchick Joanna
Published: May 2024

There is a nationwide effort to increase the representation and engagement of minoritized students in computer science education. Discourse about the barriers to diversity among computer science majors is often characterized by student pathologies and does not consider the impacts of classroom culture and instructor pedagogies. Amid the push for strategies to recruit and retain minoritized students in computer science, little has been done to transform curriculum and analyze faculty perspectives on curriculum and pedagogy as methods to increase students’ access to the computer science major. This paper presents an example of curriculum redesign for an undergraduate introductory computer science course (ICS) that sought to address issues of inequitable representation by centering student identities and redistributing power in favor of students. The authors draw upon critical sociocultural and the 4Es heuristic for disciplinary literacy to reimagine the ICS course as a space that centers on the important roles of identity and power in solving for diversity in computer science education. We highlight for researchers and practitioners how our work may be used to disrupt meritocratic practices that alienate minoritized and economically disadvantaged students and to expand definitions of mastery and expertise in computer science education.
The Potential of Narrative for Understanding Protein Biosynthesis in the Context of Viral Infections
Authors: Zabel Jörg , Averdunk Cornelia
Published: May 2024

Based on the assumption that the process of understanding is partly narrative, this study explores the potential benefits and limitations of using narrative writing in biology education. We investigate what contribution a student-centered narrative intervention can make to the conceptual understanding of protein biosynthesis in the context of viral infections and virus replication. After a teaching sequence on this topic, 68 secondary school students (M = 15.7 years, SD = 0.57 years) explained virus replication in a written text. One subsample (n = 46) was instructed to write a narrative text, while the other one (n = 22) was asked to write an expository (non-fictional) text. Our data analysis encompassed an analysis of the structural narrativity in the student texts, as well as a concept-related rating of the level of scientific correctness in three categories. A post-test questionnaire (35 items) was used to depict the learners’ viewpoints on their respective text production and the learning process that they experienced. Our findings indicate that most learners actually produced the text type they were supposed to, with exceptions in both sub-samples. As to the level of concept-related scientific correctness, we found no major differences between the two interventions. However, for two concepts, compartmentalization and levels of organization, the data indicate the significant advantage of the narrative intervention. We conclude from our results that to some extent, the effective learning properties of narrative texts, derived from the theoretical foundations, could indeed successfully be demonstrated in the field of virus replication. However, narrative text production is not equally beneficial for all aspects of the biological topic, and it also poses specific problems for some learners.
Cohesive Online Education Model Using Emergent Technologies to Improve Accessibility and Impact
Authors: Swanepoel Jan Adriaan
Published: May 2024

It is commonly known that the present systems and techniques used in education are outdated. In 1983, UNESCO had already called attention to this, calling present techniques archaic and inefficient. Though a lot of new developments have been achieved and a lot of commendable work has been carried out to remedy particular shortfalls in present systems, no literature was found that develops a concise and complete model for an education approach that maps the use of emergent technologies and techniques to improve on shortfalls in present teaching and learning paradigms. This paper reviews emergent technologies and techniques and their impacts and successes, to propose a combined model for online education to improve the effectiveness, accessibility and impact of teaching and learning activities. This paper concludes by presenting the possible future scope of education and employment structures by examining the possible impacts of the proposed model.
Exploring Decision-Making Competence in Sugar-Substitute Choices: A Cross-Disciplinary Investigation among Chemistry and Sports and Health Students
Authors: Dindorf Carlo , Weisenburger Fabienne , Bartaguiz Eva , Dully Jonas , Klappenberger Luisa , Lang Vanessa , Zimmermann Lisa , Fröhlich Michael , Seibert Johann-Nikolaus
Published: May 2024

