bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving Drug Safety in Pediatric and Young Adult Patients with Hemato-Oncological Diseases: A Prospective Study of Active Pharmacovigilance
Authors: Parzianello Anna , Fornasier Giulia , Kiren Valentina , Pigato Federico , Orzetti Sabrina , Zamagni Giulia , Arbo Anna , Baldo Paolo , Rossi Paola , Rabusin Marco , Mascarin Maurizio , Trojniak Marta Paulina
Published: January 2024

The acquisition of relevant pediatric clinical safety data is essential to ensure tolerable drug therapies. Comparing the real number of Adverse Drug Reaction (ADR) reports in clinical practice with the literature, the idea of ADR underreporting emerges. An active pharmacovigilance observational prospective study was conducted to assess the safety of oncology pharmacological prescriptions in patients aged 0–24 years at Institute for Maternal and Child Health IRCCS Burlo Garofolo in Trieste and IRCCS CRO National Cancer Institute in Aviano (Italy) between January 2021 and October 2023. Prescriptions and ADRs were evaluated by a multidisciplinary team. A total of 1218 prescriptions for 38 patients were analyzed, and 190 ADRs of grade 3–5 were collected. As compared to historical data, we registered a significant increase (p < 0.001) in the number of ADRs. The risk of ADR was 3.4 times higher in the case of off-label prescriptions compared to on-label ones (OR 3.4; [1.47; 7.89]; p-value = 0.004). The risks of error and near-miss were reported for 6.3% and 18.2% of total prescriptions, respectively. Of the total of 133 interactions, 47 (35.3%) resulted in ADRs. This study shows the importance of pro-active pharmacovigilance to efficiently highlight ADRs, and the fundamental role of multidisciplinary teams (oncologist, pharmacist, pharmacologist, pediatrician, nurse) in improving patients’ safety during therapy.
Chrysin Directing an Enhanced Solubility through the Formation of a Supramolecular Cyclodextrin–Calixarene Drug Delivery System: A Potential Strategy in Antifibrotic Diabetes Therapeutics
Authors: Hermenean Anca , Dossi Eleftheria , Hamilton Alex , Trotta Maria Consiglia , Russo Marina , Lepre Caterina Claudia , Sajtos Csilla , Rusznyák Ágnes , Váradi Judit , Bácskay Ildikó , Budai István , D’Amico Michele , Fenyvesi Ferenc
Published: January 2024

Calixarene 0118 (OTX008) and chrysin (CHR) are promising molecules for the treatment of fibrosis and diabetes complications but require an effective delivery system to overcome their low solubility and bioavailability. Sulfobutylated β-cyclodextrin (SBECD) was evaluated for its ability to increase the solubility of CHR by forming a ternary complex with OTX008. The resulting increase in solubility and the mechanisms of complex formation were identified through phase-solubility studies, while dynamic light-scattering assessed the molecular associations within the CHR-OTX008-SBECD system. Nuclear magnetic resonance, differential scanning calorimetry, and computational studies elucidated the interactions at the molecular level, and cellular assays confirmed the system’s biocompatibility. Combining SBECD with OTX008 enhances CHR solubility more than using SBECD alone by forming water-soluble molecular associates in a ternary complex. This aids in the solubilization and delivery of CHR and OTX008. Structural investigations revealed non-covalent interactions essential to complex formation, which showed no cytotoxicity in hyperglycemic in vitro conditions. A new ternary complex has been formulated to deliver promising antifibrotic agents for diabetic complications, featuring OTX008 as a key structural and pharmacological component.
An Evaluation of the Wear Resistance of Electroplated Nickel Coatings Composited with 2,2,6,6-Tetramethylpiperidine 1-oxyl-Oxidized Cellulose Nanofibers
Authors: Iioka Makoto , Kawanabe Wataru , Tsujimura Subaru , Kobayashi Tatsuya , Shohji Ikuo
Published: January 2024

In this study, the wear resistance of nickel (Ni)–cellulose nanofiber (CNF) composite electroplated films on steel plates (JIS SPCC, cold-rolled steel) was evaluated, including their surface and microstructural properties. In the CNF sample, 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO)-oxidized CNF was used. As a result of the ball-on-disk abrasion test, in which steel (SUJ2) balls were used as the counterpart material, the plated film obtained with the addition of 1 g/L of CNF to the plating solution showed the highest wear resistance in this study. Compared to the conventional Ni-plated film without CNF, the abrasion loss volume on the plated side was reduced by approximately 79%, and that on the ball side was reduced remarkably by 94%. A microstructural analysis of the abrasion scars showed areas where co-deposited CNFs were stretched in the direction of abrasion, suggesting that the wear reduction effect was caused by sliding between the individual CNFs within the aggregates. Moreover, the hardness of the plated film increased when the Ni crystallite size became finer. It was confirmed that the co-deposition of fine CNFs is effective in improving hardness, whereas the co-deposition of a certain degree of aggregated CNFs is effective in exhibiting the wear reduction effect.
The Improved U-STFM: A Deep Learning-Based Nonlinear Spatial-Temporal Fusion Model for Land Surface Temperature Downscaling
Authors: Guo Shanxin , Li Min , Li Yuanqing , Chen Jinsong , Zhang Hankui K. , Sun Luyi , Wang Jingwen , Wang Ruxin , Yang Yan
Published: January 2024

