bluuebunny/crossref_metadata_2025 huggingface dataset:
“I’ve been doing this for years”: the COVID-19 pandemic and family caregiver isolation and loneliness
Authors: Sullivan Caitlin , Vick Judith B. , Decosimo Kasey , Grubber Janet , Coffman Cynthia J. , Bruening Rebecca , Sperber Nina , Tucker Matthew , Dadolf Joshua , Boucher Nathan , Wang Virginia , Allen Kelli D. , Hastings S. Nicole , Van Houtven Courtney H. , Shepherd-Banigan Megan
Published: May 2024

Background

Family caregivers are family members or friends of care recipients who assist with activities of daily living, medication management, transportation, and help with finances among other activities. As a result of their caregiving, family caregivers are often considered a population at risk of experiencing increased stress, isolation, and loneliness. During the COVID-19 pandemic in the US, social isolation and decrease in social activities were a top concern among older adults and their family caregivers. Using secondary analysis of survey data as part of a multi-site implementation trial of a caregiver skills training program, we describe differences in caregiver experiences of loneliness before and during the COVID-19 pandemic.

Methods

Health and wellbeing surveys of family caregivers were collected on 422 family caregivers of veterans before and during COVID-19. Logistic regression modeling examined whether the loneliness differed between caregiver groups pre vs during COVID-19, using the UCLA 3-item loneliness measure. Rapid directed qualitative content analysis of open-ended survey questions was used to explore the context of how survey responses were affected by the COVID-19 pandemic.

Results

There were no significant differences in loneliness between caregivers pre vs during COVID-19. In open-ended responses regarding effects of COVID-19, caregivers described experiencing loneliness and social isolation; why they were unaffected by the pandemic; and how caregiving equipped them with coping strategies to manage negative pandemic-related effects.

Conclusion

Loneliness did not differ significantly between pre vs during COVID-19 caregivers. Future research could assess what specific characteristics are associated with caregivers who have resiliency, and identify caregivers who are more susceptible to experiencing loneliness. Understanding caregiver loneliness could assist other healthcare systems in developing and implementing caregiver support interventions.
The impact of text topic and assumed human vs. AI authorship on competence and quality assessment
Authors: Proksch Sebastian , Schühle Julia , Streeb Elisabeth , Weymann Finn , Luther Teresa , Kimmerle Joachim
Published: May 2024

Background

While Large Language Models (LLMs) are considered positively with respect to technological progress and abilities, people are rather opposed to machines making moral decisions. But the circumstances under which algorithm aversion or algorithm appreciation are more likely to occur with respect to LLMs have not yet been sufficiently investigated. Therefore, the aim of this study was to investigate how texts with moral or technological topics, allegedly written either by a human author or by ChatGPT, are perceived.

Methods

In a randomized controlled experiment, n = 164 participants read six texts, three of which had a moral and three a technological topic (predictor text topic). The alleged author of each text was randomly either labeled “ChatGPT” or “human author” (predictor authorship). We captured three dependent variables: assessment of author competence, assessment of content quality, and participants' intention to submit the text in a hypothetical university course (sharing intention). We hypothesized interaction effects, that is, we expected ChatGPT to score lower than alleged human authors for moral topics and higher than alleged human authors for technological topics and vice versa.

Results

We only found a small interaction effect for perceived author competence, p = 0.004, d = 0.40, but not for the other dependent variables. However, ChatGPT was consistently devalued compared to alleged human authors across all dependent variables: there were main effects of authorship for assessment of the author competence, p < 0.001, d = 0.95; for assessment of content quality, p < 0.001, d = 0.39; as well as for sharing intention, p < 0.001, d = 0.57. There was also a small main effect of text topic on the assessment of text quality, p = 0.002, d = 0.35.

Conclusion

These results are more in line with previous findings on algorithm aversion than with algorithm appreciation. We discuss the implications of these findings for the acceptance of the use of LLMs for text composition.
Modeling groundwater recharge potential zones in the Wadi Yalamlam, Saudi Arabia
Authors: Elsebaie Ibrahim H. , Kawara Atef Q.
Published: May 2024

