bluuebunny/crossref_metadata_2025 huggingface dataset:
CarrDet: Attention–Symmetry-Based Microscopic Carrier Detection for Wastewater Treatment
Authors: Chen Huizhen , Liu Shuning , Liu Rongkai , Shi Heyuan , Hu Chao , Shi Ronghua
Published: June 2024

The carrier is one of the key components used in wastewater treatment, which can enrich microorganisms at the surface to improve the amount of biomass in the reactor. Monitoring and adjusting the number of carriers is a key component for the processing efficiency of the ecosystem, which directly impacts wastewater treatment effectiveness. Therefore, carrier detection in wastewater microscopic images is important in the urban domestic wastewater treatment process. The current process to detect carriers is operator-dependent, which is time-consuming and expensive. Though a number of general object or cell detection approaches are used for this task, their effectiveness is limited because the carrier and background are similar and there are defective carriers as background noise. In this paper, we propose CarrDet, the first deep learning-based carrier detection framework for wastewater treatment. CarrDet uses a carrier feature block attention module and a symmetry-based defective carrier detection module to detect carriers with shallow edges and reduce false positives caused by defective carriers, respectively. To evaluate CarrDet, we propose a carrier dataset of 600 wastewater microscopic images, manually annotated by experts. Compared with state-of-the-art object detection methods, CarrDet shows superior performance in terms of both accuracy and speed, achieving a mAP of 94.32 and an IPS of 4.93. We employed CarrDet to confirm the detection results of 621 wastewater microscopic images, which were detected by inexperienced engineers who are new to the field. CarrDet added 398 unrecognized carriers with shallow edges and corrected 273 incorrect manual annotations in 5 min, which emphasizes the efficiency and practicality of CarrDet for practical business scenarios.
Improving the Design of a Multi-Gear Pump Switchgear Using CFD Analysis
Authors: Zharkevich Olga , Nikonova Tatyana , Gierz Łukasz , Reshetnikova Olga , Berg Alexandra , Warguła Łukasz , Berg Andrey , Wieczorek Bartosz , Łykowski Wiktor , Nurzhanova Oxana
Published: June 2024

Gear pumps are hydraulic machines capable of transferring energy and performing work in pumping fluid. This study presents an analysis of the hydrodynamic model of an external multiple gear pump in order to analyze the fluid flow in combinations of single and different viscosities at the same and different pressures and speeds. Solidworks Flow Simulation 2016 was used to analyze fluid flow. When the radius of the rounding on the collector inner surface is increased from 3 to 15 mm, the pressure drop decreases by 13%. When the radius of the manifold is 3 mm, cavitations are observed. With a liquid distribution system with four input ports and one outlet port in the top cover, the gear pump can handle liquids of viscosity classes 5 to 10. The speed should not exceed 1200 rpm if the liquid has a kinematic viscosity of 10 cSt. The pressure drop and velocity distribution of the liquid in the pressure and suction lines are the same. When the speed changes from 400 to 1200 rpm, the pressure drop increases five times, and the velocity increases three times. At a constant speed of 1000 rpm and an inlet pressure of 10 MPa but with different viscosities, the pressure drop decreases 8 times, and the speed increases 1.5 times. When the inlet pressure is 6 to 24 MPa, with constant speed and the same viscosity, the pressure drop and fluid velocity practically do not change. The dependence of pressure drop on the number of revolutions and radius of the rounding of the inner surface of the collector is statistically significant.
Enhancing Rock Blasting Efficiency in Mining and Tunneling: A Comparative Study of Shear-Thickening Fluid Stemming and Plug Device Performance
Authors: Baluch Khaqan , Park Heon-Joon , Kim Jung-Gyu , Ko Young-Hun , Kim Gunwoong
Published: June 2024

