bluuebunny/crossref_metadata_2025 huggingface dataset:
Equivalent Spatial Plane-Based Relative Pose Estimation of UAVs
Authors: Wang Hangyu , Gong Shuangyi , Chen Chaobo , Li Jichao
Published: August 2024

The accuracy of relative pose estimation is an important foundation for ensuring the safety and stability of autonomous aerial refueling (AAR) of unmanned aerial vehicles (UAV), and in response to this problem, a relative pose estimation method of UAVs based on the spatial equivalent plane is proposed in this paper. The UAV is equivalent to a spatial polygonal plane, and according to the measurement information of the Global Navigation Satellite System (GNSS) receivers, the equivalent polygonal plane equation is solved through the three-point normal vector and the minimum sum of squares of the distance from the four points to the plane. The equations of the distance between the geometric centers of the two polygonal planes, the angle between planes, and the angle between lines are used to calculate the relative pose information of the UAVs. Finally, the simulation environment and initial parameters are utilized for numerical simulation and results analysis. The simulation results show that without considering the motion model of the UAV, the proposed method can accurately estimate the relative pose information of the UAVs. In addition, in the presence of measurement errors, the relative pose estimation method based on the equivalent triangle plane can identify the position of the measurement point with the error, and the relative pose estimation method based on the equivalent quadrilateral plane has good robustness. The simulation results verify the feasibility and effectiveness of the proposed method.
Generalized Kinetic Equations with Fractional Time-Derivative and Nonlinear Diffusion: H-Theorem and Entropy
Authors: Lenzi Ervin K. , Rosseto Michely P. , Gryczak Derik W. , Evangelista Luiz R. , da Silva Luciano R. , Lenzi Marcelo K. , Zola Rafael S.
Published: August 2024

We investigate the H-theorem for a class of generalized kinetic equations with fractional time-derivative, hyperbolic term, and nonlinear diffusion. When the H-theorem is satisfied, we demonstrate that different entropic forms may emerge due to the equation’s nonlinearity. We obtain the entropy production related to these entropies and show that its form remains invariant. Furthermore, we investigate some behaviors for these equations from both numerical and analytical perspectives, showing a large class of behaviors connected with anomalous diffusion and their effects on entropy.
Is It Sufficient to Select the Optimal Class Number Based Only on Information Criteria in Fixed- and Random-Parameter Latent Class Discrete Choice Modeling Approaches?
Authors: Czine Péter , Balogh Péter , Blága Zsanett , Szabó Zoltán , Szekeres Réka , Hess Stephane , Juhász Béla
Published: August 2024

Heterogeneity in preferences can be addressed through various discrete choice modeling approaches. The random-parameter latent class (RLC) approach offers a desirable alternative for analysts due to its advantageous properties of separating classes with different preferences and capturing the remaining heterogeneity within classes by including random parameters. For latent class specifications, however, more empirical evidence on the optimal number of classes to consider is needed in order to develop a more objective set of criteria. To investigate this question, we tested cases with different class numbers (for both fixed- and random-parameter latent class modeling) by analyzing data from a discrete choice experiment conducted in 2021 (examined preferences regarding COVID-19 vaccines). We compared models using commonly used indicators such as the Bayesian information criterion, and we took into account, among others, a seemingly simple but often overlooked indicator such as the ratio of significant parameter estimates. Based on our results, it is not sufficient to decide on the optimal number of classes in the latent class modeling based on only information criteria. We considered aspects such as the ratio of significant parameter estimates (it may be interesting to examine this both between and within specifications to find out which model type and class number has the most balanced ratio); the validity of the coefficients obtained (focusing on whether the conclusions are consistent with our theoretical model); whether including random parameters is justified (finding a balance between the complexity of the model and its information content, i.e., to examine when (and to what extent) the introduction of within-class heterogeneity is relevant); and the distributions of MRS calculations (since they often function as a direct measure of preferences, it is necessary to test how consistent the distributions of specifications with different class numbers are (if they are highly, i.e., relatively stable in explaining consumer preferences, it is probably worth putting more emphasis on the aspects mentioned above when choosing a model)). The results of this research raise further questions that should be addressed by further model testing in the future.
The Context and Development of Teachers’ Collective Reflections on Student Data
Authors: Prough Sam , Webster Amber , Gibbons Lynsey K.
Published: August 2024

In the United States, teachers are often expected to use student assessment data to inform their instructional decisions. This study explores how teachers’ collective reflections on students’ mathematical thinking are influenced by the specific contexts of their classroom, school, and current events like the COVID-19 pandemic. The study uses audio recordings of a group of elementary teachers’ reflections on student thinking through Cognitive Interview Reports. The results highlight how teachers’ reflections on student data are heavily influenced by the shifting contexts of what is important in the world of teaching due to the COVID-19 pandemic. This ultimately shaped what the teachers were able to pay attention to in student data and what they identified as possible in their future practice.
YOLO-ADS: An Improved YOLOv8 Algorithm for Metal Surface Defect Detection
Authors: Gui Zili , Geng Jianping
Published: August 2024