Effective management of groundwater resources is vital in arid and semi-arid regions like the Yalamlam Basin. Identifying appropriate places for groundwater artificial recharge is key to addressing water shortages and guaranteeing the long-term viability of aquifers. By combining the Analytical Hierarchy Process (AHP) approach with GIS technology, this research offers a thorough framework for evaluating the potential for groundwater recharge. Data collection for the study includes lineament density, slope, drainage density, rainfall, Land Use/Land Cover (LU/LC), soil, elevation, and TWI, among other crucial variables. In this study, lineament density, slope, drainage density, rainfall, LULC, soil, elevation and TWI are the most sensitive characteristics with relative weights of 30, 23, 16, 11, 8, 5, 4 and 3%, respectively. According to the study’s findings, there are many zones in the Yalamlam region with varying capacities for groundwater recharging. Based on the locations that may be used for groundwater recharge, the study’s findings were categorized into five groups: very high (12.7%), high (23.3%), moderate (29.6%), poor (24.4%), and very poor (10%). The validation of the groundwater protection zones was conducted by using eight wells in the basin. As part of the validation process, the Total Dissolved Solids (TDS) in the boreholes and the groundwater protection zones (GWPZs) were compared. A strong positive correlation was found between them (0.61). The results of this research can be used for the management of groundwater resources and provide valuable information for the creation of policies that focus on specific actions to boost groundwater recharge. These findings may considerably enhance the effectiveness of efforts aimed at implementing customized methods to encourage groundwater recharge. The results suggest that there are substantial prospects for using artificial recharge in groundwater management and planning to tackle the issue of groundwater availability in the study region.
Computer-controlled closed-loop norepinephrine infusion system for automated control of mean arterial pressure in dogs under isoflurane-induced hypotension: a feasibility study
Authors: Sasaki Kazumasu , Kawada Toru , Matsushita Hiroki , Yokota Shohei , Kakuuchi Midori , Yokoi Aimi , Yoshida Yuki , Morita Hidetaka , Sato Kei , Nishikawa Takuya , Kutter Annette P. N. , Kataoka Yasuyuki , Alexander Joe , Saku Keita , Ishikawa Tatsuya , Uemura Kazunori
Published: May 2024

Introduction

Intra-operative hypotension is a common complication of surgery under general anesthesia in dogs and humans. Computer-controlled closed-loop infusion systems of norepinephrine (NE) have been developed and clinically applied for automated optimization of arterial pressure (AP) and prevention of intra-operative hypotension in humans. This study aimed to develop a simple computer-controlled closed-loop infusion system of NE for the automated control of the mean arterial pressure (MAP) in dogs with isoflurane-induced hypotension and to validate the control of MAP by the developed system.

Methods

NE was administered via the cephalic vein, whereas MAP was measured invasively by placing a catheter in the dorsal pedal artery. The proportional-integral-derivative (PID) controller in the negative feedback loop of the developed system titrated the infusion rate of NE to maintain the MAP at the target value of 60 mmHg. The titration was updated every 2 s. The performance of the developed system was evaluated in six laboratory Beagle dogs under general anesthesia with isoflurane.

Results

In the six dogs, when the concentration [median (interquartile range)] of inhaled isoflurane was increased from 1.5 (1.5–1.5)% to 4 (4–4)% without activating the system, the MAP was lowered from 95 (91–99) to 41 (37–42) mmHg. In contrast, when the concentration was increased from 1.5 (1.0–1.5)% to 4 (4–4.8)% for a 30-min period and the system was simultaneously activated, the MAP was temporarily lowered from 92 (89–95) to 47 (43–49) mmHg but recovered to 58 (57–58) mmHg owing to the system-controlled infusion of NE. If the acceptable target range for MAP was defined as target MAP ±5 mmHg (55 ≤ MAP ≤65 mmHg), the percentage of time wherein the MAP was maintained within the acceptable range was 96 (89–100)% in the six dogs during the second half of the 30-min period (from 15 to 30 min after system activation). The median performance error, median absolute performance error, wobble, and divergence were − 2.9 (−4.7 to 1.9)%, 2.9 (2.0–4.7)%, 1.3 (0.8–1.8)%, and − 0.24 (−0.34 to −0.11)%·min−1, respectively. No adverse events were observed during the study period, and all dogs were extubated uneventfully.

Conclusion

This system was able to titrate the NE infusion rates in an accurate and stable manner to maintain the MAP within the predetermined target range in dogs with isoflurane-induced hypotension. This system can be a potential tool in daily clinical practice for the care of companion dogs.
The Influence of Perceived Macro Environment on the Competitiveness of Internationalized Medium-Sized and Large Enterprises
Authors: Stocker Miklós , Erdélyi Ádám
Published: May 2024

Firm competitiveness is a crucial trait of companies which managers strive to improve, and even policy makers focus on it regarding economic development. As companies are embedded into different layers of the environment, this study aims to identify the influence of top managerial perception about the external environment on the firm-level competitiveness of medium-sized and large internationalized companies. The investigation is based on the 6th round of the Competitiveness Survey conducted in Hungary between October 2018 and July 2019 from which n = 107 medium-sized or large companies qualified for this study. The institution-based view from the strategic management literature was chosen to differentiate the variables in the macroeconomic environment of the firm while the FCI index was used to measure firm-level competitiveness. After conducting factor and regression analyses, the results show that the perceived macro environment is positively related to the competitiveness of internationalized medium-sized and large companies. Managerial perceptions on civil service and education had the strongest significant positive association with firm-level competitiveness, whereas perceptions on social and ecological expectations had a significant positive association with the Adaptivity of the firm. This study contributes to the existing body of literature by demonstrating that, even within contentious institutional contexts, the perceptions of internationalized medium and large companies’ top managers regarding education, civil service, and social and ecological expectations have a discernible influence on the competitiveness of these companies.
Multi-Fidelity Adaptive Sampling for Surrogate-Based Optimization and Uncertainty Quantification
Authors: Garbo Andrea , Parekh Jigar , Rischmann Tilo , Bekemeyer Philipp
Published: May 2024