Interdisciplinary teaching approaches have gained significant importance in today’s educational landscape. Among these approaches, decision-making competence plays a pivotal role by nurturing critical thinking and problem-solving skills. Focusing on the decision-making process regarding the sensibility of using sugar-substitutes, this study addresses three key questions. (1) Do chemistry and sports and health students differ in evaluation-competence? (2) What criteria do they use in evaluating the decision-making problem? (3) How do they use ChatGPT (OpenAI, San Francisco, CA, USA), an AI tool, in decision-making? Through surveys, the study revealed two evaluation-competence factors, identified decision-making criteria, and analyzed querying behavior using ChatGPT. The results revealed nuanced differences between the two student groups in the factors of evaluation-competence. While both groups showed improvements in recognizing moral dimensions and considering alternatives, chemistry students displayed enhanced abilities in establishing evaluation criteria and empathetic thinking. Furthermore, differences emerged in the criteria selected for decision-making and querying behavior, indicating varying engagement with ChatGPT. This study offers insights into enhancing interdisciplinary education and underscores the need for tailored interventions to address diverse student needs.
International Perspectives on Inclusion in Education: Exploring Common Ground from Different Angles
Authors: Honkasilta Juho , Koutsoklenis Athanasios
Published: May 2024

Inclusion in education is a globally shared principle, and its aim is to guarantee, secure, and promote the equality and equity of all people by removing barriers to learning and social participation [...]
Stability Analysis via Impedance Modelling of a Real-World Wind Generation System with AC Collector and LCC-Based HVDC Transmission Grid
Authors: Arshad Muhammad , Beik Omid , Manzoor Muhammad Owais , Gholamian Mahzad
Published: May 2024

This paper studies the stability of a real-world wind farm, Bison Wind Generation System (BWGS) in the state of North Dakota in the United States. BWGS uses an AC collector grid rated at 34.5 kV and a symmetrical bipolar high-voltage DC (HVDC) transmission grid rated at ±250 kV. The HVDC line transfers a total power of 0.5 GW, while both the HVDC rectifier and inverter substations use line-commuted converters (LCCs). The LCC-based rectifier adopts constant DC current control to regulate HVDC current, while the inverter operates in constant extinction angle control mode to maintain a fixed HVDC voltage. This paper proposes a frequency scan-based approach to obtain the d–q impedance model of (i) BWGS AC collector grids with Type 4 wind turbines that use permanent magnet synchronous generators (PMSGs) and two fully rated converters, and (ii) an LCC-HVDC system. The impedance frequency response of the BWGS is acquired by exciting the AC collector grid and LCC-HVDC with multi-sine voltage perturbations during its steady-state operation. The resulting voltage and current signals are subjected to a fast Fourier transform (FFT) to extract frequency components. By analyzing the impedance frequency response measurement of BWGS, a linear time–invariant (LTI) representation of its dynamics is obtained using the vector fitting (VF) technique. Finally, a Bode plot is applied, considering the impedance of the BWGS and grid to perform stability analyses. This study examines the influence of the short circuit ratio (SCR) of the grid and the phase lock loop (PLL) frequency bandwidth on the stability of the overall system. The findings provide valuable insights for the design and verification of an AC collector and LCC-based HVDC transmission systems. The findings suggest that the extraction of the impedance model of a real-world wind farm, achieved through frequency scanning and subsequent representation as an LTI system using VF, is regarded as a robust, suitable, and accurate methodology for investigating the dynamics, unstable operating conditions, and control interaction of the wind farm and LCC-HVDC system with the AC grid.
Flexible Quantization for Efficient Convolutional Neural Networks
Authors: Zacchigna Federico Giordano , Lew Sergio , Lutenberg Ariel
Published: May 2024