Stemming has a major impact on energy containment inside a blasting hole and is essential for increasing the efficacy of explosive charges in rock blasting. This method is essential in many fields, including road project development, mining, tunneling, and underground construction. By fortifying the confinement of the energy generated by a loaded explosive charge in a blasting hole, stemming increases the fragmentation of rock. Improper or missing stemming leads to the gas escaping in advance from blast holes, resulting not only in the wastage of explosive energy and poor fragmentation but also in environmental problems such as ground vibration, noise, flying rocks, back breaks, and air blasts. When the process to keep gases inside blast holes is not performed correctly or is skipped, it can waste explosive energy and produce poorly fragmented rocks. This also causes problems like high ground vibrations, loud noise, flying rocks, cracks behind the blast area, and strong air shocks. In this study, a shock chamber blasting experiment and numerical analysis were conducted to evaluate the pressure confinement effect of stemming material and plug devices in a blast hole. The resulting stemming effect was compared with that of a shear-thickening fluid (STF)-based stemming material currently under development and sand, which is a commonly used blast stemming material. To evaluate the enhancement of the confinement effect inside the pressurized blast hole, three types of stemming plugs were adopted. The blasting experiment and numerical simulation results revealed that the STF-based stemming materials were superior to conventional stemming materials. In addition, the STF-based stemming and plug system can prevent detonation gas from prematurely overflowing the borehole and effectively prolong the action time and scope of the detonation gas in the borehole.
A Collaborative System Design for Avoiding and Removing the Unexpected Obstacles Encountered during Wheelchair Navigation
Authors: Kırmızıbiber Abdullah , Gökgöz Türkay
Published: June 2024

In this study, we designed a system that cooperates with users to always provide the most up-to-date map and the most suitable route and to cooperate with disability units to ensure that unexpected obstacles on the route are removed. It is believed that this system will contribute to (1) eliminating obstacles more quickly and preventing other people with disabilities from being aggrieved until the obstacles are removed; (2) increasing awareness of the responsibility towards people with disabilities in society; (3) greater integration of people with disabilities; and (4) increasing the economic and social welfare of society. The design process includes analysis of the current situation, data acquisition, web mapping, mobile application development, and experimental testing phases. The system successfully passed the tests. However, the optimum level of expected benefits of the system depends on users’ consistent use of the mobile application complaint tool and authorities’ consistent evaluation of the complaints received. As the number of mobile application users increases, the number of complaints will gradually increase, yet after a while, as the awareness and sensitivity of society on this issue gradually increase, the number of complaints will gradually decrease, and the expected benefits will be achieved.
A Tent-Lévy-Based Seagull Optimization Algorithm for the Multi-UAV Collaborative Task Allocation Problem
Authors: Zhou Zhao , Liu Huan , Dai Yongqiang , Qin Lijing
Published: June 2024

With the rapid advancement of unmanned aerial vehicle technology, the extensive application of multiple unmanned aerial vehicle systems in agriculture has led to significant innovations and benefits. Addressing the challenge of task allocation for multiple unmanned aerial vehicles, the primary objective is to minimize the total time required for unmanned aerial vehicles to return to their starting point after task completion. To tackle this issue, a mathematical model for the multi-constrained multiple unmanned aerial vehicle collaborative task allocation problem is developed. To efficiently solve this model, we propose an enhanced Seagull Optimization Algorithm, which integrates the Tent chaotic mapping strategy and the Lévy flight strategy. The Tent chaotic mapping helps the algorithm avoid becoming trapped in local optima, while the Lévy flight strategy, employed during the seagull attack phase, enhances the algorithm’s diversity and its ability to escape local optima. Additionally, the spiral coefficient is refined to balance the coordination between global and local searches. Simulation experiments demonstrate that the proposed algorithm can swiftly and effectively identify a reasonable task allocation scheme for solving the multi-constrained multi-UAV collaborative task allocation problem.
Numerical Analysis of Tooth Contact and Wear Characteristics of Internal Cylindrical Gears with Curved Meshing Line
Authors: Jia Chao , Zhang Ge , Li Guoju
Published: June 2024

In order to improve the contact strength and reduce the sliding friction of the gear pair, an internal cylindrical gear pair with a curved meshing line is studied in this paper. Firstly, a curved meshing line is designed. The tooth profiles of the internal gear pair with the designed meshing line are calculated by using differential geometry and the gear meshing principle. Secondly, a wear model is established by combining the finite element method and the Archard wear formula. Then, a numerical simulation is conducted; the relative curvature, sliding coefficient, sliding distance, maximum contact pressure, transmission error, and wear depth are calculated. Ultimately, the variation law of tooth surface wear of new gear with and without installation errors is observed under different stress cycles. On this basis, the influence of tooth modification on tooth surface wear is further researched. Through the results, the advantages of the introduced novel internal cylindrical gears in wear resistance are further demonstrated. The study in this paper provides new research ideas and methods for gear wear research and gear design.
PUF and Chaotic Map-Based Authentication Protocol for Underwater Acoustic Networks
Authors: Xie Qi , Yao Ye
Published: June 2024