Addressing issues such as susceptibility to background interference and variability in feature scales of fine-grained defects on metal surfaces, as well as the relatively poor versatility of the baseline model YOLOv8n, this study proposes a YOLO-ADS algorithm for metal surface defect detection. Firstly, a novel CSPNet with Average SPP-Fast Block (ASPPFCSPC) module is proposed to enhance the model’s fusion and representation ability between local features and global background information. Secondly, the newly improved module C2f_SimDCNv2 is utilized to improve the ability of the model to extract multi-scale features. Finally, the Space-to-Depth (SPD) layer is introduced to prevent the loss of fine-grained information from small target features and reduce the redundancy between convolution operations. Experimental results demonstrate that the mean Average Precision (mAP) and Precision of the YOLO-ADS algorithm on the steel strip surface defect dataset NEU-DET reach 81.4% and 79.7%, which are severally increased by 3.5% and 6.1%, and the Frames Per Second (FPS) reaches 140.4. Meanwhile, the versatility and robustness of the model are verified on the industrial steel surface defect dataset GC10-DET, the industrial aluminum surface defect dataset APSPC and even the larger public benchmark dataset VOC2012, the mAP is respectively increased by 3.7%, 3.4% and 4.3%. Compared with the mainstream detection algorithms, YOLO-ADS algorithm is ahead of a certain advanced level in detection accuracy while maintaining a good real-time performance, which provides an efficient and feasible solution for the field of metal surface defect detection.
Exploring Performance of Pyrolysis-Derived Plastic Oils in Gas Turbine Engines
Authors: Suchocki Tomasz , Kazimierski Paweł , Januszewicz Katarzyna , Lampart Piotr , Gawron Bartosz , Białecki Tomasz
Published: August 2024

This study explores the intersection of waste management and sustainable fuel production, focusing on the pyrolysis of plastic waste, specifically polystyrene. We examine the physicochemical parameters of the resulting waste plastic pyrolytic oils (WPPOs), blended with kerosene to form a potential alternative fuel for gas turbines. Our findings reveal that all WPPO blends lead to increased emissions, with NOX rising by an average of 61% and CO by 25%. Increasing the proportion of WPPO also resulted in a higher exhaust gas temperature, with an average rise of 12.2%. However, the thrust-specific fuel consumption (TSFC) decreased by an average of 13.8%, impacting the overall efficiency of waste-derived fuels. This study underscores the need for integrated waste-to-energy systems, bridging the gap between waste management and resource utilization.
Investment in Offshore Wind Energy in Poland and Its Impact on Public Opinion
Authors: Chomać-Pierzecka Ewa
Published: August 2024

The availability of energy-bearing resources is a key determinant of the development strategy of the world’s energy systems. In the case of Poland, the wind energy potential of the Baltic Sea provides the basis for the development of offshore wind energy in the country. The processes of transforming solutions towards green technologies require appropriate legislation, significant financial outlays, as well as public support for this dimension of activities. The latter strand requires continuous measurement to dynamically model the energy transition strategy. In the author’s opinion, the available literature does not sufficiently explain this theme in relation to Polish conditions. Hence, it was considered reasonable to investigate the impact of offshore wind energy development in Poland on public opinion in a selected region of Poland, in order to diagnose the current scale of support for the changes taking place, and to identify the main expectations and fears related to this activity, which was assumed as the main objective of the study. The added value of the survey is the analysis of changes in public opinion over time. The methodology used for the research was a study of the scientific literature, with analysis of the results of own and secondary research conducted in Poland. In terms of in-depth research, statistical survey techniques supported by the PQstat programme were used. The results of the survey confirmed significant public support in the surveyed area for offshore wind energy development in Poland (68%). The overall percentage of support for offshore development increased by 5% y/y. Economic considerations for the support of the activities in question with the potential vision of lowering energy prices in the domestic market were confirmed with a result of 65%. It was further confirmed that a key aspect of support for the offshore development strategy in the surveyed region of Poland is the potential for development of the region in relation to offshore farm investments, with a focus on the labour market, with indications of 53% for both themes. Interestingly, there was no concern in relation to the risk of landscape change in an undesirable direction in 2024.
A Nernst-Based Approach for Modeling of Lithium-Ion Batteries with Non-Flat Voltage Characteristics
Authors: Ahmad Athar , Iamarino Mario , D’Angola Antonio
Published: August 2024

This paper presents an easy-to-implement model to predict the voltage in a class of Li-ion batteries characterized by non-flat, gradually decreasing voltage versus capacity. The main application is for the accurate estimation of the battery state of the charge, as in the energy management systems of battery packs used in stationary and mobility applications. The model includes a limited number of parameters and is based on a simple equivalent circuit representation where an open circuit voltage source is connected in series with an equivalent resistance. The non-linear open circuit voltage is described using a Nernst-like term, and the model parameters are estimated based on the manufacturer discharge curves. The results show a good level of model accuracy in the case of three different commercial batteries considered by the study: Panasonic CGR18650AF, Panasonic NCR18650B and Tesla 4680. In particular, accurate description of the voltage curves versus the state of charge at different constant currents and during charging/discharging cycles is achieved. A possible model reduction is also addressed, and the effect of the equivalent internal resistance in improving the model predictions near fully depleted conditions is highlighted.
Identifying Weak Transmission Lines in Power Systems with Intermittent Energy Resources and DC Integration
Authors: He Anqi , Cao Jijing , Li Shangwen , Gong Lianlian , Yang Mingming , Hu Jiawei
Published: August 2024