This work focuses on the efficient quantization of convolutional neural networks (CNNs). Specifically, we introduce a method called non-uniform uniform quantization (NUUQ), a novel quantization methodology that combines the benefits of non-uniform quantization, such as high compression levels, with the advantages of uniform quantization, which enables an efficient implementation in fixed-point hardware. NUUQ is based on decoupling the quantization levels from the number of bits. This decoupling allows for a trade-off between the spatial and temporal complexity of the implementation, which can be leveraged to further reduce the spatial complexity of the CNN, without a significant performance loss. Additionally, we explore different quantization configurations and address typical use cases. The NUUQ algorithm demonstrates the capability to achieve compression levels equivalent to 2 bits without an accuracy loss and even levels equivalent to ∼1.58 bits, but with a loss in performance of only ∼0.6%.
Hydrogen Storage and Combustion for Blackout Protection of Mine Water Pumping Stations
Authors: Chmiela Andrzej , Wrona Paweł , Magdziarczyk Małgorzata , Liu Ronghou , Zhang Le , Smolinski Adam
Published: May 2024

Global warming increases the risk of power outages. Mine water pumping stations pump approximately 100 million m3 of water per year (2023). The cessation of mine water pumping would expose neighboring mines and lower lying areas to flooding. The pumping stations have some containment, but a prolonged shutdown could cause environmental problems. Remediation of the resulting damage would be costly and time-consuming. The combination of the problems of dewatering abandoned mines and storing energy in the form of hydrogen to ensure continuity of power supply to pumping stations has not been the subject of extensive scientific research. The purpose of this paper was to develop options for protecting mine water pumping stations against the “blackout” phenomenon and to assess their investment relevance. Six technically feasible options for the modernization of mine water pumping stations were designed and analyzed in the study. All pumping station modernization options include storage of the generated energy in the form of green hydrogen. For Q1 2024 conditions, the option with the partial retail sale of the produced hydrogen and the increased volume of produced water for treatment is recommended for implementation.
R455A Refrigerant as a Prospective Working Fluid in Refrigeration Systems for Gastronomy Furnishings
Authors: Bernat Tomasz , Bieńczak Krzysztof
Published: May 2024

The general development of technology and universal access means that gastronomy furnishings can be found in every corner of the world. Therefore, it is important to develop these devices and the machines that constitute them. We are talking about refrigeration systems located inside gastronomy furnishings. The R404A refrigerant, popular in recent years, is being withdrawn from use due to its harmful impact on the environment. Modern synthetic refrigerants or natural refrigerants can be used as alternative substances. In modern solutions, it is expected that devices and all cooperating elements have the lowest possible harmful impact on the environment and the user while, at the same time, having the highest possible energy efficiency. First, tests were carried out with the R404A refrigerant. Then, the working medium was replaced without changing any element of the refrigeration system with the modern R455A refrigerant. The system was tested in terms of the operating parameters achieved and in terms of electricity consumption. It was found that there is an alternative R455A refrigerant operating in the refrigeration system of catering furnishings, which provides the system with an average of 34% better energy efficiency than the reference refrigerant R404A. It was also found that the time needed to achieve the set working conditions decreased. An alternative refrigerant allows a refrigeration system to be built based on components available on the market or one that can be used as a direct replacement for the old refrigerant.
Open-Circuit Voltage Variation in LiCoO2 Battery Cycled in Different States of Charge Regions
Authors: Barcellona Simone , Codecasa Lorenzo , Colnago Silvia , Piegari Luigi
Published: May 2024