A secure and effective authentication and communication scheme between users and underwater sensors plays an important role in improving the detection and utilization of marine resources in underwater acoustic networks (UANs). However, due to the energy limitations and susceptibility to capture of underwater sensors and gateways, it is necessary to design a lightweight authentication protocol that can resist capture of sensors and gateways during attacks. In this paper, a lightweight authentication protocol for UANs based on the Physical Unclonable Function (PUF) and chaotic map is proposed. We used the advantages of PUF to resist sensors and gateways being captured in attacks and the chaotic map to achieve lightweight authentication because the computational cost of the chaotic map is almost one-third that of Elliptic Curve Cryptography (ECC). Additionally, we used the formal security proof in the random oracle model to prove the security of the proposed scheme. Our scheme was more secure and efficient compared with some other related schemes in terms of security and performance requirements, and the proposed scheme is suitable for UANs.
A Method to Evaluate the Maturity Level of Robotization of Production Processes in the Context of Digital Transformation—Polish Case Study
Authors: Hetmanczyk Mariusz Piotr
Published: June 2024

This paper puts forth a systematic approach to evaluating the maturity level of the robotization of production processes in the context of digital transformation for manufacturing companies. The method was developed to address the absence of a sector-specific framework for assessing robotization maturity growth, in line with the Industry 5.0 guidelines (incorporating sustainability, the circular economy, and human-centeredness). The survey covers six core areas for manufacturing companies: the automation and robotization of production processes, digitization of warehouse processes, flexibility and intralogistics, and end-to-end integration of key data management processes. The study aimed to advance digitalization through improved robotization maturity. The study surveyed 200 small and medium-sized businesses operating in Poland from 2022 to 2024. The study presents a method to assess enterprise operational maturity, covering current and planned levels and development plans for the next three years.
Compensation Observer-Based Adaptive Output Feedback Control for Multi-Agent Systems
Authors: Liu Zhaoyuan , Liu Ye
Published: June 2024

This study presents a modified compensating observer control strategy for nonlinear multi-agent systems affected by unknown hysteresis signal loops. Compared to conventional high-gain observers, this approach introduces a novel compensation signal, effectively reducing the tracking error of traditional observers. Then, by utilizing a backstepping method, an adaptive output feedback controller is designed, such that the tracking error converges to the small neighborhood around the origin. Simulation experiments with and without the compensation term demonstrate that this control strategy can effectively reduce error, but it increases input chattering to some extent.
Determination of the Ground Reaction Curve for an Elasto-Plasto-Fractured Rock Mass
Authors: Kamiński Paweł , Otto Aleksandra , Dawidziuk Piotr , Malinowski Leszek , Stecuła Kinga , Dyczko Artur
Published: June 2024

Polish National Standards for underground excavation support design outline the deformational pressure model for assessing loads acting on the support systems of deep underground excavations. They distinguish two different rock mass models, highlighting the pivotal role of the critical longitudinal strain of the rock mass in appropriate model selection. A comparison between the design method given by Polish Standards and the widely recognized convergence–confinement method, consisting of a ground reaction curve (GRC), longitudinal displacement profile (LDP), and support characteristics curve (SCC), reveals the advantages of the latter in capturing the three-dimensional nature of underground excavations. The following study presents a method for establishing a GRC curve for the elasto-plasto-fractured rock mass model, featured in Polish Standards, demonstrating its applicability through analyses of a typical circular roadway under varying rock mass conditions. Practical implications are discussed, including the design of yielding steel arches as the primary support system and the calculation of safety factors for both the support system and the surrounding rock mass, considered as a natural support component. Overall, the study contributes to a deeper understanding of the actions of rock masses in the vicinity of excavations located at great depths. Furthermore, it provides practical insights for engineering applications.
Edge-Guided Hierarchical Network for Building Change Detection in Remote Sensing Images
Authors: Yang Mingzhe , Zhou Yuan , Feng Yanjie , Huo Shuwei
Published: June 2024