Surrogate-based algorithms are indispensable in the aerospace engineering field for reducing the computational cost of optimization and uncertainty quantification analyses, particularly those involving computationally intensive solvers. This paper presents a novel approach for enhancing the efficiency of surrogate-based algorithms through a new multi-fidelity sampling technique. Unlike existing multi-fidelity methods which are based on a single multiplicative acquisition function, the proposed technique decouples the identification of the new infill sample from the selection of the fidelity level. The location of the infill sample is determined by leveraging the highest fidelity surrogate model, while the fidelity level used for its performance evaluation is chosen as the cheapest one within the “accurate enough” models at the infill location. Moreover, the methodology introduces the application of the Jensen–Shannon divergence to quantify the accuracy of the different fidelity levels. Overall, the resulting technique eliminates some of the drawbacks of existing multiplicative acquisition functions such as the risk of continuous sampling from lower and cheaper fidelity levels. Experimental validation conducted in surrogate-based optimization and uncertainty quantification scenarios demonstrates the efficacy of the proposed approach. In an aerodynamic shape optimization task focused on maximizing the lift-to-drag ratio, the multi-fidelity strategy achieved comparable results to standard single-fidelity sampling but with approximately a five-fold improvement in computational efficiency. Likewise, a similar reduction in computational costs was observed in the uncertainty quantification problem, with the resulting statistical values aligning closely with those obtained using traditional single-fidelity sampling.
Soybean Canopy Stress Classification Using 3D Point Cloud Data
Authors: Young Therin J. , Chiranjeevi Shivani , Elango Dinakaran , Sarkar Soumik , Singh Asheesh K. , Singh Arti , Ganapathysubramanian Baskar , Jubery Talukder Z.
Published: May 2024

Automated canopy stress classification for field crops has traditionally relied on single-perspective, two-dimensional (2D) photographs, usually obtained through top-view imaging using unmanned aerial vehicles (UAVs). However, this approach may fail to capture the full extent of plant stress symptoms, which can manifest throughout the canopy. Recent advancements in LiDAR technologies have enabled the acquisition of high-resolution 3D point cloud data for the entire canopy, offering new possibilities for more accurate plant stress identification and rating. This study explores the potential of leveraging 3D point cloud data for improved plant stress assessment. We utilized a dataset of RGB 3D point clouds of 700 soybean plants from a diversity panel exposed to iron deficiency chlorosis (IDC) stress. From this unique set of 700 canopies exhibiting varying levels of IDC, we extracted several representations, including (a) handcrafted IDC symptom-specific features, (b) canopy fingerprints, and (c) latent feature-based features. Subsequently, we trained several classification models to predict plant stress severity using these representations. We exhaustively investigated several stress representations and model combinations for the 3-D data. We also compared the performance of these classification models against similar models that are only trained using the associated top-view 2D RGB image for each plant. Among the feature-model combinations tested, the 3D canopy fingerprint features trained with a support vector machine yielded the best performance, achieving higher classification accuracy than the best-performing model based on 2D data built using convolutional neural networks. Our findings demonstrate the utility of color canopy fingerprinting and underscore the importance of considering 3D data to assess plant stress in agricultural applications.
Investigating and Characterizing the Systemic Variability When Using Generative Design for Additive Manufacturing
Authors: Peckham Owen , Elverum Christer W. , Hicks Ben , Goudswaard Mark , Snider Chris , Steinert Martin , Eikevåg Sindre W.
Published: May 2024

This paper demonstrates the unpredictability of outcomes that result from compounding variabilities when using generative design (GD) coupled with additive manufacturing (AM). AM technologies offer the greatest design freedom and hence are most able to leverage the full capability of generative design (GD) tools and thus maximize potential improvements, such as weight, waste and cost reduction, strength, and part consolidation. Implicit in all studies reported in the literature is the fundamental assumption that the use of GD, irrespective of user experience or approach followed, yields high-performing and/or comparable design outputs. This work demonstrates the contrary and shows that achieving high performance with GD tools requires careful consideration of study setup and initial conditions. It is further shown that, when coupled with the inherent variability of AM parts, the potential variation in the performance of the design output can be significant, with poorer designs achieving only a fraction of that of higher-performing designs. This investigation shows how AM by Material Extrusion (MEX), which is used to manufacture components with polylactic acid (PLA), varies through different design pathways, bridging MEX and GD. Through a practical study across nine independently generated designs, the breadth of performance—due to initial GD conditions and MEX part strength unpredictability—is shown to reach 592%. This result suggest that current GD tools, including their underlying workflows and algorithms, are not sufficiently understood for users to be able to generate consistent solutions for an input case. Further, the study purports that training and consideration on GD setup are necessary to apply GD toolsets to achieve high-performing designs, particularly when applied in the context of MEX.
Reliability of Automated Intracranial Volume Measurements by Synthetic Brain MRI in Children
Authors: Weiss Veronika , Vishwanathan Nathan , Dutschke Anja , Stranger Nikolaus , Scherkl Mario , Nagy Eszter , Ciornei-Hoffman Andreea , Tschauner Sebastian
Published: May 2024