The thermal band of a satellite platform enables the measurement of land surface temperature (LST), which captures the spatial-temporal distribution of energy exchange between the Earth and the atmosphere. LST plays a critical role in simulation models, enhancing our understanding of physical and biochemical processes in nature. However, the limitations in swath width and orbit altitude prevent a single sensor from providing LST data with both high spatial and high temporal resolution. To tackle this challenge, the unmixing-based spatiotemporal fusion model (STFM) offers a promising solution by integrating data from multiple sensors. In these models, the surface reflectance is decomposed from coarse pixels to fine pixels using the linear unmixing function combined with fractional coverage. However, when downsizing LST through STFM, the linear mixing hypothesis fails to adequately represent the nonlinear energy mixing process of LST. Additionally, the original weighting function is sensitive to noise, leading to unreliable predictions of the final LST due to small errors in the unmixing function. To overcome these issues, we selected the U-STFM as the baseline model and introduced an updated version called the nonlinear U-STFM. This new model incorporates two deep learning components: the Dynamic Net (DyNet) and the Chang Ratio Net (RatioNet). The utilization of these components enables easy training with a small dataset while maintaining a high generalization capability over time. The MODIS Terra daytime LST products were employed to downscale from 1000 m to 30 m, in comparison with the Landsat7 LST products. Our results demonstrate that the new model surpasses STARFM, ESTARFM, and the original U-STFM in terms of prediction accuracy and anti-noise capability. To further enhance other STFMs, these two deep-learning components can replace the linear unmixing and weighting functions with minor modifications. As a deep learning-based model, it can be pretrained and deployed for online prediction.
Remote Sensing Object Detection in the Deep Learning Era—A Review
Authors: Gui Shengxi , Song Shuang , Qin Rongjun , Tang Yang
Published: January 2024

Given the large volume of remote sensing images collected daily, automatic object detection and segmentation have been a consistent need in Earth observation (EO). However, objects of interest vary in shape, size, appearance, and reflecting properties. This is not only reflected by the fact that these objects exhibit differences due to their geographical diversity but also by the fact that these objects appear differently in images collected from different sensors (optical and radar) and platforms (satellite, aerial, and unmanned aerial vehicles (UAV)). Although there exists a plethora of object detection methods in the area of remote sensing, given the very fast development of prevalent deep learning methods, there is still a lack of recent updates for object detection methods. In this paper, we aim to provide an update that informs researchers about the recent development of object detection methods and their close sibling in the deep learning era, instance segmentation. The integration of these methods will cover approaches to data at different scales and modalities, such as optical, synthetic aperture radar (SAR) images, and digital surface models (DSM). Specific emphasis will be placed on approaches addressing data and label limitations in this deep learning era. Further, we survey examples of remote sensing applications that benefited from automatic object detection and discuss future trends of the automatic object detection in EO.
Assessing Derawan Island’s Coral Reefs over Two Decades: A Machine Learning Classification Perspective
Authors: Manessa Masita Dwi Mandini , Ummam Muhammad Al Fadio , Efriana Anisya Feby , Semedi Jarot Mulyo , Ayu Farida
Published: January 2024

This study aims to understand the dynamic changes in the coral reef habitats of Derawan Island over two decades (2003, 2011, and 2021) using advanced machine learning classification techniques. The motivation stems from the urgent need for accurate, detailed environmental monitoring to inform conservation strategies, particularly in ecologically sensitive areas like coral reefs. We employed non-parametric machine learning algorithms, including Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Tree (CART), to assess spatial and temporal changes in coral habitats. Our analysis utilized high-resolution data from Landsat 9, Landsat 7, Sentinel-2, and Multispectral Aerial Photos. The RF algorithm proved to be the most accurate, achieving an accuracy of 71.43% with Landsat 9, 73.68% with Sentinel-2, and 78.28% with Multispectral Aerial Photos. Our findings indicate that the classification accuracy is significantly influenced by the geographic resolution and the quality of the field and satellite/aerial image data. Over the two decades, there was a notable decrease in the coral reef area from 2003 to 2011, with a reduction to 16 hectares, followed by a slight increase in area but with more heterogeneous densities between 2011 and 2021. The study underscores the dynamic nature of coral reef habitats and the efficacy of machine learning in environmental monitoring. The insights gained highlight the importance of advanced analytical methods in guiding conservation efforts and understanding ecological changes over time.
Analysis of Local Track Discontinuities and Defects in Railway Switches Based on Track-Side Accelerations
Authors: Reetz Susanne , Najeh Taoufik , Lundberg Jan , Groos Jörn
Published: January 2024