Building change detection monitors building changes by comparing and analyzing multi-temporal images acquired from the same area and plays an important role in land resource planning, smart city construction and natural disaster assessment. Different from change detection in conventional scenes, buildings in the building change detection task usually appear in a densely distributed state, which is easy to be occluded; at the same time, building change detection is easily interfered with by shadows generated by light and similar-colored features around the buildings, which makes the edges of the changed region challenging to be distinguished. Aiming at the above problems, this paper utilizes edge information to guide the neural network to learn edge features related to changes and suppress edge features unrelated to changes, so as to accurately extract building change information. First, an edge-extracted module is designed, which combines deep and shallow features to supplement the lack of feature information at different resolutions and to extract the edge structure of the changed features; second, an edge-guided module is designed to fuse the edge features with different levels of features and to guide the neural network to focus on the confusing building edge regions by increasing the edge weights to improve the network’s ability to detect the edges that have changed. The proposed building change detection algorithm has been validated on two publicly available data (WHU and LEVIR-CD building change detection datasets). The experimental results show that the proposed model achieves 91.14% and 89.76% in F1 scores, respectively, demonstrating superior performance compared to some recent learning change detection methods.
A Toolkit of Biophilic Interventions for Existing Schools to Enhance Student and Faculty Health and Performance
Authors: Leif Kari , Loftness Vivian
Published: June 2024

School learning environments play a crucial role in both student and faculty outcomes; however, the limited funding allocated to public school facilities can result in poor environmental conditions which can hinder occupant health and performance. Existing school facilities must then explore affordable retrofit strategies that can effectively improve health and performance outcomes. The emerging field of biophilic design offers significant potential for improving existing school environments with benefits for both the students and faculty. Through case study research, this study proposes a toolkit of 42 biophilic retrofits for existing K-12 schools in a set of stakeholder cards that illustrate precedents, known impacts, and their relevance to high-performance schools. Additionally, a stakeholder card sorting study was conducted to establish the perceived viability and impact of each strategy. The findings reveal that biophilic retrofit design strategies are perceived by school community stakeholders to be impactful with varying levels of affordability. These findings further demonstrate that a toolkit of biophilic interventions for K-12 schools will offer invaluable insights to improve student and faculty conditions.
Analysis of Spatial and Temporal Changes in FVC and Their Driving Forces in the Inner Mongolia Section of the Yellow River Basin
Authors: He Danni , Wang Yong , Wang Dengji , Yang Yahui , Fang Wenya , Wang Yu
Published: June 2024

To investigate the spatial and temporal changes in fractional vegetation coverage (FVC) and their driving forces in different regions of the Inner Mongolia section of the Yellow River Basin, this paper observed the spatial trends and stability of FVC in these regions based on the MOD13Q1 information regarding the 2000–2020 period as a data source. It used the dimidiate pixel model to invert FVC, and based on the centre of gravity migration model, the coefficient of variation and the Mann–Kendall and Sen’s slope estimator test, it studied the spatial variation trend and stability of FVC in the four relevant areas of the Inner Mongolia section; an attribution analysis using a geodetector was also conducted. The following results were found: (1) in terms of temporal FVC change in the relevant areas, from 2000 to 2020, the overall FVC showed an increasing trend, indicating an obvious hierarchy of change as per different seasonal scales (summer > growing season > fall > spring). There is a mutation point in FVC in different areas, and the FVC sequence is random. (2) Regarding spatial change, the overall FVC showed a trend of being high in the eastern regions and low in the western regions and low–high–low from the north to the south; the stability of the Hetao Irrigation District–Wuliangsuhai Area changed more significantly with the successive seasons, and the degraded areas of FVC were mainly distributed in the city centre of the Kundulun River–Daheihe River Area and in the Hetao Irrigation District in the summer. (3) In terms of driving factors, soil type had a relatively higher explanatory power regarding the Hetao Irrigation District–Wuliangsuhai Area, rainfall had a relatively higher explanatory power regarding the Morin River–Wuding River Area and the Kundulun River–Daheihe River Area, and land use had a relatively higher explanatory power regarding the Ten Kongtui–Heidaigou Area.
Comparison of Future Design Rainfall with Current Design Rainfall: A Case Study in New South Wales, Australia
Authors: Hossain Iqbal , Imteaz Monzur , Gato-Trinidad Shirley , Yilmaz Abdullah Gokhan
Published: June 2024