Nowadays, intermittent energy resources, such as wind turbines, and direct current (DC) transmission have been extensively integrated into power systems. This paper proposes an identifying method for weak lines of novel power systems with intermittent energy resources and DC lines integration, which aims to provide decision making for control strategies of novel power systems and prevent system blackouts. First, from the perspective of power system safety and stability, a series of risk indicators for the risk assessment of vulnerable lines is proposed. Then, lines in the system are tripped one by one. The calculation method for the proposed risk indicators is introduced. The impact of each line outage on system safety and stability can be fairly evaluated by these proposed risk indicators. On this basis, each risk assessment indicator is weighted to obtain a comprehensive risk assessment indicator, and then the risk caused by each line outage on the system can be quantified efficiently. Finally, the test system of a modified IEEE-39 bus system with wind farms and DC lines integration is used to verify the applicability of the proposed method, and the effectiveness of the proposed method is also demonstrated by comparing with existing methods.
Categorization of Attributes and Features for the Location of Electric Vehicle Charging Stations
Authors: Mazza Andrea , Russo Angela , Chicco Gianfranco , Di Martino Andrea , Colombo Cristian , Longo Michela , Ciliento Paolo , De Donno Marco , Mapelli Francesca , Lamberti Francesco
Published: August 2024

The location of Electric Vehicle Charging Stations (EVCSs) is gaining significant importance as part of the conversion to a full-electric vehicle fleet. Positive or negative impacts can be generated mainly based on the quality of service offered to customers and operational efficiency, also potentially involving the electrical grid to which the EVCSs are connected. The EVCS location problem requires an in-depth and comprehensive analysis of geographical, market, urban planning, and operational aspects that can lead to several potential alternatives to be evaluated with respect to a defined number of features. This paper discusses the possible use of a multi-criteria decision-making approach, considering the differences between multi-objective decision making (MODM) and multi-attribute decision-making (MADM), to address the EVCS location problem. The conceptual evaluation leads to the conclusion that the MADM approach is more suitable than MODM for the specific problem. The identification of suitable attributes and related features is then carried out based on a systematic literature review. For each attribute, the relative importance of the features is obtained by considering the occurrence and the dedicated weights. The results provide the identification of the most used attributes and the categorization of the selected features to shape the proposed MADM framework for the location of the electric vehicle charging infrastructure.
Sizing Methodology of Dynamic Wireless Charging Infrastructures for Electric Vehicles in Highways: An Italian Case Study
Authors: Apicella Valerio , Turati Alessandro , Megna Giovanni , Carambia Benedetto
Published: August 2024

The necessity of pushing the road mobility towards more sustainable solutions has become of undeniable importance in last years. For this reason, both research and industry are constantly investigating new technologies able to make the usage of battery electric vehicles(BEV) as accessible and usable as traditional internal combustion engine vehicles (ICEV). One of the most limiting issues concerns the short range of electric vehicles, which complicates their use for long distances, such as for highway travels. A promising solution seems to be the “charge-while-driving” approach, by exploiting the inductive dynamic wireless power transfer (DWPT) technology. Nevertheless, such systems show different issues, first of all, high investment and maintenance costs. Furthermore, it is not clear how extensive a potential dynamic wireless charging infrastructure needs to be to make a real advantage for electric vehicle drivers. As a consequence, the aim of this paper is to introduce a new methodology to estimate the number and length of wireless charging sections necessary to allow the maximum number of electric vehicles to travel a specific highway without the need to stop for a recharge at a service area. Specifically, the methodology is based on a algorithm that, starting by real traffic data, simulates vehicle flows and defines the basic layout of the wireless charging infrastructure. This simulator can provide a decision support tool for highway road operators.
Research on Energy Management Strategy for Hybrid Tractors Based on DP-MPC
Authors: Zhao Yifan , Xu Liyou , Zhao Chenhui , Xu Haigang , Yan Xianghai
Published: August 2024

To further improve the fuel economy of hybrid tractors, an energy management strategy based on model predictive control (MPC) solved by dynamic programming (DP) is proposed, taking into account the various typical operating conditions of tractors. A coupled dynamics model was constructed for a series diesel–electric hybrid tractor under three typical working conditions: plowing, rotary tillage, and transportation. Using DP to solve for the globally optimal SOC change trajectory under each operating condition of the tractor as the SOC constraint for MPC, we designed an energy management strategy based on DP-MPC. Finally, a hardware-in-the-loop (HIL) test platform was built using components such as Matlab/Simulink, NI-Veristand, PowerCal, HIL test cabinet, and vehicle controller. The designed energy management strategy was then tested using the HIL test platform. The test results show that, compared with the energy management strategy based on power following, the DP-MPC-based energy management strategy reduces fuel consumption by approximately 7.97%, 13.06%, and 11.03%, respectively, under the three operating conditions of plowing, rotary tillage, and transportation. This achieves fuel-saving performances of approximately 91.34%, 94.87%, and 96.69% compared to global dynamic programming. The test results verify the effectiveness of the proposed strategy. This research can provide an important reference for the design of energy management strategies for hybrid tractors.
Enhancing Lambda Measurement in Hydrogen-Fueled SI Engines through Virtual Sensor Implementation
Authors: Ricci Federico , Avana Massimiliano , Mariani Francesco
Published: August 2024