Switches are an essential, safety-critical part of the railway infrastructure. Compared to open tracks, their complex geometry leads to increased dynamic loading on the track superstructure from passing trains, resulting in high maintenance costs. To increase efficiency, condition monitoring methods specific to railway switches are required. A common approach to track superstructure monitoring is to measure the acceleration caused by vehicle track interaction. Local interruptions in the wheel–rail contact, caused for example by local defects or track discontinuities, appear in the data as transient impact events. In this paper, such transient events are investigated in an experimental setup of a railway switch with track-side acceleration sensors, using frequency and waveform analysis. The aim is to understand if and how the origins of these impact events can be distinguished in the data of this experiment, and what the implications for condition monitoring of local track discontinuities and defects with wayside acceleration sensors are in practice. For the same experimental configuration, individual impact events are shown to be reproducible in waveform and frequency content. Nevertheless, with this track-side sensor setup, the different types of track discontinuities and defects (squats, joints, crossing) could not be clearly distinguished using characteristic frequencies or waveforms. Other factors, such as the location of impact event origin relative to the sensor, are shown to have a much stronger influence. The experimental data suggest that filtering the data to narrow frequency bands around certain natural track frequencies could be beneficial for impact event detection in practice, but differentiating between individual impact event origins requires broadband signals. A multi-sensor setup with time-synchronized acceleration sensors distributed over the switch is recommended.
Graphene Oxide, Carbon Nanotubes, and Polyelectrolytes-Based Impedanciometric E-Tongue for Estrogen Detection in Complex Matrices
Authors: Reis Tiago , Fino Maria Helena , Raposo Maria
Published: January 2024

Currently, it is necessary to maintain the quality of aquifers and water bodies, which means the need for sensors that detect molecules as emerging pollutants (EPs) at low concentrations in aqueous complex solutions. In this work, an electronic tongue (e-tongue) prototype was developed to detect 17β-estradiol in tap water. To achieve such a prototype, an array of sensors was prepared. Each sensor consists of a solid support with interdigitated electrodes without or with thin films prepared with graphene oxide, nanotubes, and other polyelectrolytes molecules adsorbed on them. To collect data from each sensor, impedance spectroscopy was used to analyze the electrical characteristics of samples of estrogen solutions with different concentrations. To analyze the collected data from the sensors, principal components analysis (PCA) method was used to create a three-dimensional plane using the calculated principal components, namely PC1 and PC2, and the estrogen concentration values. Then, damped least squares (DLS) was used to find the optimal values for the hyperplane calibration, as the sensitivity of this e-tongue was not represented by a straight line but by a surface. For the collected data, from nanotubes and graphene oxide sensors, a calibration curve for concentration given by the 10PC1×0.492−PC2×0.14–14.5 surface was achieved. This e-tongue presented a detection limit of 10−16 M of 17β-estradiol in tap water.
Learning from Power Signals: An Automated Approach to Electrical Disturbance Identification within a Power Transmission System
Authors: Boyd Jonathan D. , Tyler Joshua H. , Murphy Anthony M. , Reising Donald R.
Published: January 2024

As power quality becomes a higher priority in the electric utility industry, the amount of disturbance event data continues to grow. Utilities do not have the required personnel to analyze each event by hand. This work presents an automated approach for analyzing power quality events recorded by digital fault recorders and power quality monitors operating within a power transmission system. The automated approach leverages rule-based analytics to examine the time and frequency domain characteristics of the voltage and current signals. Customizable thresholds are set to categorize each disturbance event. The events analyzed within this work include various faults, motor starting, and incipient instrument transformer failure. Analytics for fourteen different event types have been developed. The analytics were tested on 160 signal files and yielded an average accuracy of 99%. Continuous nominal signal data analysis was performed using an approach called the cyclic histogram. The cyclic histogram process is intended to be integrated into the digital fault recorders themselves in order to facilitate the detection of subtle signal variations that are too small to trigger a disturbance event and that can occur over hours or days. In addition to reducing memory requirements by a factor of 320, it is anticipated that cyclic histogram processing will aid in identifying incipient events and identifiers. This project is expected to save engineers time by automating the classification of disturbance events and increasing the reliability of the transmission system by providing near real-time detection and identification of disturbances as well as prevention of problems before they occur.
The Impact of Line-of-Sight and Connected Vehicle Technology on Mitigating and Preventing Crash and Near-Crash Events
Authors: Herbers Eileen , Doerzaph Zachary , Stowe Loren
Published: January 2024

Line-of-sight (LOS) sensors developed in newer vehicles have the potential to help avoid crash and near-crash scenarios with advanced driving-assistance systems; furthermore, connected vehicle technologies (CVT) also have a promising role in advancing vehicle safety. This study used crash and near-crash events from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP2 NDS) to reconstruct crash events so that the applicable benefit of sensors in LOS systems and CVT can be compared. The benefits of CVT over LOS systems include additional reaction time before a predicted crash, as well as a lower deceleration value needed to prevent a crash. This work acts as a baseline effort to determine the potential safety benefits of CVT-enabled systems over LOS sensors alone.
Time Constant as the Main Component to Optimize the Resistance Temperature Sensors’ Calibration Process
Authors: Klebba Maciej , Frącz Arkadiusz , Brodzicki Michal , Rzepkowska Adrianna , Wąż Mariusz
Published: January 2024