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design rainfall from historical rainfall, which is required for the design of stormwater management infrastructure, may be ineffective and costly. It is essential to consider climate change impacts in estimating design rainfall for the successful design of stormwater management infrastructure. In this study, the probability of the occurrence of daily extreme rainfall has been assessed under climate change conditions. The assessment was performed using data from 29 meteorological stations in NSW, Australia. For the evaluation of future design rainfall, the probability of the occurrence of extreme rainfall for different recurrence intervals was developed from daily extreme rainfall for the periods of 2020 to 2099 and compared with the current Australian Bureau of Meteorology (BoM) design rainfall estimates. The historical mean extreme rainfall across NSW varied from 37.71 mm to 147.3 mm, indicating the topographic and climatic influences on extreme rainfall. The outcomes of the study suggested that the future design rainfall will be significantly different from the current BoM estimates for most of the studied stations. The comparison of the results showed that future rainfall in NSW will change from −4.7% to +60% for a 100-year recurrence interval. However, for a 2-year recurrence interval, the potential design rainfall change varies from an approximately 8% increase to a 40% decrease. This study revealed that the currently designed stormwater management infrastructure will be idle in the changing climate.
Reinterpreting Trends: The Impact of Methodological Changes on Reported Sea Salt Aerosol Levels
Authors: Karle Nakul N. , Sakai Ricardo K. , Chiao Sen , Fitzgerald Rosa M. , Stockwell William R.
Published: June 2024

Since 2017, there has been a considerable increase in the recorded sea salt aerosol (SSA) levels across the United States, particularly the economically critical Baltimore–Washington Corridor (BWC). This unexpected escalation, as reported in the Environmental Protection Agency’s (EPA) annual air quality report, has generated worries about the potential effects on air quality, public health, and regional climate dynamics. However, this technical note demonstrates that the apparent rise in SSA levels is mostly due to a change in the EPA’s Chemical Speciation Network’s (CSN) approach to measuring these aerosols. In 2017, the CSN switched from utilizing chlorine to chloride as a tracer for SSAs. Speciation data for this region show that chloride concentrations are often an order of magnitude greater than chlorine concentrations, explaining the significant increase in SSA levels following the methodological modification. The absence of a similar spike in SSA levels at the nearby IMPROVE site, which has been consistent with its methodology, provides more evidence to corroborate this conclusion. These findings demonstrate the importance of methodological consistency and openness in environmental monitoring networks. Clear documentation of such changes is critical to avoiding data misunderstanding, which might lead to the development of incorrect public health and environmental policies. We advocate for continued collaboration among researchers to establish standardized measuring procedures and data analysis tools to accommodate and clarify methodological changes, resulting in accurate environmental evaluations and informed decision-making.
Climate Classification for Major Cities in China Using Cluster Analysis
Authors: Duan Huashuai , Li Qinglan , He Lunkai , Zhang Jiali , An Hongyu , Ali Riaz , Vazifedoust Majid
Published: June 2024

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and precipitation (PRE). Both original hourly sequences and daily value sequences were used as inputs, applying two non-hierarchical clustering methods (k-means and k-medoids) and four hierarchical clustering methods (ward, complete, average, and single) for clustering. The classification results were compared using two clustering evaluation indices: the silhouette coefficient and the Calinski–Harabasz index. Additionally, the clustering was compared with the Köppen–Geiger climate classification based on the maximum difference in intra-cluster variables. The results showed that the clustering method outperformed the Köppen–Geiger climate classification, with the k-medoids method achieving the best results. Our research also compared the effectiveness of climate classification using two variables (T2 and PRE) versus three variables, including the addition of hourly RH. Cluster evaluation confirmed that incorporating the original sequence of hourly T2, PRE, and RH yielded the best performance in climate classification. This suggests that considering more meteorological variables and using hourly observation data can significantly improve the accuracy and reliability of climate classification. In addition, by setting the class numbers to two, the clustering methods effectively identified climate boundaries between northern and southern China, aligning with China’s traditional geographical division along the Qinling–Huaihe River line.
Improvements and Extension of the Linear Carbon Sink Model
Authors: Dengler Joachim
Published: June 2024

