bluuebunny/crossref_metadata_2025 huggingface dataset:
Specialized Genetic Operators for the Planning of Passive Optical Networks
Authors: Pereira Oeber Izidoro , Carreño-Franco Edgar Manuel , López-Lezama Jesús M. , Muñoz-Galeano Nicolás
Published: October 2024

Passive Optical Networks (PONs) are telecommunication technologies that use fiber-optic cables to deliver high-speed internet and other communication services to end users. PONs split optical signals from a single fiber into multiple fibers, serving multiple homes or businesses without requiring active electronic components. PONs planning involves designing and optimizing the infrastructure for delivering fiber-optic communications to end users. The main contribution of this paper is the introduction of tailored operators within a genetic algorithm (GA) optimization approach for PONs planning. A three vector and an aggregator vector are devised to account, respectively, for physical and logical connections of the network, facilitating the execution of GA operators. This codification and these operators are versatile and can be applied to any population-based algorithm, not limited to GAs alone. Furthermore, the proposed operators are specifically designed to exploit the unique characteristics of PONs, thereby minimizing the occurrence of unfeasible solutions and accelerating convergence towards an optimal network design. By incorporating these specialized operators, this research aims to enhance the efficiency of PONs planning, ultimately leading to reduced costs and improved network performance.
Fungal Diversity Detected by ITS-5.8S from Coffea arabica Leaves Infected by Rust (Hemileia vastatrix) in Southern Ecuador
Authors: Cruz Darío , Jaramillo-Riofrío Andrea , Herrera Paulo , Aguinsaca Ruth , Chamba Marianela
Published: October 2024

Coffee production worldwide is affected by the pathogen Hemileia vastatrix, which causes the “coffee rust” disease and may be associated with other fungi. Ecuador lacks studies on fungal diversity associated with coffee rust, which could potentially control or escalate pathogen activity. Using the ITS-5.8S nrDNA region, we randomly detected a small preliminary fungi diversity related to coffee rust in Ecuador, which we report here for the first time. Ten coffee farms (four in Loja, three in Calvas, and three in Quilanga) from the Loja Province were sampled to analyze the genetic diversity of the pathogen Hemileia vastatrix in rust lesions on coffee leaves. A high number of selected sequences (Sanger sequencing) showed the presence of 48 OTUs (Operational Taxonomic Units) or “hypothetical species” of Ascomycetes and Basidiomycetes distributed across all the sampled farms. The genera Akanthomyces, Ceramothyrium, Cladosporium, Didymella, Fusarium, Mycosphaerella, Neoceratosperma, and Trichothecium of Ascomycetes, as well as Bulleribasidium, Hannaella, and Meira of Basidiomycetes, were the most abundant. To avoid taxonomic conflict, some sequences were placed into Capnodiales (Ascomycetes) and Tremelalles (Basidiomycetes) without a genus definition. A new phylogenetic group of sequences is considered Incertae Sedis from Basidiomycetes. Additionally, morphospecies of Akanthomyces (synonymous with some Lecanicillium species) and Colletotrichum were observed macroscopically and microscopically growing closely with rust. Most of the OTUs probably correspond to rust mycoparasites, as previously reported in the literature. However, this study is limited by the number of sequences analyzed phylogenetically, which may hinder the discovery of significant insights. Future studies are needed to determine whether this preliminary fungal diversity is associated with the rust fungus or corresponds to ubiquitous airborne fungi. Furthermore, research into the function of these species may reveal whether they promote rust pathogenicity or enhance plant responses by activating resistance mechanisms.
Improved Diabetic Foot Ulcer Outcomes in Medicaid Beneficiaries with Podiatric Care Access
Authors: Luu Ivan Y. , Hong Alexander T. , Lee Ashton , Arias Juan C. , Shih Chia-Ding , Armstrong David G. , Tan Tze-Woei
Published: October 2024

Objectives: This study aims to examine the association between state Medicaid coverage of podiatry services and the outcomes of beneficiaries with new diabetic foot ulcers (DFUs). Methods: Medicaid beneficiaries who developed a DFU between 2010 and 2015 were identified using the PearlDiver claims database. The states were categorized into covered states (CS) and non-covered states (NCS) based on podiatric coverage during the study period. The outcomes included major amputation, minor amputation, and hospitalization due to foot infection within 12 months of index diagnosis. Logistic regression was used to assess the association of state coverage type and outcomes, controlling for age, sex, and the Charlson Comorbidity Index (CCI). Results: Our study included 16,905 Medicaid beneficiaries who developed new DFUs: 14,748 in CS and 2157 in NCS. The overall major amputation rate was 2.6%. The risk of major amputation was 48% lower among Medicaid beneficiaries in CS (OR 0.52, 95% CI 0.31–0.90) than in NCS. The Medicaid beneficiaries in CS had a 24% lower risk of hospitalization for foot infection (OR 0.76, 95% CI 0.67–0.85) but had a 58% higher risk of minor amputation (OR 1.58, 95% CI 1.22–2.07) than in NCS. Conclusions: Medicaid coverage of podiatry services might be associated with lower rates of major amputation and reduced risk of hospitalization for foot infection.
The Diagnosis and Management of Pediatric Blunt Abdominal Trauma—A Comprehensive Review
Authors: Bašković Marko , Keretić Dorotea , Lacković Matej , Borić Krakar Marta , Pogorelić Zenon
Published: October 2024