Temperature sensor calibration in the majority of measurement laboratories is performed on the ground of measurement procedures. The procedures specify the timespan for the temperature of the tested sensor to stabilize. In practice, the fact of time constant increase above expectations can be observed. This results from the method of operation, time of use, and level of contamination of individual sensors. The paper proposes a method to optimize the calibration process of resistance temperature sensors based on the measurement of the time constant and, on this basis, to determine the sensor stabilization time during calibration.
Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network
Authors: Yin Songfeng , Zou Xiang , Cheng Yue , Liu Yunlong
Published: January 2024

We aimed to improve the detection accuracy of laser methane sensors in expansive temperature application environments. In this paper, a large-scale dataset of the measured concentration of the sensor at different temperatures is established, and a temperature compensation model based on the ISSA-BP neural network is proposed. On the data side, a large-scale dataset of 15,810 sets of laser methane sensors with different temperatures and concentrations was established, and an Improved Isolation Forest algorithm was used to clean the large-scale data and remove the outliers in the dataset. On the modeling framework, a temperature compensation model based on the ISSA-BP neural network is proposed. The quasi-reflective learning, chameleon swarm algorithm, Lévy flight, and artificial rabbits optimization are utilized to improve the initialization of the sparrow population, explorer position, anti-predator position, and position of individual sparrows in each generation, respectively, to improve the global optimization seeking ability of the standard sparrow search algorithm. The ISSA-BP temperature compensation model far outperforms the four models, SVM, RF, BP, and PSO-BP, in model evaluation metrics such as MAE, MAPE, RMSE, and R-square for both the training and test sets. The results show that the algorithm in this paper can significantly improve the detection accuracy of the laser methane sensor under the wide temperature application environment.
The Potential of Co-Designing with Living Organisms: Towards a New Ecological Paradigm in Architecture
Authors: Chayaamor-Heil Natasha , Houette Thibaut , Demirci Özge , Badarnah Lidia
Published: January 2024

Living organisms have been progressively used by designers to propose alternative design outcomes aiming towards more ecological aspects. The design development and manufacturing of new materials or design components from living organisms are more achievable in textile, fashion, or product design than in architecture and construction due to the scale, multi-layer constraints, and requirements. The aim of this paper is to investigate the interdisciplinary framework, the opportunities, and limitations of introducing living organisms into the design process, including the implementation from the design ideas to prototyping until commercialization. In this paper, we focus on three types of living organisms: algae, bacteria, and fungi. Firstly, we overviewed and studied existing projects and experimentations to understand the design process and fabrication of living organisms in other domains in comparison to architecture. Secondly, we selected three case studies in architecture for each organism to analyze. We collected the data and conducted interviews with multidisciplinary experts involved in each case. Our findings show a better understanding of the potential to integrate living organisms in architectural design, the advantages, and the difficulties towards ecological awareness. The results from the interview and a comparative analysis show the advantages and constraints of each case. The future outlooks towards the use of living organisms as part of design in architecture are also discussed.
Reliability of Municipal Solid Waste Landfills within the Eurocode Framework
Authors: Dodigović Filip , Ivandić Krešo
Published: January 2024

Municipal solid waste (MSW) landfill slope failures can have significant consequences for the economy, environment, and human health. One potential cause of slope failure is insufficient reliability, resulting from inadequate design. The usual practice in the design of MSW landfills involves utilizing established geotechnical codes, such as Eurocode 7 (EC7), to perform slope stability assessments. Considering the substantial heterogeneity of MSW relative to soil, questions arise regarding the justification of such an approach in the design of MSW landfills. This study examines the suitability of applying EC7 in MSW landfill design, analyzing the stability and reliability of landfill slopes across various heights, front slope angles, design approaches, and consequence classes. This study finds that, in most cases considered, EC7 does not ensure an adequate level of reliability for MSW landfill slopes. Therefore, it is suggested that EC7 should be complemented with specific guidelines for incorporating MSW in geotechnical analyses to achieve the desired structural reliability. Adopting this strategy will not only enhance the reliability of landfill design but also promote the development of solutions that are economically and environmentally sustainable.
Thermal Performance Analysis of Porous Foam-Assisted Flat-Plate Solar Collectors with Nanofluids
Authors: Lin Xinwei , Xia Yongfang , Cheng Zude , Liu Xianshuang , Fu Yingmei , Li Lingyun , Zhou Wenqin
Published: January 2024