The automotive industry is increasingly challenged to develop cleaner, more efficient solutions to comply with stringent emission standards. Hydrogen (H2)-powered internal combustion engines (ICEs) offer a promising alternative, with the potential to reduce carbon-based emissions and improve efficiency. However, hydrogen combustion presents two main challenges related to the calibration process: emissions control and measurement of the air excess coefficient (λ). Traditional lambda sensors struggle with hydrogen’s combustion dynamics, leading to potential inefficiencies and increased pollutant emissions. Consequently, the determination of engine performance could also be compromised. This study explores the feasibility of using machine learning (ML) to replace physical lambda sensors with virtual ones in hydrogen-fueled ICEs. The research was conducted on a single-cylinder spark-ignition (SI) engine, collecting data across a range of air excess coefficients from 1.6 to 3.0. An advanced hybrid model combining long short-term memory (LSTM) networks and convolutional neural networks (CNNs) was developed and fine-tuned to accurately predict the air–fuel ratio; its predictive performance was compared to that obtained with the backpropagation (BP) architecture. The optimal configuration was identified through iterative experimentation, focusing on the neuron count, number of hidden layers, and input variables. The results demonstrate that the LSTM + 1DCNN model successfully converged without overfitting; it also showed better prediction ability in terms of accuracy and robustness when compared with the backpropagation approach.
Analysis of the Energy Potential of Hazelnut Husk Depending on the Variety
Authors: Borkowska Anna , Klimek Kamila , Maj Grzegorz , Kapłan Magdalena
Published: August 2024

Interest in bioenergy, in particular the use of biomass, has increased significantly in recent years due to increasing climate and economic concerns. As one of the key renewable energy sources, biomass plays an important role in the new energy framework. The aim of this research was to estimate the mass of woody husks and to check the influence of morphological features of selected hazelnut varieties on the energy parameters of waste biomass in the form of husk. Technical and elemental analyses were carried out on the husks of four varieties: ‘Kataloński’, ‘Olbrzymi z Halle’, ‘Olga’, and ‘Webba Cenny’, taking into account their weight, moisture content, heat of combustion (HHV and LHV), and pollutant emission factors (CO, CO2, NOx, SO2, Dust). Research has shown significant differences between the varieties in terms of their energy potential and pollutant emissions. The varieties ‘Olbrzymi z Halle’ and ‘Olga’ were found to have higher calorific values, making them more energy efficient. On the other hand, the varieties ‘Kataloński’ and ‘Webba Cenny’ showed lower dust and NOx emissions, which is beneficial from an environmental point of view. The analysis of the chemical and morphological composition of hazelnut husks allowed for the identification of relationships between morphological features and energy value and emission indicators. The conclusions from the conducted research suggest that hazelnut husks have significant potential as an energy raw material. The selection of an appropriate variety for energy crops should take into account both the calorific value and emission indicators, which will allow for the optimization of production processes and the promotion of sustainable development.
Effect of Using Moisture-Buffering Finishing Materials and DCV Systems on Environmental Comfort and Energy Consumption in Buildings
Authors: Kaczorek Dobrosława , Basińska Małgorzata
Published: August 2024

One of the technical solutions to improve indoor thermal comfort and reduce energy consumption in buildings is the use of demand-controlled ventilation (DCV) systems. The choice of the control method becomes more important when the walls in the room are finished with moisture-buffering materials. This study explores the impact of four DCV system control scenarios (control of temperature, relative humidity, and carbon dioxide concentration for two different supply airflows to the room) combined with various indoor moisture-buffering materials (gypsum board and cement–lime plaster) on the variability of indoor air quality parameters, thermal comfort, and energy. The analysis was performed by computer simulation using WUFI Plus v.3.1.0.3 software for whole-building hydrothermal analysis. Control-based systems that maintain appropriate relative humidity levels were found to be the most favourable for localised comfort and were more effective in terms of energy consumption for heating and cooling without humidification and dehumidification. This research also revealed that the moisture-buffering effect of finishing materials can passively contribute to enhancing indoor air quality, regardless of the room’s purpose. However, higher energy consumption for heating was observed for better moisture-buffering materials.
Unravelling the Epigenetic Code: DNA Methylation in Plants and Its Role in Stress Response
Authors: Talarico Emanuela , Zambelli Alice , Araniti Fabrizio , Greco Eleonora , Chiappetta Adriana , Bruno Leonardo
Published: August 2024