Blunt abdominal trauma in childhood has always been full of diagnostic and therapeutic challenges that have tested the clinical and radiological skills of pediatric surgeons and radiologists. Despite the guidelines and the studies carried out so far, to this day, there is no absolute consensus on certain points of view. Around the world, a paradigm shift towards non-operative treatment of hemodynamically stable children, with low complication rates, is noticeable. Children with blunt abdominal trauma require a standardized methodology to provide the best possible care with the best possible outcomes. This comprehensive review systematizes knowledge about all aspects of caring for children with blunt abdominal trauma, from pre-hospital to post-hospital care.
Physics Guided Neural Networks with Knowledge Graph
Authors: Gupta Kishor Datta , Siddique Sunzida , George Roy , Kamal Marufa , Rifat Rakib Hossain , Haque Mohd Ariful
Published: October 2024

Over the past few decades, machine learning (ML) has demonstrated significant advancements in all areas of human existence. Machine learning and deep learning models rely heavily on data. Typically, basic machine learning (ML) and deep learning (DL) models receive input data and its matching output. Within the model, these models generate rules. In a physics-guided model, input and output rules are provided to optimize the model’s learning, hence enhancing the model’s loss optimization. The concept of the physics-guided neural network (PGNN) is becoming increasingly popular among researchers and industry professionals. It has been applied in numerous fields such as healthcare, medicine, environmental science, and control systems. This review was conducted using four specific research questions. We obtained papers from six different sources and reviewed a total of 81 papers, based on the selected keywords. In addition, we have specifically addressed the difficulties and potential advantages of the PGNN. Our intention is for this review to provide guidance for aspiring researchers seeking to obtain a deeper understanding of the PGNN.
The Power of Acceptance of Their Disability for Improving Flourishing: Preliminary Insights from Persons with Physical Acquired Disabilities
Authors: Martis Chiara , Levante Annalisa , De Carlo Elisa , Ingusci Emanuela , Signore Fulvio , Lecciso Flavia
Published: October 2024

Following Wright’s theory, the process of acceptance of disability helps persons with an acquired disability to change their attitudes toward it. Consequently, a sense of self-satisfaction was developed, a de-emphasis on disability salience was placed, and compensatory behavioral qualities were acquired. Together, these factors promote an individual’s adjustment according to disability-related strengths and difficulties. Our cross-sectional study examines how acceptance of disability influences flourishing, characterized by high well-being and low distress. Due to the exploratory nature of the study, two research questions were formulated: Would each factor of acceptance of disability positively predict each dimension of well-being? (RQ1); Would each factor of acceptance of disability negatively predict distress? (RQ2). Additionally, we considered gender effects. 107 Italian adults with acquired physical disabilities [Myear (SD) = 48.12 (14.87)] filled out an e-survey. Measures of acceptance of disability, well-being, and distress were used. The results indicate that self-satisfaction is a key predictor of flourishing while de-emphasizing disability salience only predicts purpose in life. Compensatory behavioral qualities predicted personal growth, positive relationships, life purposes, and self-acceptance. Gender did not significantly affect outcomes. Despite being preliminary, these initial results support the acceptance of disability as a personal resource for promoting flourishing. They suggest the potential for interventions to help individuals with disabilities process grief and accept their new self-representation.
Dataset Augmentation and Fractional Frequency Offset Compensation Based Radio Frequency Fingerprint Identification in Drone Communications
Authors: Li Dongming , Wang Zhaorui , Lai Yuting , Shen Huafei
Published: October 2024

The open nature of the wireless channel makes the drone communication vulnerable to adverse spoofing attacks, and the radio frequency fingerprint (RFF) identification is promising in effectively safeguarding the access security for drones. Since drones are constantly flying in the three dimensional aerial space, the unique RFF identification problem emerges in drone communication that the effective extraction and identification of RFF suffer from the time-varying channel effects and unavoidable jitterings due to the constant flight. To tackle this issue, we propose augmenting the training RFF dataset by regenerating the drone channel characteristics and compensate the fractional frequency offset. The proposed method estimates the Rician K value of the channel and curve-fits the statistical distribution, the Rician channels are regenerated using the sinusoidal superposition method. Then, a probabilistic switching channel is also set up to introduce the Rayleigh channel effects into the training dataset. The proposed method effectively addresses the unilateral channel effects in the training dataset and achieves the balanced channel effect distribution. Consequently, the pre-trained model can extract channel-robust RFF features in drone air-ground channels. In addition, by compensating the fractional frequency offset, the proposed method removes the unstable frequency components and retains the stable integer frequency offset. Then, the stable frequency offset features that are robust to environmental changes can be extracted. The proposed method achieves an average classification accuracy of 97% under spatial and temporal varying conditions.
YOLO-RWY: A Novel Runway Detection Model for Vision-Based Autonomous Landing of Fixed-Wing Unmanned Aerial Vehicles
Authors: Li Ye , Xia Yu , Zheng Guangji , Guo Xiaoyang , Li Qingfeng
Published: October 2024