While the simple model of the total atmospheric carbon sink effect as a linear function of concentration has provided excellent prediction results, several problems remained to be investigated and solved. The most obvious open issue is the correct treatment of land use change emissions. It turns out that the model improves by mostly neglecting these emissions after 1950. This effectively implies that land use change emissions have been constant and small since then. The key investigation starts with the observation that the total carbon sink has a short-term component that can be explained by temperature changes. The apparent paradox, why contrary to the short-term changes no temperature-caused trend can be detected, despite the fact that several contributing processes exhibit clear temperature dependency, is analyzed and explained. The result of this analysis leads to the model extension, where the total effect of absorptions and natural emissions are a linear function of concentration and temperature. This extended model not only explains current measurements but also paleo-climate data from ice core time series.
Design, Assessment, and Modeling of Multi-Input Single-Output Neural Network Types for the Output Power Estimation in Wind Turbine Farms
Authors: Sharkawy Abdel-Nasser , Ameen Asmaa , Mohamed Shuaiby , Abdel-Jaber Gamal , Hamdan I.
Published: June 2024

The use of renewable energy, especially wind power, is the most practical way to mitigate the environmental effects that various countries around the world are suffering from. To meet the growing need for electricity, wind energy is, nevertheless, being used more and more. Researchers have come to understand that a near-perfect output power estimate must be sacrificed. Variations in the weather influence wind energy, including wind speed, surface temperature, and pressure. In this study, the wind turbine output power was estimated using three approaches of artificial neural networks (ANNs). The multilayer feed-forward neural network (MLFFNN), cascaded forward neural network (CFNN), and recurrent neural network (RNN) were employed for estimating the entire output power of wind turbine farms in Egypt. Therefore, each built NN made use of wind speed, surface temperature, and pressure as inputs, while the wind turbine’s output power served as its output. The data of 62 days were gathered from wind turbine farm for the training and efficiency examination techniques of every implemented ANN. The first 50 days’ worth of data were utilized to train the three created NNs, and the last 12 days’ worth of data were employed to assess the efficiency and generalization capacity of the trained NNs. The outcomes showed that the trained NNs were operating successfully and effectively estimated power. When analyzed alongside the other NNs, the RNN produced the best main square error (MSE) of 0.00012638, while the CFNN had the worst MSE of 0.00050805. A comparison between the other relevant research studies and our suggested approach was created. This comparison led us to the conclusion that the recommended method was simpler and had a lower MSE than the others. Additionally, the generalization ability was assessed and validated using the approved methodology.
Analysis of Fat Big Data Using Factor Models and Penalization Techniques: A Monte Carlo Simulation and Application
Authors: Khan Faridoon , Albalawi Olayan
Published: June 2024

This article assesses the predictive accuracy of factor models utilizing Partial·Least·Squares (PLS) and Principal·Component·Analysis (PCA) in comparison to autometrics and penalization techniques. The simulation exercise examines three types of scenarios by introducing the issues of multicollinearity, heteroscedasticity, and autocorrelation. The number of predictors and sample size are adjusted to observe the effects. The accuracy of the models is evaluated by calculating the Root·Mean·Square·Error (RMSE) and the Mean·Absolute·Error (MAE). In the presence of severe multicollinearity, the factor approach utilizing (PLS demonstrates exceptional performance in comparison. Autometrics achieves the lowest RMSE and MAE values across all levels of heteroscedasticity. Autometrics provides better forecasts with low and moderate autocorrelation. However, Elastic·Smoothly·Clipped·Absolute·Deviation (E-SCAD) forecasts well with severe autocorrelation. In addition to the simulation, we employ a popular Pakistani macroeconomic dataset for empirical research. The dataset contains 79 monthly variables from January 2013 to December 2020. The competing approaches perform differently compared to the simulation datasets, although “The PLS factor approach outperforms its competing approaches in forecasting, with lower RMSE and MAE”. It is more probable that the actual dataset exhibits a high degree of multicollinearity.
Fault Diagnosis for Lithium-Ion Battery Pack Based on Relative Entropy and State of Charge Estimation
Authors: Fan Tian-E , Chen Fan , Lei Hao-Ran , Tang Xin , Feng Fei
Published: June 2024