Currently, the urgent needs of sustainable mobility and green energy generation are driving governments and researchers to explore innovative energy storage systems. Concurrently, lithium-ion batteries are one of the most extensively employed technologies. The challenges of battery modeling and parameter estimation are crucial for building reliable battery management systems that ensure optimal battery performance. State of charge (SOC) estimation is particularly critical for predicting the available capacity in the battery. Many methods for SOC estimation rely on the knowledge of the open-circuit voltage (OCV) curve. Another significant consideration is understanding how these curves evolve with battery degradation. In the literature, the effect of cycle aging on the OCV is primarily addressed through the look-up tables and correction factors applied to the OCV curve for fresh cells. However, the variation law of the OCV curve as a function of the battery cycling is not well-characterized. Building upon a simple analytical function with five parameters proposed in the prior research to model the OCV as a function of the absolute state of discharge, this study investigates the dependency of these parameters on the moved charge, serving as an indicator of the cycling level. Specifically, the analysis focuses on the impact of cycle aging in the low-, medium-, and high-SOC regions. Three different cycle aging tests were conducted in these SOC intervals, followed by the extensive experimental verification of the proposed model. The results were promising, with mean relative errors lower than 0.2% for the low- and high-SOC cycling regions and 0.34% for the medium-SOC cycling region. Finally, capacity estimation was enabled by the model, achieving relative error values lower than 1% for all the tests.
‘Low ILUC-Risk’ as a Sustainability Standard for Biofuels in the EU
Authors: Sandford Cato , Malins Chris , Vourliotakis George , Panoutsou Calliope
Published: May 2024

Producers of biofuels for the EU market may use ‘low ILUC-risk’ certification as evidence that they have not deprived other economic sectors of feedstock material, and hence that indirect land use change (ILUC) emissions have been avoided. At present, the uptake of low ILUC-risk certification is limited to a handful of niche projects, as there is little commercial incentive for obtaining certification. This may be considered a missed opportunity, because low ILUC-risk farming methods offer a range of sustainability co-benefits beyond the mitigation of ILUC emissions. This paper examines the policy foundations of low ILUC-risk and develops policy recommendations that would aim to confer advantages to low ILUC-risk biofuels. Some weaknesses in the low ILUC-risk system’s environmental safeguards are also highlighted.
Vertical-Axis Tidal Turbines: Model Development and Farm Layout Design
Authors: Pucci Micol , Spina Raffaele , Zanforlin Stefania
Published: May 2024

In this paper, we propose a new 3D model for vertical-axis tidal turbines (VATTs) embedded in the shallow-water code SHYFEM. The turbine model is based on the Blade-Element∖Momentum (BEM) theory and, therefore, is able to predict turbine performance based on the local flow conditions and the geometric characteristics of the turbine. It is particularly suitable for studying turbine arrays, as it can capture the interactions between the turbines. For this reason, the model is used to test a tidal farm of 21 devices with fluid dynamic simulations. In particular, we deploy the farm at Portland Bill, which is a marine site characterised by a wide spread in the direction of the tidal currents during a flood-ebb tide cycle. We optimised the lateral and longitudinal spacing of the turbines in a fence using computational fluid dynamics simulations and then performed a sensitivity analysis by changing the distance between the fences. The results show that the greater the distance between the fences, the higher the power output. The increase in power generation is around 16%, but this implies a huge increase in the horizontal extent of the farm. Further assessments should be carried out, as the expansion of a marine area dedicated to energy exploitation may conflict with other stakeholder interests.
Real-Time Microgrid Energy Scheduling Using Meta-Reinforcement Learning
Authors: Shen Huan , Shen Xingfa , Chen Yiming
Published: May 2024

With the rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids’ efficient, stable, and economical operation in their initial stages.
Start of Injection Influence on In-Cylinder Fuel Distribution, Engine Performance and Emission Characteristic in a RCCI Marine Engine
Authors: Kakoee Alireza , Mikulski Maciej , Vasudev Aneesh , Axelsson Martin , Hyvönen Jari , Salahi Mohammad Mahdi , Mahmoudzadeh Andwari Amin
Published: May 2024