(1) Background: Hydrocephalus poses challenges in pediatric neuroimaging, and conventional MRI methods have limitations regarding its accurate quantification. Synthetic MRI (SyMRI) offers a promising automated solution to assess intracranial compartment volumes. However, its clinical utility in pediatric patients remains underexplored. Our study aims to assess the accuracy and reliability of automated CSF volume measurements using SyMRI in children and adolescents, comparing them with manual measurements and human expert ratings. (2) Methods: A single-center retrospective study included 124 pediatric patients undergoing cranial MRI with SyMRI. CSF, brain parenchyma, and intracranial volumes were measured using both automated SyMRI and manual methods. Human radiologists assessed hydrocephalus subjectively. (3) Results: Correlations between manual and SyMRI volume evaluations were significant. Human raters demonstrated good agreement on hydrocephalus ratings among themselves (Fleiss’ kappa = 0.66, p < 0.001) but only moderate agreement with the SyMRI method (Cohen’s kappa = 0.45, p < 0.001). SyMRI volumes were systematically tendentially higher in SyMRI (CSF p = 0.005; BPV and ICV p < 0.001). (4) Conclusions: Our findings highlight SyMRI’s reliability in assessing hydrocephalus and intracranial volumes in pediatric cases. Despite some differences from manual measurements, the strong correlation suggests its clinical viability.
Virulence of Different Entomopathogenic Fungi Species and Strains against the Hazel Longhorn Beetle Oberea linearis (Coleoptera: Cerambycidae)
Authors: Mantzoukas Spiridon , Lagogiannis Ioannis , Kitsiou Foteini , Eliopoulos Panagiotis A. , Petrakis Panagiotis
Published: May 2024

The aim of this study was to investigate alternative methods to control longhorn beetle (Oberea linearis) infestations in walnut orchards. Wild isolates of entomopathogenic fungi obtained from soil samples from Greece and Cyprus were tested for their efficacy against adults and larvae of O. linearis. Insect populations were acquired from a heavily infested walnut orchard and individuals were placed in Petri dishes provided with ground walnut wood for larvae and fresh leaves for adults. The tested insects were subjected to 16 different wild isolates from the genera Beauveria, Cordyceps, Metarhizium, and Purpureocillium, where 108 conidia/mL were applied by spraying, and insects were monitored daily for 16 days. The results showed that all the tested fungi resulted in a mortality rate of 66–100%, with Cordyceps fumosorosea exhibiting the highest virulence, causing complete mortality to both larvae and adults. These findings suggest that the management of O. linearis, which has traditionally relied on chemical applications, could transition to an organic approach by utilizing entomopathogenic fungi.
Partial Oscillation Flow Control on Airfoil at Low Reynolds Numbers
Authors: Li Guanxiong , Wang Jingyu
Published: May 2024

Among the critical factors contributing to the decline in the aerodynamic performance of near-space aircraft under low Reynolds number conditions, a significant one lies in the occurrence of laminar separation bubbles forming on the wings. Within the scope of this investigation, the primary research methodology adopted involves utilizing an unsteady numerical simulation technique rooted in a spring-smoothed dynamic grid system. This study meticulously examines the aerodynamic attributes and flow patterns exhibited by an airfoil undergoing partial oscillation, thereby elucidating the underlying mechanisms through which such oscillations lead to enhanced lift and diminished drag forces. The outcomes of this research reveal that the imposition of partial oscillation engenders a noteworthy augmentation of 4.9% in the lift coefficient of the airfoil, concurrent with a substantial diminution of 15.3% in its drag coefficient when juxtaposed against the non-deforming counterpart. The oscillation frequency exerts a profound influence on both the onset location of transition and the extent of the laminar separation bubble’s development. As the oscillation frequency escalates, it follows an initial ascending trend in the lift coefficient of the airfoil, followed by a subsequent decline, whereas the drag coefficient exhibits an initial decrement prior to a rising tendency, thus indicating the existence of an optimal frequency point where the airfoil achieves its most favorable aerodynamic characteristics. It is observed that the flow control effects are optimally pronounced when the region subjected to partial oscillation is proximate to the airfoil’s leading edge or situated precisely at the centroid of the laminar separation bubble.
Application of Response Surface Methodology for Fermented Plant Extract from Syzygium aromaticum L. (Myrtaceae): Optimisation of Antioxidant Activity, Total Polyphenol Content, and Lactic Acid Efficiency
Authors: Kucharska Edyta , Zagórska-Dziok Martyna , Bilewicz Paweł , Kowalczyk Sebastian , Jurkiewicz Martyna , Wachura Dominika , Miądlicki Piotr , Pełech Robert
Published: May 2024