In scenarios where global navigation satellite systems (GNSSs) and radio navigation systems are denied, vision-based autonomous landing (VAL) for fixed-wing unmanned aerial vehicles (UAVs) becomes essential. Accurate and real-time runway detection in VAL is vital for providing precise positional and orientational guidance. However, existing research faces significant challenges, including insufficient accuracy, inadequate real-time performance, poor robustness, and high susceptibility to disturbances. To address these challenges, this paper introduces a novel single-stage, anchor-free, and decoupled vision-based runway detection framework, referred to as YOLO-RWY. First, an enhanced data augmentation (EDA) module is incorporated to perform various augmentations, enriching image diversity, and introducing perturbations that improve generalization and safety. Second, a large separable kernel attention (LSKA) module is integrated into the backbone structure to provide a lightweight attention mechanism with a broad receptive field, enhancing feature representation. Third, the neck structure is reorganized as a bidirectional feature pyramid network (BiFPN) module with skip connections and attention allocation, enabling efficient multi-scale and across-stage feature fusion. Finally, the regression loss and task-aligned learning (TAL) assigner are optimized using efficient intersection over union (EIoU) to improve localization evaluation, resulting in faster and more accurate convergence. Comprehensive experiments demonstrate that YOLO-RWY achieves AP50:95 scores of 0.760, 0.611, and 0.413 on synthetic, real nominal, and real edge test sets of the landing approach runway detection (LARD) dataset, respectively. Deployment experiments on an edge device show that YOLO-RWY achieves an inference speed of 154.4 FPS under FP32 quantization with an image size of 640. The results indicate that the proposed YOLO-RWY model possesses strong generalization and real-time capabilities, enabling accurate runway detection in complex and challenging visual environments, and providing support for the onboard VAL systems of fixed-wing UAVs.
A More-than-Human Ecology: Evolving Generative Artificial Intelligence in Higher Education
Authors: Fern James
Published: October 2024

The significant improvements in generative artificial intelligence (GenAI) observed in recent years present higher education with both an opportunity and a significant challenge. Its successful integration will require careful planning and sound pedagogical underpinnings, both in regard to learning and teaching as well as assessment and feedback. Drawing upon theories from the more-than-human world, as well as concepts such as originality, equality, and sustainability, it is possible to develop a dialogue around GenAI that places the students’ learning journey at the heart of the discussion.
Buddychecking, a Way to Enhance Student Participation in Bioscience Project-Based Learning
Authors: Wood David , Pranjol Md Zahidul Islam
Published: October 2024

Project-based learning (PBL) is a widely used active learning approach in science, technology, engineering and mathematics (STEM) education, but concerns about unequal participation in group work can arise. To address this, we incorporated peer evaluation via the Buddycheck tool into a summative PBL assessment. In this study, students worked in small groups to create and present posters, with Buddycheck enabling them to evaluate each other’s contributions. This peer evaluation process generated an adjustment factor, which was applied to the final group mark to assign individual grades based on performance. Students reported that the peer evaluation promoted fairness in grading and increased their accountability, leading to higher engagement in group activities. They also found the exercise valuable for consolidating their knowledge and improving communication skills. Overall, the use of Buddycheck in PBL was well received, with students expressing greater satisfaction and a sense of equity in the grading process. The tool not only improved learning outcomes but also contributed to better group dynamics and an overall improvement in final grades.
The Role of Family in the Life Satisfaction of Young Adults: An Ecological-Systemic Perspective
Authors: Morales Almeida Paula , Brás Marta , Nunes Cristina , Martins Cátia
Published: October 2024

The support provided by parents plays a relevant role in the life satisfaction (LS) of young people, as well as in their level of psychological distress (PD), which are among the important mediators of their well-being. Family structure has also been identified as a protective or risk factor. Hence, the present study provides a more complex analysis of young people’s LS, considering the type of family cohabitation (based on parental presence), the personal conditions of the young people (PS), and their perception of the context (social support; SP). A cross-sectional design was used, and 557 young people, with a mean age of 20.68 (SD = 2.23), 50.8% women, 60.7% students, participated. Their levels of psychological distress, perceived social support, life satisfaction, and parental cohabitation were assessed. A mediation and a moderated-mediation model were used. Young people living in a biparental family reveal higher levels of LS and lower levels of PS. A partial mediation was found in the effect of SP on the relation between PS and LS. The moderated-mediation model tested showed that the indirect effects on the paths PS–SP and SP–LS were not significant by the type of parental family cohabitation. Several implications regarding family structure on young people’s LS are discussed.
Modeling, System Identification, and Control of a Railway Running Gear with Independently Rotating Wheels on a Scaled Test Rig
Authors: Posielek Tobias
Published: October 2024