This study proposed a model of a porous media-assisted flat-plate solar collector (FPSC) using nanofluid flow. The heightened thermal efficiency of FPSC undergoes numerical scrutiny, incorporating various factors for analysis, including aspects like the configuration of the porous block introduced, Darcy number (Da = 10−5~10−2), types of nanoparticles, volume fraction (φ), and mixing ratio (φc). The numerical findings indicate that the dominant factor in the channel is the global Nusselt number (Nug). As the Darcy number rises, there is an improvement in the heat transfer performance within the channel. Simultaneously, for the case of Re = 234, φ = 3%, and φc = 100%, the Nug in the channel reaches a maximum value of 6.80, and the thermal efficiency can be increased to 70.5% with the insertion of rectangular porous blocks of Da = 10−2. Finally, the performance evaluation criteria (PEC) are employed for a comprehensive assessment of the thermal performance of FPSC. This analysis considers both the improved heat transfer and the pressure drop in the collector channel. The FPSC registered a maximum PEC value of 1.8 when rectangular porous blocks were inserted under conditions of Da = 10−2 and Re = 234 and the nanofluid concentrations of φ = 3% and φc = 100%. The findings can be provided to technically support the future commercial applications of FPSC. The findings may serve as a technical foundation for FPSC in upcoming porous media and support commercial applications.
Driving Manufacturing Companies toward Industry 5.0: A Strategic Framework for Process Technological Sustainability Assessment (P-TSA)
Authors: Vacchi Marco , Siligardi Cristina , Settembre-Blundo Davide
Published: January 2024

This study explores the complex nexus between technological innovation, Industry 4.0′s transformative paradigm, and the emerging concept of Industry 5.0, highlighting the critical role of integrating sustainability into factories to enhance organizational competitiveness. In this context, confusion arises between the terms “sustainable technologies” and “technological sustainability” due to two factors: the misuse of the terms as synonyms and the misattribution of conceptual meaning to each term. To clarify this ambiguity, this study validates a conceptual framework for technological sustainability by examining the processes of a ceramic manufacturing company. This assessment highlights the potential of technological sustainability and its associated measurement model to facilitate the transition from Industry 4.0 to Industry 5.0. This research provides fundamental insights into technological sustainability and serves as a guide for future empirical efforts aimed at achieving a balanced and sustainable integration of technology into manufacturing practices.
Life Cycle Assessment of Carbon Capture by an Intelligent Vertical Plant Factory within an Industrial Park
Authors: Chen Haoyang , Dong Xue , Lei Jie , Zhang Ning , Wang Qianrui , Shi Zhiang , Yang Jinxing
Published: January 2024

Bio-based carbon capture and utilization emerges as a critical pathway to mitigate carbon dioxide (CO2) emissions from industrial activities. Within this context, plant factories become an innovative solution for biological carbon capture within industrial parks, fed with the substantial carbon emissions inherent in industrial exhaust gases to maximize their carbon sequestration capabilities. Among the various plant species suitable for such plant factories, Pennisetum giganteum becomes a candidate with the best potential, characterized by its high photosynthetic efficiency (rapid growth rate), perennial feature, and significant industrial value. This paper studies the feasibility of cultivating Pennisetum giganteum within an intelligent plant factory situated in an industrial park. An automated and intelligent plant factory was designed and established, in which multiple rounds of Pennisetum giganteum cultivations were performed, and life cycle assessment (LCA) was carried out to quantitatively evaluate its carbon capture capacity. The results show that the primary carbon emission in the plant factory arises from the lighting phase, constituting 67% of carbon emissions, followed by other processes (15%) and the infrastructure (10%). The absorption of CO2 during Pennisetum giganteum growth in the plant factory effectively mitigates carbon emissions from industrial exhaust gases. The production of 1 kg of dry Pennisetum giganteum leads to a net reduction in emissions by 0.35 kg CO2 equivalent. A plant factory with dimensions of 3 m × 6 m × 2.8 m can annually reduce carbon emissions by 174 kg, with the annual carbon sequestration per unit area increased by 56% compared to open-field cultivation. Furthermore, large-scale plant factories exhibit the potential to offset the carbon emissions of entire industrial parks. These findings confirm the viability of bio-based carbon capture using intelligent plant factories, highlighting its potential for carbon capture within industrial parks.
Evaluating Sustainable Online Education: A Cross-Disciplinary Analysis of IT Device Utilization among Slovakian and Hungarian University Students
Authors: Gombkötő Nóra , Štempeľová Iveta , Takáč Ondrej
Published: January 2024