Environmental stress significantly affects plant growth, development, and survival. Plants respond to stressors such as temperature fluctuations, water scarcity, nutrient deficiencies, and pathogen attacks through intricate molecular and physiological adaptations. Epigenetic mechanisms are crucial in regulating gene expression in response to environmental stress. This review explores the current understanding of epigenetic modifications, including DNA methylation, and their roles in modulating gene expression patterns under environmental stress conditions. The dynamic nature of epigenetic modifications, their crosstalk with stress-responsive pathways, and their potential implications for plant adaptation and crop improvement are highlighted in the face of changing environmental conditions.
Innovative Postharvest Management for Hass Avocado at the Preclimacteric Stage: A Combined Technology with GABA and 1-MCP
Authors: Ruiz-Aracil María Celeste , Valverde Juan Miguel , Ilea Mihaela Iasmina Madalina , Valero Daniel , Castillo Salvador , Guillén Fabián
Published: August 2024

Avocado (Persea americana Mill.) is a subtropical climacteric fruit with a limited shelf life due to its high sensitivity to low temperatures. Chilling injury (CI) produced by cold storage displays symptoms in avocado fruit such as irregular ripening, darkening of the mesocarp, hardening of vascular strands, lipid oxidation with “off flavors”, and pitting and darkening of the skin, increasing weight loss. Accordingly, we studied the effect of γ-aminobutyric acid (GABA) and 1-methylcyclopropene (1-MCP) alone or in combination as postharvest treatments to maintain quality and to increase cold tolerance. Hass avocados were stored at 5 °C plus 5 days at room temperature. The results showed that the combined treatment improved fruit quality parameters as compared with control fruit and with those treated with only 1-MCP or GABA. The combined treatment delayed synergistically the postharvest ripening process. This delayed pattern was concomitant with a delayed ethylene pattern in GABA + 1-MCP or 1-MCP fruit batches. CI symptoms and electrolyte leakage were minimized in all GABA and 1-MCP fruit batches specifically in the combined treatment. For this reason, the synergistic effect of the combination of treatments may be recommended as an effective alternative strategy to prolong the postharvest quality of avocado during refrigerated storage.
Contemporary Speculations and Insightful Thoughts on Buckwheat—A Functional Pseudocereal as a Smart Biologically Active Supplement
Authors: Kurćubić Vladimir S. , Stajić Slaviša B. , Jakovljević Vladimir , Živković Vladimir , Stanišić Nikola , Mašković Pavle Z. , Matejić Vesna , Kurćubić Luka V.
Published: August 2024

Today, food scientists are interested in more rational use of crops that possess desirable nutritional properties, and buckwheat is one of the functional pseudocereals that represents a rich source of bioactive compounds (BACs) and nutrients, phytochemicals, antimicrobial (AM) agents and antioxidants (AOs), which can be effectively applied in the prevention of malnutrition and celiac disease and treatment of various important health problems. There is ample evidence of the high potential of buckwheat consumption in various forms (food, dietary supplements, home remedies or alone, or in synergy with pharmaceutical drugs) with concrete benefits for human health. Contamination as well as other side-effects of all the aforementioned forms for application in different ways in humans must be seriously considered. This review paper presents an overview of the most important recent research related to buckwheat bioactive compounds (BACs), highlighting their various functions and proven positive effects on human health.
Influence of Penicillium lanosum and Staphylococcus equorum on Microbial Diversity and Flavor of Mianning Hams
Authors: Wang Wenli , Zhu Yanli , Wang Wei , Zhang Jiamin , He Daolin , Ji Lili , Chen Lin
Published: August 2024

Mianning ham is a traditional meat product in China. In this experiment, solid-phase microextraction–gas chromatography (SPME-GC-MS) and high-throughput sequencing were used to study the effects of adding Penicillium lanosum and adding the mixture of Penicillium lanosum and Staphylococcus equorum on the flavor and microbiology of Mianning ham. The results showed that the addition of the ferments resulted in an increase in the abundance of both the dominant bacterial phylum (Thick-walled Bacteria) and the dominant fungal phylum (Ascomycota). The variety of volatile flavor substances and key flavor substances increased after adding fermentation agents. A free amino acid analysis showed that hams from the Penicillium lanosum and Staphylococcus equorum group had significantly higher umami flavor amino acids than the control group and Penicillium lanosum group. Therefore, inoculation with Penicillium lanosum and Staphylococcus equorum favored the dominant bacteria and flavor of Mianning ham.
Preparation and Adsorption Photocatalytic Properties of PVA/TiO2 Colloidal Photonic Crystal Films
Authors: Qian Zhangyi , Wang Menghan , Li Junling , Chu Zhaoran , Tang Wenwei , Chen Cheng
Published: August 2024