The development and validation of lateral control strategies for railway running gears with independently rotating driven wheels (IRDWs) are an active research area due to their potential to enhance straight-track centering, curve steering performance, and reduce noise and wheel–rail wear. This paper focuses on the practical application of theoretical models to a 1:5 scaled test rig developed by the German Aerospace Center (DLR), addressing the challenges posed by unmodeled phenomena such as hysteresis, varying damping and parameter identification. The theoretical model from prior work is adapted based on empirical measurements from the test rig, incorporating the varying open-loop stability of the front and rear wheel carriers, hysteresis effects, and other dynamic properties typically neglected in literature. A transparent procedure for identifying dynamic parameters is developed, validated through closed- and open-loop measurements. The refined model informs the design and tuning of a cascaded PI and PD controller, enhancing system stabilization by compensating for hysteresis and damping variations. The proposed approach demonstrates improved robustness and performance in controlling the lateral displacement of IRDWs, contributing to the advancement of safety-critical railway technologies.
Research on Electric Hydrogen Hybrid Storage Operation Strategy for Wind Power Fluctuation Suppression
Authors: Li Dongsen , Qian Kang , Gao Ciwei , Xu Yiyue , Xing Qiang , Wang Zhangfan
Published: October 2024

Due to real-time fluctuations in wind farm output, large-scale renewable energy (RE) generation poses significant challenges to power system stability. To address this issue, this paper proposes a deep reinforcement learning (DRL)-based electric hydrogen hybrid storage (EHHS) strategy to mitigate wind power fluctuations (WPFs). First, a wavelet packet power decomposition algorithm based on variable frequency entropy improvement is proposed. This algorithm characterizes the energy characteristics of the original wind power in different frequency bands. Second, to minimize WPF and the comprehensive operating cost of EHHS, an optimization model for suppressing wind power in the integrated power and hydrogen system (IPHS) is constructed. Next, considering the real-time and stochastic characteristics of wind power, the wind power smoothing model is transformed into a Markov decision process. A modified proximal policy optimization (MPPO) based on wind power deviation is proposed for training and solving. Based on the DRL agent’s real-time perception of wind power energy characteristics and the IPHS operation status, a WPF smoothing strategy is formulated. Finally, a numerical analysis based on a specific wind farm is conducted. The simulation results based on MATLAB R2021b show that the proposed strategy effectively suppresses WPF and demonstrates excellent convergence stability. The comprehensive performance of the MPPO is improved by 21.25% compared with the proximal policy optimization (PPO) and 42.52% compared with MPPO.
Optimizing Energy Efficiency in a Peltier-Module-Based Cooling Microunit through Selected Control Algorithms
Authors: Lis Stanisław , Knaga Jarosław , Kurpaska Sławomir , Famielec Stanisław , Łyszczarz Piotr , Machaczka Marek
Published: October 2024

This research covers the process of heat exchange in a cooling microunit equipped with Peltier modules. We put forward that by choosing the control algorithm, not only the control signal quality in such a system is affected but also its energy consumption. Tests were carried out for the following algorithms: relay, parallel PID, serial PID, and PID + DD. An experimental setup was developed that allowed for recording the step response of the investigated plant. Next, the transfer function of the plant was formulated, and a simulation model of the control system was developed using the MatLab®-Simulink environment. Through computer simulation for a selected system operation procedure (cooling down to three set temperatures and maintaining them for 5000 s), the quality of control signals and the influence on energy use were investigated. The cumulative energy value for each of the algorithms and the cumulative difference in energy consumption between the controllers were calculated. The best results in terms of control quality were obtained for the parallel PID controller. The lowest energy consumption was observed for the relay controller, with the difference compared to other investigated controllers reaching 4.3% and 9.0%, without and with the presence of signal disturbances, respectively.
Preparation and Performance Study of CaCl2 Composite Adsorbent Based on Rock Wool Board Suitable for Continuous Heat Storage/Release of Trombe Wall
Authors: Xiao Yutong , Wei Siyu , Yang Yuanyi , Wang Chunhao , Peng Shanbi
Published: October 2024

As a passive solar design technology, the Trombe wall can improve buildings’ energy efficiency and thermal comfort. However, the traditional Trombe wall heating efficiency is low and cannot meet the needs of continuous night heating of the building. To solve these problems, a new type of sheet-like composite adsorbent is proposed in this study, prepared from calcium chloride supported by a rock wool board, a high-porosity building material. The high adaptability of rock wool board to the building wall makes it possible for the composite adsorbent to be directly applied to the Trombe wall. The results show that the macroporous structure of the rock wool board provides a wealth of space for loading hydrated salts. The smaller the density and thickness, the more calcium chloride the rock wool board can carry, speeding up the absorption/deportation process. The rock wool slab-based calcium chloride composite adsorbent has a maximum adsorption capacity of 51% and a heat storage density of about 838 J/g. Achieving the desorbed balance within 8 h and applying it to the Trombe wall is expected to attain continuous heating of buildings and has significant potential in building energy conservation.
Enhancing PV Hosting Capacity of Electricity Distribution Networks Using Deep Reinforcement Learning-Based Coordinated Voltage Control
Authors: Suchithra Jude , Rajabi Amin , Robinson Duane A.
Published: October 2024