By the onset of the 21st century, online presence had become prevalent in higher education, with the COVID-19 pandemic further accelerating this trend. However, the success of online education and its assessment by students can differ significantly from region to region and according to the field of study. This can be influenced by students’ habits of using IT devices, but it can also occur the other way around. In this research, experiences related to online education were examined in the fields of Informatics, Agriculture and Pharmacy education at two higher-education institutions in Slovakia and one in Hungary, considering the environmental and social sustainability implications. In the study, in addition to simple statistical methods, a cross-tabulation analysis was carried out using Cramer’s V method. The results have shown that the students of the investigated institutions confidently navigate the online world; they are conscious users of IT tools without being addicted. A total of 74% of students in Mosonmagyaróvár believe they possess sufficient information about the risks associated with computers, mobile phones, and the Internet, whereas only 34% of students in Košice share the same sentiment. The reason for the differences between these characteristics can be attributed to the specialties of the different majors, and not to those arising from regional differences, raising important questions about the ecological sustainability of online education practices. A relatively great consistency can be observed in the assessment of online learning among students from the three institutions, with approximately 85% expressing overall satisfaction with the online learning experience. The easier availability of study materials and savings on travel are mentioned as advantages, contributing to economic sustainability. However, separation from their mates and the lack of practical training may be regarded as a disadvantage for them, as they seem to have a preference for face-to-face training. Overall, it may be concluded that purely online training in the fields of Informatics, Agriculture, and Pharmacy training is not feasible for the time being, necessitating a balanced and sustainable approach for the future.
On Some Origins of Tautomeric Preferences in Neutral Creatinine in Vacuo: Search for Analogies and Differences in Cyclic Azoles and Azines
Authors: Raczyńska Ewa Daniela
Published: January 2024

In order to look for the origins of tautomeric preferences in neutral creatinine in vacuo, we examined prototropic conversions for model azoles, namely mono-hydroxy and mono-amino imidazoles, and also for their selected 1-methyl derivatives. All possible isomeric forms of creatinine and model compounds, resulting from intramolecular proton transfer (prototropy), conformational isomerism about –OH, and configurational isomerism about =NH, were studied in the gas phase (model of non-polar environment) by means of quantum-chemical methods. Because the bond-length alternation is a consequence of the resonance phenomenon, it was measured for all DFT-optimized structures by means of the harmonic oscillator model of electron delocalization (HOMED) index. Important HOMED analogies were discussed for investigated azoles and compared with those for previously studied cyclic azines, including pyrimidine nucleic acid bases. The internal effects were taken into account, and the stabilities of the investigated tautomers-rotamers were analyzed. Significant conclusions on the favored factors that can dictate the tautomeric preferences in creatinine were derived.
Tetrodotoxin and Its Analogues (TTXs) in the Food-Capture and Defense Organs of the Palaeonemertean Cephalothrix cf. simula
Authors: Malykin Grigorii V. , Velansky Peter V. , Magarlamov Timur Yu.
Published: January 2024

Tetrodotoxin (TTX), an extremely potent low-molecular-weight neurotoxin, is widespread among marine animals including ribbon worms (Nemertea). Previously, studies on the highly toxic palaeonemertean Cephalothrix cf. simula showed that toxin-positive structures are present all over its body and are mainly associated with glandular cells and epithelial tissues. The highest TTXs concentrations were detected in a total extract from the intestine of the anterior part of the body and also in a total extract from the proboscis. However, many questions as to the TTXs distribution in the organs of the anterior part of the worm’s body and the functions of the toxins in these organs are still unanswered. In the present report, we provide additional results of a detailed and comprehensive analysis of TTXs distribution in the nemertean’s proboscis, buccal cavity, and cephalic gland using an integrated approach including high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS), confocal laser scanning microscopy with anti-TTX antibodies, light and electron microscopies, and observations of feeding behavior. For the proboscis, we have found a TTXs profile different from that characteristic of other organs and tissues. We have also shown for the first time that the major amount of TTXs is localized in the anterior part of the proboscis that is mainly involved in hunting. TTX-containing glandular cells, which can be involved in the prey immobilization, have been found in the buccal cavities of the nemerteans. A significant contribution of the cephalic gland to the toxicity of this animal has been shown for the first time, and the role of the gland is hypothesized to be involved not only in protection against potential enemies but also in immobilizing prey. The data obtained have made it possible to extend the understanding of the role and features of the use of TTXs in the organs of the anterior part of nemertean’s body.
Respiratory Syncytial Virus-Associated Deaths among Children under Five before and during the COVID-19 Pandemic in Bangladesh
Authors: Hassan Md Zakiul , Islam Md. Ariful , Haider Saleh , Shirin Tahmina , Chowdhury Fahmida
Published: January 2024

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory infections in young children worldwide. RSV-associated deaths in children are underreported in Bangladesh. We analyzed hospital-based surveillance data on severe acute respiratory infections (SARIs) in under-five children before (August 2009–February 2020) and during the COVID-19 pandemic (March 2020–March 2022). Using the World Health Organization definition, we identified SARI cases in 14 tertiary-level hospitals. Nasopharyngeal and oropharyngeal swabs were collected for real-time reverse-transcriptase–polymerase chain reaction (rRT-PCR) testing of six respiratory viruses, including RSV. SARI deaths during the pandemic (2.6%, 66) were higher than pre-pandemic (1.8%, 159; p < 0.001). Nearly half of pandemic deaths (47%) had underlying respiratory viruses, similar to the pre-pandemic rate (45%). RSV detection in deaths was consistent pre-pandemic (13%, 20/159) and during the pandemic (12%, 8/66). Children aged < 6 months constituted 57% (16) of RSV-related deaths. Evaluating interventions like maternal vaccination and infant monoclonal antibody prophylaxis is crucial to address RSV, a major contributor to under-five SARI deaths.
Incidence and Severity of COVID-19 in Relation to Anti-Receptor-Binding Domain IgG Antibody Level after COVID-19 Vaccination in Kidney Transplant Recipients
Authors: Messchendorp A. Lianne , Sanders Jan-Stephan F. , Abrahams Alferso C. , Bemelman Frederike J. , Bouwmans Pim , van den Dorpel René M. A. , Hilbrands Luuk B. , Imhof Céline , Reinders Marlies E. J. , Rispens Theo , Steenhuis Maurice , ten Dam Marc A. G. J. , Vart Priya , de Vries Aiko P. J. , Hemmelder Marc H. , Gansevoort Ron T. ,   RECOVAC Investigators
Published: January 2024