Syzygium aromaticum L. Myrtaceae is one of the plants rich in bioactive compounds that have beneficial effects on the skin. Fermented plant extracts (FPEs) obtained from this plant have recently been exploited as new cosmetic ingredients. The concept of our study was related to the use of clove buds in the fermentation process in order to obtain new cosmetic raw materials with high antioxidant potential. The focus was on evaluating antioxidant activity (AA), total polyphenol content (TPC), and lactic acid efficiency (LAe). For this purpose, the most favourable technological parameters of the fermentation process of clove buds were determined, including the type of microorganisms, initial sugar content, plant raw material content, and fermentation time. The most favourable parameters were correlated with the optimal parameters, which were determined based on response surface methodology (RSM). Based on DPPH and Folin–Ciocalteu assays and GC-MS analysis, optimal points of antioxidant activity against reactive oxygen species (analysed with RSM) were successfully selected, enabling quantitative mathematical representations. The optimisation revealed that using a strain of Lactobacillus rhamnosus MI-0272 in lactic fermentation and plant material (6.40%) and beet molasses (3.20%) results in the highest antioxidant potential of FPE (33.90 mmol Tx/L) and yielding LA with the highest efficiency (96%). The optimised FPE had higher polyphenol content (11.60 mmol GA/L ± 0.14), chelating and antioxidant activity (0.32 mmol Fe2+/L ± 0.01 and 11.60 mmol Tx/L ± 0.09), and Fe3+ ion reduction (49.09 mmol Fe3+/L ± 0.16) than the PE. In addition, the possibility of using the spent plant material remaining after the extraction process to prepare activated carbons capable of treating wastewater was investigated.
Detecting False Data Injection Attacks Using Machine Learning-Based Approaches for Smart Grid Networks
Authors: Abudin MD Jainul , Thokchom Surmila , Naayagi R. T. , Panda Gayadhar
Published: May 2024

Current electricity sectors will be unable to keep up with commercial and residential customers’ increasing demand for data-enabled power systems. Therefore, next-generation power systems must be developed. It is possible for the smart grid, an advanced power system of the future, to make decisions, estimate loads, and execute other data-related jobs. Customers can adjust their needs in smart grid systems by monitoring bill information. Due to their reliance on data networks, smart grids are vulnerable to cyberattacks that could compromise billing data and cause power outages and other problems. A false data injection attack (FDIA) is a significant attack that targets the corruption of state estimation vectors. The primary goal of this paper is to show the impact of an FDIA attack on a power dataset and to use machine learning algorithms to detect the attack; to achieve this, the Python software is used. In the experiment, we used the power dataset from the IoT server of a 10 KV solar PV system (to mimic a smart grid system) in a controlled laboratory environment to test the effect of FDIA and detect this anomaly using a machine learning approach. Different machine learning models were used to detect the attack and find the most suitable approach to achieve this goal. This paper compares machine learning algorithms (such as random forest, isolation forest, logistic regression, decision tree, autoencoder, and feed-forward neural network) in terms of their effectiveness in detecting false data injection attacks (FDIAs). The highest F1 score of 0.99 was achieved by the decision tree algorithm, which was closely followed by the logistic regression method, which had an F1 score of 0.98. These algorithms also demonstrated high precision, recall, and model accuracy, demonstrating their efficacy in detecting FDIAs. The research presented in this paper indicates that combining logistic regression and decision tree in an ensemble leads to significant performance enhancements. The resulting model achieves an impressive accuracy of 0.99, a precision of 1, and an F1 score of 1.
“CANTINA 5.0”—A Novel, Industry 5.0-Based Paradigm Applied to the Winemaking Industry in Italy
Authors: Venturi Francesca , Tonacci Alessandro , Ascrizzi Roberta , Sansone Francesco , Conte Raffaele , Pala Anna Paola , Tarabella Angela , Sanmartin Chiara , Taglieri Isabella , Marangoni Roberto , Bietresato Marco , Comuzzo Piergiorgio , Zironi Roberto , Zironi Alessandro , Ciotti Gellio , Gubiani Rino
Published: May 2024