Coordinated voltage control enables the active management of voltage levels throughout electricity distribution networks by leveraging the voltage support capabilities of existing grid-connected PV inverters. The efficient management of power flows and precise voltage regulation through coordinated voltage control schemes facilitate the increased adoption of rooftop PV systems and enhance the hosting capacity of electricity distribution networks. The research work presented in this paper proposes a coordinated voltage control scheme and evaluates the enhanced hosting capacity utilizing a deep reinforcement learning-based approach. A comparative analysis of the proposed algorithm is presented, and the performance is benchmarked against existing local voltage control schemes. The proposed coordinated voltage control scheme in this paper is evaluated using simulations on a real-world low-voltage electricity distribution network. The evaluation involves quasi-static time series power flow simulations for assessing performance. Furthermore, a discussion is presented that reflects on the strengths and limitations of the proposed scheme based on the results observed from the case study.
The Bidirectional Link between Major Depressive Disorder and Type 2 Diabetes: The Role of Inflammation
Authors: Bodnaruc Alexandra M. , Roberge Mathilde , Giroux Isabelle , Aguer Céline
Published: October 2024

Background/Objectives: There is a bidirectional relationship between major depressive disorder (MDD) and type 2 diabetes (T2D), as MDD increases the risk of T2D by 38% to 67%, and T2D increases the risk of MDD by 15% to 33%. Many factors contribute to the occurrence of comorbid MDD and T2D, including converging pathophysiological pathways like inflammation. The objective of this review was to comprehensively summarize available evidence on the relationship between MDD, T2D, and inflammation. Results: Although the precise mechanisms linking T2D and MDD are still not fully understood, shared inflammatory mechanisms likely contributes to the heightened risk of developing this comorbidity. To date, the evidence supports that chronic low-grade inflammation is a feature of both MDD and T2D and has been shown to interact with pathways that are relevant to the development of both chronic disorders, including the hypothalamic–pituitary–adrenal (HPA) axis, neuroplastic processes, gut microbiome, insulin resistance, and adipose tissue dysfunction. Through their impact on inflammation, dietary and physical activity interventions can play a role in the risk and management of MDD and T2D. Conclusions: Deepening our understanding of the mechanisms underlying the augmented inflammatory responses observed in individuals with the MDD and T2D comorbidity is essential for tailoring appropriate therapeutic strategies.
Bio-Power Generation in Microbial Fuel Cell with Vermicompost Using Eisenia foetida
Authors: Solares Basurto Adriana , Pérez Ruiz Mateo , Luján Vega María Angélica , Olivares-Ramírez Juan Manuel , Vera-Estrada Irma Lucía , González-Duran José Eli Eduardo , Rodríguez Reséndiz Juvenal
Published: October 2024

This research emphasizes the effect of using Eisenia foetida in vermicompost for power generation in microbial fuel cells (MFCs). By accelerating the organic decomposition, the bioenergy generation is improved. A vermicompost-microbial fuel cell employing electrogenic microorganisms was used to convert chemical energy into electrical energy. In this work, substrates of black soil, tree bark, leaves, eggshells, and ground tomatoes were used. The vermicompost MFC has a copper cathode and a stainless steel anode. In this study, the performance of MFCs was evaluated using different numbers of Eisenia foetida specimens, with three specimens (MFCW3), five specimens (MFCW5), and seven specimens (MFCW7). Our key findings show that by increasing the number of Eisenia foetida specimens does not bring higher power densities; as a result, the best power density was observed in MFCW3 and MFCW5 at the end of the fourth week, both presenting a total of five Eisenia foetida specimens with a power density of 192 mW m−2. Therefore, optimal results were found when 330 g of substrate and five Eisenia foetida specimens were used to achieve a maximum current density of 900 mW m−2 and a maximum power density of 192 mW m−2. This type of microbial fuel cell can be considered as an alternative for power generation with a significantly reduced environmental impact, considering the use of organic waste. It can be considered a game-changer in waste management and bioenergy projects.
Resilience, Anger, and Insomnia in Nurses after the End of the Pandemic Crisis
Authors: Pachi Argyro , Panagiotou Aspasia , Soultanis Nikolaos , Ivanidou Maria , Manta Maria , Sikaras Christos , Ilias Ioannis , Tselebis Athanasios
Published: October 2024

Introduction: Nurses seem to be persistently experiencing intense psychological repercussions, even after the official conclusion of the COVID-19 pandemic. In this cross-sectional study conducted after the end of the pandemic crisis, from 1 June 2023 to 30 June 2023, we evaluated the levels and explored the associations between anger, insomnia, and resilience among Greek nurses. Methods: A total of 441 nurses participated in an online survey and were invited to state their work experience, gender, and age and to complete the self-report measures of the Dimensions of Anger Reactions-5 (DAR-5), the Athens Insomnia Scale (AIS), and the Brief Resilience Scale (BRS). Results: Overall, 62.1% of the participants presented with positive scores on the AIS, and 41.5% displayed positive values on the DAR-5 scale, whereas 24.9% demonstrated scores indicative of low resilience on the BRS. A regression analysis revealed that 23.5% of the variance in the AIS scores can be attributed to the DAR-5 scores and 3% to the BRS scores. A mediation analysis confirmed the protective role of resilience, contributing as a negative mediator in the DAR-5 and AIS relationship. Conclusions: Screening for insomnia symptoms and anger issues among nurses after the end of the pandemic and implementing appropriate interventions is considered imperative to avoid long-term health consequences.
Dead Fuel Moisture Content Reanalysis Dataset for California (2000–2020)
Authors: Farguell Angel , Drucker Jack Ryan , Mirocha Jeffrey , Cameron-Smith Philip , Kochanski Adam Krzysztof
Published: October 2024