Kidney transplant recipients (KTRs) elicit an impaired immune response after COVID-19 vaccination; however, the exact clinical impact remains unclear. We therefore analyse the relationship between antibody levels after vaccination and the risk of COVID-19 in a large cohort of KTRs. All KTRs living in the Netherlands were invited to send a blood sample 28 days after their second COVID-19 vaccination for measurement of their IgG antibodies against the receptor-binding domain of the SARS-CoV-2 spike protein (anti-RBD IgG). Information on COVID-19 was collected from the moment the blood sample was obtained until 6 months thereafter. Multivariable Cox and logistic regression analyses were performed to analyse which factors affected the occurrence and severity (i.e., hospitalization and/or death) of COVID-19. In total, 12,159 KTRs were approached, of whom 2885 were included in the analyses. Among those, 1578 (54.7%) became seropositive (i.e., anti-RBD IgG level >50 BAU/mL). Seropositivity was associated with a lower risk for COVID-19, also after adjusting for multiple confounders, including socio-economic status and adherence to COVID-19 restrictions (HR 0.37 (0.19–0.47), p = 0.005). When studied on a continuous scale, we observed a log-linear relationship between antibody level and the risk for COVID-19 (HR 0.52 (0.31–0.89), p = 0.02). Similar results were found for COVID-19 severity. In conclusion, antibody level after COVID-19 vaccination is associated in a log-linear manner with the occurrence and severity of COVID-19 in KTRs. This implies that if future vaccinations are indicated, the aim should be to reach for as high an antibody level as possible and not only seropositivity to protect this vulnerable patient group from disease.
Steady-State and Dynamic Simulation for Wastewater Treatment Plant Management: Case Study of Maghnia City, North-West Algeria
Authors: Tiar Sidi Mohamed , Bessedik Madani , Abdelbaki Chérifa , ElSayed Nadia Badr , Badraoui Abderrahim , Slimani Amaria , Kumar Navneet
Published: January 2024

Given the critical importance of addressing effluent quality concerns, the present study was dedicated to developing a dynamic simulation model based on the Activated Sludge Model 1 (ASM1) of a wastewater treatment plant located in Maghnia City, Algeria. The model calibration process involved collecting and analyzing 56 samples from the plant over a period of 18 months (from July 2021 to January 2023). Thirteen physicochemical parameters were analyzed to identify the variations in their water quality over time. Stoichiometric and kinetic parameters were adjusted during the plant calibration process. These modifications resulted in a reasonable alignment with the investigated variables, enabling the accurate prediction of the wastewater treatment plants (WWTPs)’ steady-state behavior regarding the removal measurements of chemical oxygen demand (COD), total suspended solids (TSS), and ammonium (NH4-N). The model was validated using 14-day measurements spanning a 4-month duration, and the results indicated good agreement between the observed and simulated effluent variable of chemical oxygen demand (COD) with a root mean square error (RMSE) of 23%. These findings highlight the utility of the ASM1 Model in comprehending and managing the intricate dynamics of the activated sludge process in wastewater treatment plants.
Compound Impact of Storm Surge and Flood Characteristics in Coastal Area Based on Copula
Authors: Zhu Zhenglei , Zhang Wei , Zhu Wenjin
Published: January 2024

In low-lying coastal areas, the interplay of various factors including precipitation, river flow, and storm surge can lead to greater influence on floods when they occur simultaneously. The copula method was used in this study to investigate the bivariate flood risk of compounding storm surge and river discharge events in the Pearl River Delta (PRD). Our results indicate that while the correlation between storm surge and flood peak (S-Q) was weak, there was a strong dependence between the pairs of storm surge–flood volume (S-V) and storm surge–flood duration (S-D). For these three pairs, the Clayton copula was the optimal function for S-Q, while the Frank copula was the optimal function for S-V and S-D, respectively. When the flood volume exceeds 2.0 × 104 m3/s and the flood duration is more than 10 days, the bivariate hydrologic risk for S-V and S-D is observed to decrease rapidly. Furthermore, the failure probability (FP) would be underestimated when the combined impact of river flow and storm surge is ignored in coastal flood risk assessment. Such bivariate hydrologic risk analysis implies that when determining design values in coastal flood risk assessment, the combined impact of river flow and storm surge should be taken into account.
Temporal Environmental Status of a Shallow Lake Using Alpha and Beta Diversity on Phytoplankton Communities
Authors: Ríos-Henríquez Catalina , Fuentes Norka
Published: January 2024