The concept of Industry 5.0 is novel from many points of view, as it fosters the transition to a sustainable, human-centric, resilient European industry. To reach this ambitious goal, it is necessary to act simultaneously on many fronts, starting from guaranteeing basic human rights (e.g., privacy, independence, and dignity) and paying attention to the circular economy and energy efficiency. Despite being difficult to adopt in its general formulation, this concept can be scaled up to specific fields, thus producing increased value with repercussions to the whole industrial process. The winemaking industry puts Italy at the forefront globally, as it is also among the key components of the whole national agrifood/agritech value chain. However, the Italian winemaking industry is quite fragmented, with a heterogeneous mix of small and medium enterprises (SMEs) and with large companies having opposite approaches to the production process, both in terms of involvement of human resources and seasonality of efforts, due to the existing climate differences nationwide. This fact makes the adoption of common practices even harder but makes the benefits of projects promoting this process innovation more tangible. In such a framework, CANTINA 5.0 seeks to fill in this important gap, promoting the Industry 5.0 principles in a selected group of SMEs and large companies from two different Italian areas featuring different climate conditions and different seasonality, hence characterized by different wine harvesting periods and types of wine production. The present article deals with the description of this paradigm in its single parts, including the use of questionnaires and smart tools to detect the health and well-being state of factory workers and winemakers, the use of well-grounded (including gas chromatography/mass spectrometry) and novel (e.g., based on the Internet-of-Things) environmental monitoring tools applied to the cellars/production departments, and the sensory analysis of the end-products, also leveraging the chemical and emotional characteristics of wines produced using the Industry 5.0 approach.
Synthesis and Biological Studies of New 2-Benzoxazolinone Derivatives as Antibacterial Agents
Authors: Šiugždaitė Jūratė , Lelešius Raimundas , Grybaitė Birutė , Vaickelionienė Rita , Mickevičius Vytautas
Published: May 2024

In the present study, new series of benzoxazolin-2-one linked to a variety of hydrazones and azoles were synthesized and assessed for their antibacterial properties against different bacterial microorganisms. All the synthesized target compounds were characterized by 1H NMR, 13C NMR and IR spectroscopy, and elemental analysis as well. The antibacterial activity of the synthesized compounds was evaluated according to the bacteriostatic and bactericidal activity against the tested pathogen strains by determining the minimum inhibition (MIC) and minimum bactericidal (MBC) concentrations and MBC/MIC ratios. The MIC was evaluated by the broth dilution and the MBC was evaluated by plating methods. The in vitro analysis suggested that some compounds, namely, amide, 5-chlorobenzimidazole, hydrazones with a 3-chloro substitution on the additional phenyl ring, and hydrazones with 2-furyl and 5-nitro-2-furyl substituents, demonstrated wide antibacterial activity against Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Salmonella Enteritidis. The most sensitive strains appeared to be Gram-negative E. coli and Gram-positive B. subtilis, while S. aureus showed some resistance. The most resistant pathogen was found to be S. enteritidis. The remaining compounds demonstrated moderate to low antibacterial potential. The research results have shown that benzoxazolinone-based derivatives are suitable for the development of a library of compounds and can be used in the future development of antibacterial drugs against various Gram-positive and Gram-negative pathogens, which is of great importance in therapy practice.
Strategic Integration of Drone Technology and Digital Twins for Optimal Construction Project Management
Authors: Salem Tareq , Dragomir Mihai , Chatelet Eric
Published: May 2024

This research aims to develop an integrated approach to construction project management by integrating digital technology into monitoring and surveillance operations. Through the use of drones and image processing software, data can be updated regularly and accurately about the progress at the construction site, allowing managers and decision makers to have a clear view of the current situation and make effective decisions based on accurate. In addition, this approach contributes to improving communication and coordination among project team members, as data and images can be easily and effectively shared, reducing opportunities for error and enhancing effective interaction among different parties. Using digital twin technologies, planning and forecasting processes can also be improved, as comprehensive analysis of digital data provides a deeper understanding of project dynamics, identifies potential risks, and enables appropriate preventive measures to be taken. In conclusion, the integration of digital twins and the use of drones in construction projects represent a significant step towards achieving smarter and more efficient management, and successfully achieving the defined goals with greater effectiveness.
Analysis of Altitude and Ambient Temperature Effects on the Reactivity of Oxidation Catalysts in the Presence of H2
Authors: Serrano José Ramón , Piqueras Pedro , Sanchis Enrique José , Conde Carla
Published: May 2024

Worldwide emission standards are now required to cover engine operation under extreme ambient conditions, which affect the raw emissions and the efficiency of the exhaust aftertreatment systems. These regulations also target new combustion technologies for decarbonization, such as neat hydrogen (H2) combustion or dual-fuel strategies, which involve a challenge to the analysis of exhaust aftertreatment system requirements and performance. This work addresses the impact of high altitude and low ambient temperature conditions on the reactivity of an oxidation catalyst in the presence of H2. A reaction mechanism is proposed to cover the main conversion paths of CO, HC, and H2, including the formation and consumption of high-energy surface reaction intermediates. The mechanism has been implemented into a faster-than-real-time reduced-order model for multi-layer washcoat honeycomb catalytic converters. The model was utilized to investigate the effect of H2 concentration on the reactivity of CO and HC within the catalyst under various operating and ambient conditions. By applying the model and examining the selectivity towards different reaction pathways in the presence of H2, insights into surface intermediates and reactivity across different cross-sections of the monolith were obtained. This analysis discusses the underlying causes of reactivity changes promoted by H2 and its relative importance as a function of driving boundary conditions.
Coopetition with the Industrial IoT: A Service-Dominant Logic Approach
Authors: da Silva Agostinho , Cardoso Antonio J. Marques
Published: May 2024