This study presents a novel reanalysis dataset of dead fuel moisture content (DFMC) across California from 2000 to 2020 at a 2 km resolution. Utilizing a data assimilation system that integrates a simplified time-lag fuel moisture model with 10-h fuel moisture observations from remote automated weather stations (RAWS) allowed predictions of 10-h fuel moisture content by our method with a mean absolute error of 0.03 g/g compared to the widely used Nelson model, with a mean absolute error prediction of 0.05 g/g. For context, the values of DFMC in California are commonly between 0.05 g/g and 0.30 g/g. The presented product provides gridded hourly moisture estimates for 1-h, 10-h, 100-h, and 1000-h fuels, essential for analyzing historical fire activity and understanding climatological trends. The methodology presented here demonstrates significant advancements in the accuracy and robustness of fuel moisture estimates, which are critical for fire forecasting and management.
Experimental Study on the Influence of Staged Oxygen Consumption on the Oxidation Characteristics of Coal Spontaneous Combustion
Authors: Guo Jun , Wang Lei , Liu Yin , Chen Changming , Cai Guobin , Du Wentao
Published: October 2024

The oxidation characteristic parameters of residual coal in working face change with the advance of coal seam. To explore the influence of dynamic oxygen-consuming environments, we examined the influence of reducing the oxygen concentration on the formation characteristics and characteristic parameters of coal oxidation products, conducted with temperature-programmed experiments under staged oxygen consumption. The correlation between the characteristic oxidation parameters was determined, and the critical oxygen concentration that determined the gas yield was obtained. The results show that after staged oxygen-consumption, the oxidation of coal is stronger than that under constant low oxygen, the oxidation products are greatly affected, and the influence of pyrolysis gas is small. The oxidation characteristic parameters such as gas product volume fraction, production rate, and heat release intensity are positively correlated with the oxygen-consumed temperature. We found that the oxidation reaction heat of coal is 180~330 kJ·mol−1, and the maximum and minimum exothermic intensities are significantly linearly correlated with the oxygen consumption rate. Finally, the critical oxygen concentrations for gas production rate under oxygen-consumed conditions were 17, 9, and 5%. These results have practical significance for strengthening the prevention and control of spontaneous combustion disasters in goafs.
Experimental Study on the Effect of Sealing Time on Combustion State of the Fuel-Ventilation Controlled Wood Crib
Authors: Xu Zuohui , Wang Haiyan , Hu Jiaying , Chen Lei , Lu Sentao , Tang Simin
Published: October 2024

A tunnel fire may gradually change from a fuel-controlled fire to a ventilation-controlled fire during the sealing process, so it is of great significance to study the influence of sealing time on the combustion state for safety control. In this study, an unsealed wood-crib fire test was first carried out using a reduced-scale tunnel model. When the wind velocity is 0.10 m/s, the wood crib is fuel-controlled. Based on this, the combustion state of a wood-crib fire was studied experimentally when the sealing time was 1 min, 3 min, 7 min, and 10 min. The results showed that after sealing, the flame orientation is approximately vertical, and as the sealing time increases, the carbonization of the wood crib becomes more pronounced. The ratio of XCO/XCO2 exceeds 0.057 1 min after sealing, and the wood-crib fire becomes ventilation-controlled. When the sealing time is 7 min and 10 min, the increase rate of XCO/XCO2 is faster than when the sealing time is 1 min and 3 min. The earlier the initial sealing time, the better the fire can be suppressed. During the sealing process, the temperature on the downwind side of the fire source decreases exponentially. This study aims to provide a reference for the application of sealing technology in tunnel fires.
A Numerical Analysis of Premixed Hydrogen–Methane Flame with Three Different Header Types of Combustor
Authors: Lee Jaeyoung , Sohn Chang Bum , Jeong Young Sik , Kim Young Bae
Published: October 2024

This study investigated the impact of thin-flame combustor design on hydrogen flame characteristics and combustion performance through numerical simulations. Differences in the flame shape and combustibility between pure methane and pure hydrogen combustion were analyzed. Three combustor header shapes (flat, concave, and convex) were modeled to assess the influence of header shape on flame behavior. The results revealed distinct flow patterns, with the concave header promoting strong central flows and the convex header dispersing the flow outward. Temperature field analysis indicated that the hydrogen flames had higher temperatures and shorter quenching distances than the methane flames. A comparative analysis of combustion products was conducted to evaluate combustion performance and NOx emissions. The findings showed that the concave header had a high combustibility, with hydrogen combustion producing greater temperatures and NOx fractions than methane combustion.
Simultaneous Detection of Eight Dairy-Derived Components Using Double-Tube Multiplex qPCR Based TaqMan Probe
Authors: Su Yingying , Meng Lu , Wang Jiaqi , Zhao Yankun , Zheng Nan
Published: October 2024