Polyvinyl alcohol (PVA)/TiO2/colloidal photonic crystal (CPC) films with photocatalytic properties are presented, where TiO2 nanoparticles were introduced into the PVA gel network. Such PVA/TiO2/CPC films possess three-dimensional periodic structures that are supported with a PVA/TiO2 composite gel. The unique structural color of CPCs can indicate the process of material preparation, adsorption, and desorption. The shift of diffraction peaks of CPCs can be more accurately determined using fiber-optic spectroscopy. The effect of the PVA/TiO2/CPC catalyst films showed better properties as the degradation of methylene blue (MB) by the PVA/TiO2/CPC film catalyst in 4 h was 77~90%, while the degradation of MB by the PVA/TiO2 film was 33% in 4 h, indicating that the photonic crystal structure was 2.3~2.7 times more effective than that of the bulk structure.
MALAMA: Cultivating Food Sovereignty through Backyard Aquaponics with Native Hawaiian Families
Authors: Chung-Do Jane J. , Hwang Phoebe W. , Ho-Lastimosa Ilima , Rogerson Ikaika , Ho Kenneth , DeMello Kauʻi , Kauahikaua Dwight , Ahn Hyeong Jun
Published: August 2024

Native Hawaiians were a healthy and robust population who developed a sophisticated food system that was dismantled by colonization. Currently, Native Hawaiians face pervasive health disparities due to the limited access to healthy foods and lifestyles. This study pilot tested a family-based community-driven intervention called MALAMA, which teaches families to build and use a backyard aquaponics system to grow their own food. A total of 21 participants from 10 families completed a three-month curriculum that included a series of hands-on workshops. Participant attendance was recorded and participants completed a behavioral health questionnaire as well as provided clinical indicators at three time points. They also attended a focus group at the end of the curriculum. There was a high level of engagement and no participant attrition. Fruit consumption among all participants significantly increased and there were favorable trends in blood pressure and fish and vegetable consumption. No significant differences were found in the other clinical indicators. Participants found MALAMA to be highly culturally acceptable and identified multiple benefits. Community-driven solutions, such as MALAMA, may be a promising approach to addressing pervasive health disparities and promoting health equity in minority and Indigenous communities.
Lessons of the COVID-19 Pandemic for Ambulance Service in Kazakhstan
Authors: Messova Assylzhan , Pivina Lyudmila , Ygiyeva Diana , Batenova Gulnara , Dyussupov Almas , Jamedinova Ulzhan , Syzdykbayev Marat , Adilgozhina Saltanat , Bayanbaev Arman
Published: August 2024

Background: Emergency medical services (EMS) are intended to provide people with immediate, effective, and safe access to the healthcare system. The effects of pandemics on emergency medical services (EMS) have not been studied sufficiently. The aim of this paper is to assess the frequency and structure of calls at an ambulance station in Kazakhstan during the period of 2019–2023. Methods: A retrospective analysis was conducted to estimate the incidence of emergency assistance cases from 2019 to 2023. Results: An analysis of the structure and number of ambulance calls before the pandemic, during the pandemic, and post-pandemic period did not reveal significant changes, except for calls in urgency category IV. Patients of urgency category IV handled by an ambulance decreased by 2 and 1.7 times in 2020 and 2021, respectively, which appears to be related to quarantine measures. In 2022 and 2023, category IV calls were 4.7 and 4.5 times higher than in 2019. Conclusions: This study’s findings suggest no changes in the dynamics of ambulance calls, except urgency category IV calls. The number of category IV urgent calls decreased significantly during the COVID-19 pandemic and increased in the post-pandemic period.
Enhancing Parental Understanding of Emotions in Children with Developmental Language Disorder: An Online Parent-Led Intervention Program
Authors: Durgungoz Fatma Canan , St Clair Michelle C.
Published: August 2024

Many children with developmental language disorder (DLD) have emotion recognition and regulation difficulties, but there are currently no known interventions enhancing emotional awareness in this population. This study explores the impact of parents’ perspectives regarding children with DLD emotional understanding through a parent-led online emotion recognition (ER) intervention. Ten parents of children with DLD aged 6–11 participated in the study. A nonconcurrent multiple baseline design was employed, allowing for a rigorous analysis of changes in parental beliefs over time. Weekly data were collected through the Parents’ Beliefs About Children’s Emotions Questionnaire. Interviews were also conducted to gain deeper insights into parents’ perceptions regarding the ER skills of their children. Results indicated that parents’ beliefs about the need for guiding and supporting their child’s ER skills increased over the intervention. Interviews also supported this, and three main themes were generated. The intervention program increased parents’ awareness of (a) the importance of ER for children with DLD, (b) emotion-focused communication and engagement with their child, and (c) the integration of emotions into daily life. This study is the first known study that explores parents’ beliefs about children with DLD ER skills, highlighting the importance of supporting parents through accessible interventions.
Assessment of Park Paths and Trails for Physical Activity Promotion among Older Adults in Saudi Arabia: Feasibility and Future Directions
Authors: Chippendale Tracy , Bakhsh Hadeel R. , Alhaizan Najat A. , Bin Sheeha Bodor H.
Published: August 2024