Reactivity-controlled compression ignition (RCCI) is a promising new combustion technology for marine applications. It has offered the potential to achieve low NOx emissions and high thermal efficiency, which are both important considerations for marine engines. However, the performance of RCCI engines is sensitive to a number of factors, including the start of injection. This study used computational fluid dynamics (CFD) to investigate the effects of start of ignition (SOI) on the performance of a marine RCCI engine. The CFD model was validated against experimental data, and the results showed that the SOI has a significant impact on the combustion process. In particular, the SOI affected the distribution of fuel and air in the combustion chamber, which in turn affected the rate of heat release and the formation of pollutants. Ten different SOIs were implemented on a validated closed-loop CFD model from 96 to 42 CAD bTDC (crank angle degree before top dead center) at six-degree intervals. A chemical kinetic mechanism of 54 species and 269 reactions tuned and used for simulation of in-cylinder combustion. The results show that in early injection, high-reactivity fuel was distributed close to the liner. This distribution was around the center of late injection angles. A homogeneity study was carried out to investigate the local equivalence ratio. It showed a more homogenous mixture in early injection until 66 CAD bTDC, after which point, earlier injection timing had no effect on homogeneity. Maximum indicated mean effective pressure (IMEP) was achieved at SOI 48 CAD bTDC, and minimum amounts of THC (total hydrocarbons) and NOx were observed with middle injection timing angles around 66 CAD bTDC.
Environmental Impact Evaluation of CO2 Absorption and Desorption Enhancement by Membrane Gas Absorption: A Life Cycle Assessment Study
Authors: Li Fuzhao , Lv Yuexia , Bi Jinpeng , Zhang Hui , Zhao Wei , Su Yancai , Du Tingting , Mu Junkun
Published: May 2024

Membrane gas absorption technology has been considered a promising approach to mitigate CO2 emissions from power plants. The aim of this study is to evaluate the environmental impacts of CO2 absorption and desorption processes by hollow fiber membrane contactors using a life cycle assessment methodology. On the basis of the ReCipe 2016 Midpoint and the ReCipe 2016 Endpoint methods, the research results show that membrane gas absorption systems exhibit the lowest environmental impacts across the majority of assessed categories in comparison with chemical absorption and membrane gas separation systems. The CO2 capture process via membrane gas absorption has the most significant impact on the METP category, with heat consumption as the primary contributing factor accounting for 55%, followed by electricity consumption accounting for 43.1%. According to the sensitivity analysis, heating by natural gas shows better performance than other heat supply sources in improving overall environmental impacts. In addition, the increasing utilization of renewable energy in electricity supply reduces the global warming potential, fossil resource consumption and ozone formation.
Insights into Cold Plasma Treatment on the Cereal and Legume Proteins Modification: Principle, Mechanism, and Application
Authors: Li Bin , Peng Lianxin , Cao Yanan , Liu Siyao , Zhu Yuchen , Dou Jianguo , Yang Zhen , Zhou Chenguang
Published: May 2024

Cereal and legume proteins, pivotal for human health, significantly influence the quality and stability of processed foods. Despite their importance, the inherent limited functional properties of these natural proteins constrain their utility across various sectors, including the food, packaging, and pharmaceutical industries. Enhancing functional attributes of cereal and legume proteins through scientific and technological interventions is essential to broadening their application. Cold plasma (CP) technology, characterized by its non-toxic, non-thermal nature, presents numerous benefits such as low operational temperatures, lack of external chemical reagents, and cost-effectiveness. It holds the promise of improving proteins’ functionality while maximally retaining their nutritional content. This review delves into the pros and cons of different cold plasma generation techniques, elucidates the underlying mechanisms of protein modification via CP, and thoroughly examines research on the application of cold plasma in augmenting the functional properties of proteins. The aim is to furnish theoretical foundations for leveraging CP technology in the modification of cereal and legume proteins, thereby enhancing their practical applicability in diverse industries.
Therapeutic Potential of Fucoidan in Alleviating Histamine-Induced Liver Injury: Insights from Mice Studies
Authors: Zhang Mengyao , Liu Huiqian , Xu Linlin , Zhang Xizi , Chen Wei , Wang Chengtao
Published: May 2024