The authentication of milk and dairy products has great significance for food fraud. The present investigation entailed the development of a novel method that amalgamates the double-tube approach with multiplex real-time polymerase chain reaction (PCR) technology, incorporating TaqMan probes, to facilitate the high-throughput screening and detection of animal-derived constituents within milk and dairy products. Eight dairy-derived animal-specific primers and probes were designed for the mitochondrial cytochrome b (Cytb) gene of eight dairy products, including cow, buffalo, yak, goat, sheep, horse, donkey, and camel. Through the developed double-tube detection assays, the above eight targets could be simultaneously identified with a detection limit of 0.00128–0.0064 ng/μL. The multiplex qPCR assay was effectively validated using simulated adulterated samples with different mixing ratios and demonstrated a detection limit of 0.1%. Upon analysis of 54 commercially available dairy products, a mislabeling rate of 33% was revealed. This method affords an efficacious means of detecting dairy product ingredients, thereby offering robust technical backing for market oversight and regulatory enforcement of milk and dairy products.
Is a Meta-Analysis of Clinical Trial Outcomes for Ketogenic Diets Justifiable? A Critical Assessment Based on Systematic Research
Authors: Hunter Nicole , Czina László , Murányi Edit , Németh Balázs , Varjas Tímea , Szendi Katalin
Published: October 2024

While the macronutrient content of a ketogenic diet specifically utilized for childhood epilepsy is clearly defined in the literature, variations among other ketogenic diets exhibit substantial heterogeneity. Furthermore, studies utilizing ketogenic diets contain several confounders with notable impacts on outcomes, thereby rendering both their findings and those of the meta-analyses less reliable. The objective of this meta-epidemiological assessment was to scrutinize existing clinical trials that investigated the effects of ketogenic diets on patients with obesity and diabetes, thereby determining the feasibility of conducting a meta-analysis. The Ovid Medline, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), and Embase databases were searched from 1946 to 24 September 2024. Of the studies reviewed, none met the predefined inclusion criteria. However, seven articles met these criteria very closely. In the future, studies investigating the effects of ketogenic diets containing significant confounding factors should adopt a single definition of a ketogenic diet. Additionally, accurate measurement of actual macronutrient and caloric intake, along with regularly monitored nutritional ketosis, will be essential to highlight the true effects of a ketogenic diet.
Valorization of Strawberry Juice Production Wastewater: Possibilities for Polyphenols Recovery and Plant Biostimulant Production
Authors: Danilov Ivana , Vlajkov Vanja , Šumić Zdravko , Milić Anita , Horecki Aleksandra Tepić , Dujković Tatjana , Živanović Nemanja , Simin Nataša , Lesjak Marija , Grahovac Jovana
Published: October 2024

Fruit juice production is one of the most important branches of the food and beverage industry, considering both the market size and demand. It is also one of the largest generators of industrial wastewater, considering the large consumption of fresh water during fruit processing. Hence, the appropriate treatment strategies are of the utmost importance to minimize the environmental footprint of food industry effluents. This study aimed to investigate the valorization routes for strawberry juice production wastewater (SJPW), both in terms of nutrient recovery and a circular approach to its utilization as a medium for plant biostimulant production. The results show a low antioxidant capacity and low content of polyphenols in SJPW; however, promising results were obtained for the in vitro seed germination and tomato growth promotion when investigating a biostimulant based on Bacillus sp. BioSol021, which was cultivated using SJPW in a lab-scale bioreactor, with root and shoot length improvements of approximately 30% and 25%, respectively, compared to the control samples. The plant growth promotion (PGP) traits indicated the ability of IAA production, in a concentration of 8.55 ± 0.05 mg/L, and the enzymatic activity was evaluated as through the enzymatic activity index (EAI), achieving the following: 2.26 ± 0.04 for cellulolytic activity, 2.49 ± 0.08 for hemicellulolytic activity, 2.91 ± 0.16 for pectinolytic activity, and 1.05 ± 0.00 for proteolytic activity. This study opens a new chapter of possibilities for the development of techno-economically viable circular bioprocess solutions aimed at obtaining value-added microbial products for sustainable agriculture based on the valorization of food industry effluents thus contributing to more sustainable food production at both the agricultural and industrial levels.
Exploring Cerebrospinal Fluid: Validation of a New Method for Quantification of 39 Drugs of Abuse by LC-MS/MS
Authors: Dimitrova Alexandra , Croce Emma Beatrice , Iaquinta Gaia , Ferri Elisa , Faccioli Simone , Chiavacci Giulia , Gualco Barbara , Focardi Martina , Grassi Simone , Vaiano Fabio
Published: October 2024

The use of cerebrospinal fluid (CSF) in post-mortem (PM) toxicological analysis is an under-addressed topic, likely due to the technical complexity of the collection of a proper sample. However, it is a matrix of significant interest since it has similar chemical and physical properties to the blood and it is less exposed to risks like PM redistribution and diffusion due to its anatomical location. This study aimed to validate a sensitive analytical method for the quantification of drugs of abuse and their metabolites (i.e., cocaine, ketamine, amphetamine, MDPV, 6-monoacetylmorphine, morphine, codeine, and methadone) through liquid chromatography–tandem mass spectrometry (LC-MS/MS). CSF was collected through ventricular puncture, and 200 µL was deproteinated with acetonitrile (600 µL). Quantification was carried out, acquiring two MRM transitions for each compound in positive ionization mode. Chromatographic separation was achieved with a C18 column. Limits of quantification ranged from 0.05 to 5 ng/mL. Bias and precision were always within the acceptance criteria. Ion enhancement and suppression effects were observed depending on the substance. The method validated here was applied to a real case, proving to be suitable for PM analysis. CSF and blood were positive for methadone (460 vs. 280 ng/mL), cocaine (125 vs. 69 ng/mL), benzoylecgonine (4640 vs. 3160 ng/mL), and lorazepam (19 vs. 25 ng/mL). In the future, this will be useful for the evaluation of CSF as a valuable alternative matrix in PM investigations.
Formation of Optical Fractals by Chaotic Solitons in Coupled Nonlinear Helmholtz Equations
Authors: Al-Sawalha M. Mossa , Noor Saima , Alqudah Mohammad , Aldhabani Musaad S. , Shah Rasool
Published: October 2024