Abstract: This research addresses the critical gap in enabling effective coopetition networks through technological innovation with the development of Cockpit4.0+, an Industrial Internet of Things (IIoT) artefact tailored for small- and medium-sized enterprises (SMEs). By employing the principles of Service-Dominant Logic (S-D Logic) and leveraging the Design Science Research (DSR) methodology, Cockpit4.0+ represents a pioneering approach to incorporating the IIoT within ecosystems for value co-creation. This facilitates competition and cooperation among firms, enhancing the operational dynamics within SME networks. Evaluated by experts in the ornamental stone sector, a significant sector of the Portuguese economy, the system demonstrated a positive functional acceptance rate of 78.9%. An experimental test was conducted following the positive preliminary functional evaluation of Cockpit4.0+, especially among more digitally advanced companies. The findings revealed that the on-time delivery performance under current best practices (CB.Ps) was 67.1%. In contrast, implementing coopetition network practices (CN.Ps) increased on-time delivery to 77.5%. These positive evaluations of Cockpit4.0+ underscore the practical applicability of S-D Logic and provide fresh insights into the dynamics of coopetition, particularly beneficial for SMEs. Despite its promising results, the real-world efficacy of IIoT systems like Cockpit4.0+ requires further empirical studies to verify these findings. Future research should focus on examining the scalability of Cockpit4.0+ and its adaptability across various sectors and enhancing its cybersecurity measures to ensure its long-term success and broader adoption.
Five Large 13th Century C.E. Volcanic Eruptions Recorded in Antarctica Ice Cores
Authors: Cole-Dai Jihong , Brandis Derek L. , Ferris Dave G.
Published: May 2024

Major explosive volcanic eruptions impact the climate by altering the radiative balance of the atmosphere and through feedback mechanisms in the climate system. The extent of the impact depends on the magnitude (aerosol mass loading) and the number or frequency of such eruptions. Multiple Antarctica ice core records of past volcanic eruptions reveal that the number (5) of major eruptions (volcanic sulfate deposition flux greater than 10 kg km−2) was the highest in the 13th century over the last two millennia. Signals of four of the five eruptions are dated to the second half of the century, indicating consecutive major eruptions capable of causing sustained climate impact via known feedback processes. The fact that signals of four corresponding eruptions have been found in a Greenland ice core indicates that four of the five 13th century eruptions were probably by volcanoes in the low latitudes (between 20° N and 20° S) with substantial aerosol mass loading. These eruptions in the low latitudes likely exerted the strongest volcanic impact on climate in the last two millennia.
Advanced Understanding of Sea Surface Cooling Off Northeastern Taiwan to Tropical Cyclone by Using Numerical Modeling
Authors: Wu Hsin-Ju , Zheng Zhe-Wen
Published: May 2024

From 2001 to 2020, three typhoons with similar moving paths and intensities were found to trigger markedly different cooling off northeastern Taiwan. They were typhoons Utor (2001), Nuri (2008), and Hagupit (2008), which led to maximum sea surface temperature (SST) cooling temperatures of 8.8, 2.7, and 1.4 °C, respectively. The drastic cooling discrepancy implies that the existing understanding of the key mechanism leading to the cooling off northeastern Taiwan could be insufficient. For further exploring the key reason(s) contributing to the marked discrepancy, a regional oceanic modeling system (ROMS) was used to reconstruct the background oceanic environment corresponding to three typhoon passages. Results show that the wide radius of maximum winds of typhoon Utor contributes to the strongest SST cooling by enhancing the Kuroshio intrusion (KI) onto the shelf northeast of Taiwan. Heat budget diagnostics explain why including tidal forcing can substantially promote SST cooling. The process was associated mainly with a stronger vertical advection tied to the influence of de-stratification by tidal mixing. Finally, warmer Taiwan Strait currents, driven by wind forcing the typhoons to pass zonally through the north South China Sea, intruded clockwise into the Longdong coast and accelerated the recovery of sea surface cooling around Longdong.
Spatiotemporal Exposure Assessment of PM2.5 Concentration Using a Sensor-Based Air Monitoring System
Authors: Shin Jihun , Woo Jaemin , Choe Youngtae , Min Gihong , Kim Dongjun , Kim Daehwan , Lee Sanghoon , Yang Wonho
Published: May 2024