Phytoplankton communities are excellent indicators of the environmental status of shallow lakes since changes in diversity alert us to potential deterioration. To assess the environmental condition of a shallow lake with strong anthropogenic pressure from forest monocultures, alpha and beta diversities were determined. Three monitoring stations were established in the shallow Kusrüpuyewe Lake, southern Chile, which were monitored during the 2021 austral summer and winter. Alpha diversity was high indicating a stable environmental condition. In total, 103 species in summer, 96 species in winter and a high species diversity (Shannon index: H′ > 5 bits/ind) were recorded. Beta diversity indicated that this ecosystem is seasonally heterogeneous, is potentially productive and has a high species turnover. Based on the large species inventory, we conclude that this shallow lake is stable and diverse. Although it is threatened by the presence of forest monocultures, it maintains a stable environmental condition, mainly due to the ability of the phytoplankton present to self-regulate through the species turnover. This study provides the relevant background information to establish conservation measures around the shallow lake, an ecosystem that provides various ecosystem services for the local indigenous communities.
Integrated Constructed Wetland–Microbial Fuel Cell Systems Using Activated Carbon: Structure-Activity Relationship of Activated Carbon, Removal Performance of Organics and Nitrogen
Authors: Wang Xiaoou , Xue Ming , Wang Zhaoyu , Xia Weiyi , Zhang Changping
Published: January 2024

This study designed integrated constructed wetland–microbial fuel cell (CW–MFC) systems using activated carbon (AC) as both CW substrates and MFC anodes and investigated the structure-activity relationship of six kinds of commercial columnar AC, as well as the organics and nitrogen removal, microbial activity and diversity of CW–MFCs. Results showed that the nitrogen adsorption by AC tended to be a linear process in which physical adsorption played a leading role and micropores made great contributions. A higher specific surface area, developed mesopores, and oxygen functionalities were conducive to the capacitance properties of AC, while a higher specific surface area and developed micropores were conducive to reduce material resistance and improve ion permeability. Coconut-shell-based AC had both excellent nitrogen adsorption capacity and electrochemical properties, making it ideal as both CW substrates and MFC anodes for CW–MFCs. The electricity generation, coulombic efficiency, internal resistance, and organics and nitrogen removal of CW–MFCs were positively correlated with the total depth of AC anodes. The total depth of AC anodes can be determined based on the influent organics/nitrogen loadings and organics/nitrogen removal load of AC, and a relatively smaller depth of a single AC anode (5 cm) was recommended. The MFC effectively improved the enzymatic activity (by 10.33% dehydrogenase, 8.72% catalase, and 7.35% ammonia monooxygenase), nitrification/denitrification intensity (by 9.53%/6.68%), and microbial diversity (by 1.64–4.07%) of AC (MFC anodes) in CW–MFCs, while the depth of a single AC anode barely influenced the microbial activity and diversity. MFCs increased COD and NH3-N removal in CW–MFCs by 11.60% and 3.4%, respectively. The increased total adsorption capacity of AC with the increase of its total depth narrowed the difference in COD removal resulting from the promotion of MFCs on organics degradation. MFCs increased TN removal in CW–MFCs by 5.29% through promoting denitrification in cathodes and enhancing NH3-N assimilation in anodes. The phyla of EAB (Proteobacteria, Bacteroidetes, Firmicutes, and Acidobacteria) and genera of EAB (Citrobacter, Geobacter, and Pseudomonas) accounted for 85–86% and 15.58–16.64% of the microbial community on AC anodes in CW–MFCs, respectively.
Flexible Electrohydrodynamic Fluid-Driven Valveless Water Pump via Immiscible Interface
Authors: Mao Zebing , Hosoya Naoki , Maeda Shingo
Published: January 2024

The conventional electrohydrodynamic (EHD) pump is limited to pumping functional and dielectric liquids, which restricts its applications in fields like microfluidics, food safety, and materials production. In this study, we present a flexible water pump driven by EHD fluid, achieved by integrating valveless elements into the fluidic channel. Our approach leverages the water–EHD interface to propel the immiscible aqueous liquid and reciprocate this process using the nozzle–diffuser system. All components of the water pump are digitally fabricated and assembled. The valveless parts are created using a laser cutting machine. Additionally, we develop a model for the EHD pump and nozzle–diffuser system to predict the generated flow rate, considering factors such as the asymmetrical performance of the EHD pump, pulse frequency, applied voltage, and structural parameters. Finally, we experimentally characterize the flow rates of both the EHD pump and water pump and apply the newly developed device to air bubble manipulation and droplet generation. This research broadens the range of specialized liquids pumped by EHD pumps to include other aqueous liquids or mixtures.