In the present research work, we construct and examine the self-similarity of optical solitons by employing the Riccati Modified Extended Simple Equation Method (RMESEM) within the framework of non-integrable Coupled Nonlinear Helmholtz Equations (CNHEs). This system models the transmission of optical solitons and coupled wave packets in nonlinear optical fibers and describes transverse effects in nonlinear fiber optics. Initially, a complex transformation is used to convert the model into a single Nonlinear Ordinary Differential Equation (NODE), from which hyperbolic, exponential, rational, trigonometric, and rational hyperbolic solutions are produced. In order to better understand the physical dynamics, we offer several 3D, contour, and 2D illustrations for the independent selections of physical parameter values. These illustrations highlight the graphic behaviour of some optical solitons and demonstrate that, under certain constraint conditions, acquired optical solitons lose their stability when they approach an axis and display periodic-axial perturbations, which lead to the generation of optical fractals. As a framework, the generated optical solitons have several useful applications in the field of telecommunications. Furthermore, our suggested RMESEM demonstrates its use by broadening the spectrum of optical soliton solutions, offering important insights into the dynamics of the CNHEs, and suggesting possible applications in the management of nonlinear models.
AI Applications in Transportation and Equity: A Survey of U.S. Transportation Professionals
Authors: Sanchez Thomas W. , Qian Yiheng , Yan Xiang
Published: October 2024

This paper reports on a study investigating transportation professionals’ perceptions of AI’s equity impacts in the transportation sector, focusing on demographic variations in views. A survey conducted among U.S. transportation professionals examined their attitudes toward AI’s potential to influence transportation equity and ethics. The findings reveal insights based on gender, employment sector, educational background, and AI knowledge level, with notable differences in confidence towards AI’s ability to reduce bias and engage communities. This research highlights a commonly held opinion that there is a limited understanding of AI ethics within the transportation community, emphasizing the need for ongoing education and adaptation to AI technologies. This study contributes valuable perspectives to the discourse on AI, equity, and ethics in transportation, offering a foundation for future policy and strategy development.
An Overview of Microorganisms Immobilized in a Gel Structure for the Production of Precursors, Antibiotics, and Valuable Products
Authors: Berillo Dmitriy , Malika Turganova , Baimakhanova Baiken B. , Sadanov Amankeldi K. , Berezin Vladimir E. , Trenozhnikova Lyudmila P. , Baimakhanova Gul B. , Amangeldi Alma A. , Kerimzhanova Bakhytzhan
Published: October 2024

Using free microorganisms for industrial processes has some limitations, such as the extensive consumption of substrates for growth, significant sensitivity to the microenvironment, and the necessity of separation from the product and, therefore, the cyclic process. It is widely acknowledged that confining or immobilizing cells in a matrix or support structure enhances enzyme stability, facilitates recycling, enhances rheological resilience, lowers bioprocess costs, and serves as a fundamental prerequisite for large-scale applications. This report summarizes the various cell immobilization methods, including several synthetic (polyvinylalcohol, polyethylenimine, polyacrylates, and Eudragit) and natural (gelatin, chitosan, alginate, cellulose, agar–agar, carboxymethylcellulose, and other polysaccharides) polymeric materials in the form of thin films, hydrogels, and cryogels. Advancements in the production of well-known antibiotics like penicillin and cephalosporin by various strains were discussed. Additionally, we highlighted cutting-edge research related to strain producers of peptide-based antibiotics (polymyxin B, Subtilin, Tyrothricin, varigomycin, gramicidin S, friulimicin, and bacteriocin), glusoseamines, and polyene derivatives. Crosslinking agents, especially covalent linkers, significantly affect the activity and stability of biocatalysts (penicillin G acylase, penicillinase, deacetoxycephalosporinase, L-asparaginase, β-glucosidase, Xylanase, and urease). The molecular weight of polymers is an important parameter influencing oxygen and nutrient diffusion, the kinetics of hydrogel formation, rigidity, rheology, elastic moduli, and other mechanical properties crucial for long-term utilization. A comparison of stability and enzymatic activity between immobilized enzymes and their free native counterparts was explored. The discussion was not limited to recent advancements in the biopharmaceutical field, such as microorganism or enzyme immobilization, but also extended to methods used in sensor and biosensor applications. In this study, we present data on the advantages of cell and enzyme immobilization over microorganism (bacteria and fungi) suspension states to produce various bioproducts and metabolites—such as antibiotics, enzymes, and precursors—and determine the efficiency of immobilization processes and the optimal conditions and process parameters to maximize the yield of the target products.