Sensor-based air monitoring instruments (SAMIs) can provide high-resolution air quality data by offering a detailed mapping of areas that air quality monitoring stations (AQMSs) cannot reach. This enhances the precision of estimating PM2.5 concentration levels for areas that have not been directly measured, thereby enabling an accurate assessment of exposure. The study period was from 30 September to 2 October 2019 in the Guro-gu district, Seoul, Republic of Korea. Four models were applied to assess the suitability of the SAMIs and visualize the temporal and spatial distribution of PM2.5. Assuming that the PM2.5 concentrations measured at a SAMI located in the center of the Guro-gu district represent the true values, the PM2.5 concentrations estimated using QGIS spatial interpolation techniques were compared. The SAMIs were used at seven points (S1–S7) according to the distance. Models 3 and 4 accurately estimated the unmeasured points with higher coefficients of determination (R2) than the other models. As the distance from the AQMS increased from S1 to S7, the R2 between the observed and estimated values decreased from 0.89 to 0.29, respectively. The auxiliary installation of SAMIs could resolve regional concentration imbalances, allowing for the accurate estimation of pollutant concentrations and improved risk assessment for the population.
Mathematical Model of the Evolution of a Simple Dynamic System with Dry Friction
Authors: Alaci Stelian , Ciornei Florina-Carmen , Lupascu Costica , Romanu Ionut-Cristian
Published: May 2024

A simple dynamic system with dry friction is studied theoretically and numerically. Models of systems including dry friction are not easily obtained, as defining the relationship between the friction force and the relative velocity presents a significant challenge. It is known that friction forces exhibit notable discontinuities when there is a change in the direction of motion. Additionally, when the relative motion ceases, the friction force can assume any value within a certain range. In the literature, numerous models of dry friction are presented, and most of them assume a biunivocal dependency of the friction force with respect to relative velocity. The dynamic system considered here is a tilted rod with spherical ends, initially at rest. Dry friction forces are evident at the contact point with the horizontal plane. The ball–plane contact highlights the rolling friction or/and sliding friction. The problem is theoretically solved after adopting one of the two cases of friction: rolling friction or sliding friction. The nonlinear differential equations of motion have been derived, along with expressions for the magnitude of the normal reaction and the friction force. The results of the model are displayed graphically for three different sets of values for the coefficient of friction. It is revealed that there is a critical value of the coefficient of friction that determines the transition from rolling to sliding regimes. To validate the theoretical model, dynamic simulation software was utilised. The excellent match between the theoretical predictions and the results from the numerical simulation confirms the accuracy of the proposed analytical solution.
Rapid Estimation of Static Capacity Based on Machine Learning: A Time-Efficient Approach
Authors: Son Younggill , Choi Woongchul
Published: May 2024

With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical than ever. A crucial step for battery reuse or recycling is the precise estimation of static capacity at retirement. Traditional methods are time-consuming, often taking several hours. To address this issue, a machine learning-based approach is introduced to estimate the static capacity of retired batteries rapidly and accurately. Partial discharge data at a 1 C rate over durations of 6, 3, and 1 min were analyzed using a machine learning algorithm that effectively handles temporally evolving data. The estimation performance of the methodology was evaluated using the mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE). The results showed reliable and fairly accurate estimation performance, even with data from shorter partial discharge durations. For the one-minute discharge data, the maximum RMSE was 2.525%, the minimum was 1.239%, and the average error was 1.661%. These findings indicate the successful implementation of rapidly assessing the static capacity of EV batteries with minimal error, potentially revitalizing the retired battery recycling industry.
Dislodgment Effects of Different Cage Arrangements in Posterior Lumbar Interbody Fusion: A Finite Element Study
Authors: Yang Shih-Chieh , Wu Chih-Lin , Tu Yuan-Kun , Liu Pao-Hsin
Published: May 2024

The vertebral cage has been widely used in posterior lumbar interbody fusion. The risk of cage dislodgment is high for patients undergoing lumbar fusion surgery. Therefore, the main objective of this study was to use a lumbar fusion model to investigate the effects of cage dislodgment on different cage arrangements after PLIF. Finite element analysis was used to compare three PEEK cage placements, together with the fibula-type cage, with respect to the four kinds of lumbar movements. The results revealed that a horizontal cage arrangement could provide a better ability to resist cage dislodgment. Overall lumbar flexion movements were confirmed to produce a greater amount of cage slip than the other three lumbar movements. The lower part of the lumbar fusion segment could create a greater amount of cage dislodgment for all of the lumbar movements. Using an autograft with a fibula as a vertebral cage cannot effectively reduce cage dislodgment. Considering the maximum movement type in lumbar flexion, we suggest that a horizontal arrangement of the PEEK cage might be considered when a single PEEK cage is placed in the fusion segment, as doing so can effectively reduce the extent of cage dislodgment.
The Peroxisome Proliferator-Activated Receptors of Ray-Finned Fish: Unique Structures, Elusive Functions
Authors: Boukouvala Evridiki , Krey Grigorios
Published: May 2024

The Actinopterygian and specifically the Teleostean peroxisome proliferator-activated receptors (PPARs) present an impressive variability and complexity in their structures, both at the gene and protein levels. These structural differences may also reflect functional divergence from their mammalian homologs, or even between fish species. This review, taking advantage of the data generated from the whole-genome sequencing of several fish species, highlights the differences in the primary structure of the receptors, while discussing results from the literature pertaining to the functions of fish PPARs and their activation by natural and synthetic compounds.