Histamine, a bioactive component in certain foods such as Huangjiu has been associated with liver injury and disrupted intestinal balance. This study explored the potential therapeutic effects of fucoidan (FCD) in mitigating histamine-induced imbalances in mice. We found that FCD mitigated liver injury, reducing transaminases, oxidative stress, and inflammation. Histological improvements included decreased cell infiltration and necrosis. FCD restored tight junction proteins and suppressed inflammation-related genes. Western blot analysis revealed FCD’s impact on TGF-β1, p-AKT, AKT, CYP2E1, Grp78, NLRP3, Cas-1, and GSDMD. Gut LPS levels decreased with FCD. Gut microbiota analysis showed FCD’s modulation effect, reducing Firmicutes and increasing Bacteroides. FCD demonstrates potential in alleviating histamine-induced liver injury, regulating inflammation, and influencing gut microbiota. Further research exploring higher dosages and additional parameters is warranted.
Altered Expression of PDE4 Genes in Schizophrenia: Insights from a Brain and Blood Sample Meta-Analysis and iPSC-Derived Neurons
Authors: Burrack Nitzan , Yitzhaky Assif , Mizrahi Liron , Wang Meiyan , Stern Shani , Hertzberg Libi
Published: May 2024

Schizophrenia symptomatology includes negative symptoms and cognitive impairment. Several studies have linked schizophrenia with the PDE4 family of enzymes due to their genetic association and function in cognitive processes such as long-term potentiation. We conducted a systematic gene expression meta-analysis of four PDE4 genes (PDE4A-D) in 10 brain sample datasets (437 samples) and three blood sample datasets (300 samples). Subsequently, we measured mRNA levels in iPSC-derived hippocampal dentate gyrus neurons generated from fibroblasts of three groups: healthy controls, healthy monozygotic twins (MZ), and their MZ siblings with schizophrenia. We found downregulation of PDE4B in brain tissues, further validated by independent data of the CommonMind consortium (515 samples). Interestingly, the downregulation signal was present in a subgroup of the patients, while the others showed no differential expression or even upregulation. Notably, PDE4A, PDE4B, and PDE4D exhibited upregulation in iPSC-derived neurons compared to healthy controls, whereas in blood samples, PDE4B was found to be upregulated while PDE4A was downregulated. While the precise mechanism and direction of altered PDE4 expression necessitate further investigation, the observed multilevel differential expression across the brain, blood, and iPSC-derived neurons compellingly suggests the involvement of PDE4 genes in the pathophysiology of schizophrenia.
Genome-Wide Identification and Hormone Response Analysis of the COBL Gene Family in Barley
Authors: Ren Panrong , Ma Liang , Bao Wei , Wang Jie
Published: May 2024

Barley (Hordeum vulgare L.), a diverse cereal crop, exhibits remarkable versatility in its applications, ranging from food and fodder to industrial uses. The content of cellulose in barley is significantly influenced by the COBRA genes, which encode the plant glycosylphosphatidylinositol (GPI)-anchored protein (GAP) that plays a pivotal role in the deposition of cellulose within the cell wall. The COBL (COBRA-Like) gene family has been discovered across numerous species, yet the specific members of this family in barley remain undetermined. In this study, we discovered 13 COBL genes within the barley genome using bioinformatics methods, subcellular localization, and protein structure analysis, finding that most of the barley COBL proteins have a signal peptide structure and are localized on the plasma membrane. Simultaneously, we constructed a phylogenetic tree and undertook a comprehensive analysis of the evolutionary relationships. Other characteristics of HvCOBL family members, including intraspecific collinearity, gene structure, conserved motifs, and cis-acting elements, were thoroughly characterized in detail. The assessment of HvCOBL gene expression in barley under various hormone treatments was conducted through qRT-PCR analysis, revealing jasmonic acid (JA) as the predominant hormonal regulator of HvCOBL gene expression. In summary, this study comprehensively identified and analyzed the barley COBL gene family, aiming to provide basic information for exploring the members of the HvCOBL gene family and to propose directions for further research.