Chronic diseases affect more than 80% of older adults. One modifiable risk factor for secondary prevention is physical activity. Public parks are an essential resource for physical activity, but environmental features may limit participation. Our aims were (1) to assess the feasibility and utility of the Path Environment Audit Tool (PEAT) for use in a larger-scale study focused on older adults and (2) to examine the physical activity-promoting features of five public parks. Methods: A descriptive study design was used to assess five public parks in Riyadh, Saudi Arabia, from April to June 2022. Additionally, process, resource, and management assessments were also conducted. Results: The PEAT was easy to use, but additions are recommended to increase relevance to older adults with chronic disease. Descriptive analyses revealed positive features, such as adequate lighting, but other features such as path slope were more variable. Conclusions: Study findings can guide the future use of the PEAT for older adult participants and inform environmental modifications.
End-of-Life Care during the COVID-19 Pandemic: Decreased Hospitalization of Nursing Home Residents at the End of Life
Authors: Bárrios Helena , Nunes José Pedro Lopes , Teixeira João Paulo Araújo , Rêgo Guilhermina
Published: August 2024

(1) Background: Nursing homes (NHs) face unique challenges in end-of-life care for their residents. High rates of hospitalization at the end of life are frequent, often for preventable conditions. The increased clinical uncertainty during the pandemic, the high symptom burden of the COVID-19 disease, and the challenges in communication with families and between care teams might impact the option to hospitalize NH residents at the end of life. (2) Materials and methods: The study covered a 3-year period and compared the hospitalization rates of the NH residents of a sample of Portuguese NH during the last year of life before and during the pandemic. A total of 387 deceased residents were included in the study. (3) Results: There were fewer hospitalizations in the last year of life during the pandemic period, although the proportion of deaths at hospitals was the same. Hospitalizations occurred closer to death, and with more serious clinical states. The lower rate of hospitalization was due to lower hospitalization due to infection; (4) Conclusions: The data suggest an improvement in end-of-life care practices during the pandemic period, with the decrease in hospitalizations being due to potentially burdensome hospitalizations. The importance of the role of physicians, nurses, and caregivers in this setting may be relatively independent of each other, and each may be targeted in end-of-life care training. Further study is recommended to clarify the implications of the results and if the changes can be sustained in the long term.
AF among Nurses Working in Neonatal and Paediatric Intensive Care Units: A Cross-Sectional Study
Authors: Ali Taibah M. , Alharbi Manal F.
Published: August 2024

Aim: This research study aims to determine nurses’ alarm fatigue (AF) levels in paediatric critical care units in two governmental hospitals and to examine the significant differences in the mean between nurses’ attributes, nurses’ working environment, and nurses’ alarm management with the level of fatigue caused by the alarm. Background: In recent years, AF has become a significant and growing concern among nurses. However, in the Saudi Arabian paediatrics context, the impact of AF on nurses working in intensive care units remains unexplored. Method: A descriptive cross-sectional survey was conducted using a non-probability purposive sampling method. Data were collected from 216 nurses in two governmental hospitals through self-administered questionnaires comprised of four sections: individual attributes, work environment, alarm management, and AF scale. Data analysis: The Statistical Package of Social Science (SPSS) was used to analyse the data, and ANOVA was utilised to describe the sample’s demographic characteristics and determine any differences. Results: Most participants were female, held a bachelor’s degree, and were aged 31 to 35. Of the participants, 62.5% reported experiencing a medium level of AF, 29.2% reported a low level, and 8.3% reported a high level. Participants expressed that recurrent false alarms disrupt patient care and decrease trust in alarm systems. Significant differences in AF levels were observed based on marital status and the percentage of non-actionable alarms. Conclusions: Nurses working in paediatric critical units with high rates of false alarms, the frequent de-activation of alarms, and decreased trust in alarm systems are more likely to experience AF. Addressing AF is crucial for patient safety; nurse training on alarm management, the collaboration between biomedical and nursing staff, and technological advancements can help mitigate this issue. Implications for Practice: To minimise the adverse effects of AF, policymakers, biomedical experts, and nursing administrators must establish comprehensive policies and protocols concerning alarms. These measures aim to ensure secure and efficient care for the well-being of patients and nurses.
Anxiety in Nursing Students during the COVID-19 Pandemic: Systematic Review and Meta-Analysis
Authors: García-Rivas Aroa , Martos-Cabrera María Begoña , Membrive Jiménez María José , Aguayo-Estremera Raimundo , Suleiman Martos Nora , Albendín-García Luis , Gómez-Urquiza José L.
Published: August 2024

Objectives: To analyse the influence of the COVID-19 pandemic on the development of anxiety in nursing students and the factors involved. Design: A systematic review and meta-analysis. Data source: PubMed, CINAHL, Scopus and Web of Science. Background: Nursing students are at an increased risk of developing mental overload, due to the presence of many sources of stress during their academic training. Therefore, the COVID-19 pandemic has had an impact on the mental health of the general population, especially on healthcare workers and consequently on students undertaking placements in healthcare settings. Methods: A systematic review was conducted using PubMed, CINAHL, Scopus and Web of Science databases. A total of 24 articles were included in the review, and 20 articles were selected for the meta-analysis. Results: We found that the anxiety scores of nursing students during the COVID-19 pandemic were slightly higher (50%) than before the pandemic. The most influential risk factors for developing anxiety were academics, age, gender, having children, living in urban areas or with family, having an addiction to social networks, and having a fear of becoming infected with COVID-19. Resilience, spiritual support and feelings of happiness protected students against the risk of developing high levels of anxiety. Conclusions: The COVID-19 pandemic has led to increased levels of anxiety in nursing students. Thirty-five percent of the meta-analytically analysed sample had elevated levels of anxiety.
Promoting Anthocyanin Biosynthesis in Purple Lettuce through Sucrose Supplementation under Nitrogen Limitation
Authors: Liu Chunhui , Yu Haiye , Liu Yucheng , Zhang Lei , Li Dawei , Zhao Xiaoman , Zhang Junhe , Sui Yuanyuan
Published: August 2024

Although nitrogen deficiency and sucrose are linked to anthocyanin synthesis, the potential role of sucrose in regulating anthocyanin biosynthesis under low nitrogen conditions (LN) in purple lettuce (Lactuca sativa L.) remains unclear. We found that adding exogenous sucrose enhanced anthocyanin biosynthesis but significantly inhibited lettuce growth at high concentrations. Optimal results were obtained using 1 mmol/L sucrose in a low-nitrogen nutrient solution (LN + T1). Chlorophyll fluorescence imaging indicated that the addition of exogenous sucrose induced mild stress. Meanwhile, the activities of antioxidant enzymes (SOD, CAT, and POD) and antioxidant capacity were both enhanced. The mild stress activated the antioxidant system, thereby promoting the accumulation of anthocyanins induced by exogenous sucrose. LN + T1 (low nitrogen nutrient solution supplemented with 1 mmol/L sucrose) up-regulated enzyme genes in the biosynthetic pathway of anthocyanins, including phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), dihydroflavonol reductase (DFR), flavanone 3-hydroxylase (F3H), flavonoid 3′-hydroxylase (F3′H), flavone synthase II (FNSII), and anthocyanidin synthase (ANS). Additionally, various transcription factors such as AP2/ERF, MYB, bHLH, C2H2, NAC, C2C2, HB, MADS, bZIP, and WRKY were found to be up-regulated. This study elucidates the regulatory mechanism of anthocyanin metabolism in response to the addition of exogenous sucrose under low nitrogen conditions and provides a nutrient solution formula to enhance anthocyanin content in modern, high-quality agricultural cultivation.
Strategies to Delay Ethylene-Mediated Ripening in Climacteric Fruits: Implications for Shelf Life Extension and Postharvest Quality
Authors: Alonso-Salinas Ramiro , López-Miranda Santiago , Pérez-López Antonio José , Acosta-Motos José Ramón
Published: August 2024

Climacteric fruits undergo a characteristic ripening process regulated by ethylene, a key plant hormone. Extending the shelf life of these fruits while preserving their postharvest quality poses a significant challenge for the food industry. This review provides a comprehensive overview of physiological and molecular strategies to delay ethylene-mediated ripening in climacteric fruits and their impact on shelf life, postharvest quality, sensory attributes, and volatile compounds. Additionally, it examines the role of ethylene in fruit ripening, analysing various ethylene managing strategies including ethylene inhibitors, ethylene adsorbents, and ethylene scavengers by catalytic oxidation. This review concludes with future research directions including molecular and genetic approaches for reducing ethylene production or responsiveness in fruits, integrated strategies, environmental considerations, and commercial applications for improving postharvest handling and fruit quality.
Microbial Immobilized Enzyme Biocatalysts for Multipollutant Mitigation: Harnessing Nature’s Toolkit for Environmental Sustainability
Authors: Abdelhamid Mohamed A. A. , Khalifa Hazim O. , Yoon Hyo Jik , Ki Mi-Ran , Pack Seung Pil
Published: August 2024

The ever-increasing presence of micropollutants necessitates the development of environmentally friendly bioremediation strategies. Inspired by the remarkable versatility and potent catalytic activities of microbial enzymes, researchers are exploring their application as biocatalysts for innovative environmental cleanup solutions. Microbial enzymes offer remarkable substrate specificity, biodegradability, and the capacity to degrade a wide array of pollutants, positioning them as powerful tools for bioremediation. However, practical applications are often hindered by limitations in enzyme stability and reusability. Enzyme immobilization techniques have emerged as transformative strategies, enhancing enzyme stability and reusability by anchoring them onto inert or activated supports. These improvements lead to more efficient pollutant degradation and cost-effective bioremediation processes. This review delves into the diverse immobilization methods, showcasing their success in degrading various environmental pollutants, including pharmaceuticals, dyes, pesticides, microplastics, and industrial chemicals. By highlighting the transformative potential of microbial immobilized enzyme biocatalysts, this review underscores their significance in achieving a cleaner and more sustainable future through the mitigation of micropollutant contamination. Additionally, future research directions in areas such as enzyme engineering and machine learning hold immense promise for further broadening the capabilities and optimizing the applications of immobilized enzymes in environmental cleanup.