Timely and accurate fault diagnosis for a lithium-ion battery pack is critical to ensure its safety. However, the early fault of a battery pack is difficult to detect because of its unobvious fault effect and nonlinear time-varying characteristics. In this paper, a fault diagnosis method based on relative entropy and state of charge (SOC) estimation is proposed to detect fault in lithium-ion batteries. First, the relative entropies of the voltage, temperature and SOC of battery cells are calculated by using a sliding window, and the cumulative sum (CUSUM) test is adopted to achieve fault diagnosis and isolation. Second, the SOC estimation of the short-circuit cell is obtained, and the short-circuit resistance is estimated for a quantitative analysis of the short-circuit fault. Furthermore, the effectiveness of our method is validated by multiple fault tests in a thermally coupled electrochemical battery model. The results show that the proposed method can accurately detect different types of faults and evaluate the short-circuit fault degree by resistance estimation. The voltage/temperature sensor fault is detected at 71 s/58 s after faults have occurred, and a short-circuit fault is diagnosed at 111 s after the fault. In addition, the standard error deviation of short-circuit resistance estimation is less than 0.12 Ω/0.33 Ω for a 5 Ω/10 Ω short-circuit resistor.
Oenological Capabilities of Yeasts Isolated from High-Sugar Matrices (Manna and Honey) as Potential Starters and Co-Starters for Winemaking
Authors: Craparo Valentina , Viola Enrico , Vella Azzurra , Prestianni Rosario , Pirrone Antonino , Naselli Vincenzo , Amato Filippo , Oliva Daniele , Notarbartolo Giuseppe , Guzzon Raffaele , Settanni Luca , Moschetti Giancarlo , Francesca Nicola , Alfonzo Antonio
Published: June 2024

Non-Saccharomyces yeasts have recently garnered significant interest in oenology. When co-inoculated with Saccharomyces cerevisiae, they contribute to the improvement of wine quality from a sensory point of view. In the present study, a group of yeasts previously isolated from manna and honey by-products were subjected to a genotypic identification. The D1/D2 variable domains of the 26-sRNA gene and the ITS region of the 5.8S gene were sequenced. Additionally, a differentiation of strains was carried out by RAPD-PCR. All strains underwent in vitro screening. Subsequently, a micro-vinification experiment was conducted, focusing on strains with favourable technological characteristics: Lachancea thermotolerans, Starmerella lactis-condensi, and Candida oleophila. These strains were sequentially inoculated alongside a control strain of Saccharomyces cerevisiae. Technological screening revealed that some strains exhibited limited H2S production, ethanol tolerance (up to 8% v/v), resistance to potassium metabisulphite (200 mg/L), osmotic stress tolerance (up to 320 g/L of glucose), and copper resistance (on average 5 mM). The findings from this study can guide the selection of new starters and co-starters for regional wine production.
Proteomic Blueprint of Atlantic Cod (Gadus morhua) Otoliths Revealing Environmental Stress Insights through Label-Free Quantitative Shotgun Proteomics
Authors: Youssef Trevena N. , Christian Sherri L. , Rideout Rick , Adamack Aaron , Thibault Pierre , Bonneil Eric , Fridgen Travis D. , Banoub Joseph
Published: June 2024

Otoliths of the fish’s inner ear serve as a natural chronological recorder because of their continuous formation marked by daily, monthly, and annual increments. Despite their importance, the comprehensive protein content of otoliths remains not fully identified. Using the label-free shotgun proteomics method with one-dimensional liquid chromatography coupled to electrospray ionization-orbitrap tandem mass spectrometry, we quantified a broad range of proteins, with individual otoliths containing between 1341 and 1839 proteins. The identified proteins could potentially serve as a blueprint for fish growth from embryo to adult. We quantified eleven heat-shock proteins (HSPs) in both sexes and several proteins impacted by endocrine disruptors, indicating the otolith’s capacity to reflect environmental stress, potentially linked to climate change effects and altering of hormonal and neuroendocrine functions. Our bioinformatic ontology analysis confirmed the presence of proteins critical for various biological processes, including structural and enzymatic proteins. Protein–protein interaction (PPI) mapping also identified key interactions between the identified proteins. These findings significantly advance our understanding of otolith proteomics, offering a solid foundation for future work. Most of the identified proteins deposited daily and influenced by the environment were not implicated in the biomineralization of otolith, raising the potential for the otolith proteome to recreate details of fish life history at previously unrealized levels.
Rapid, Point-of-Care Microwave Lysis and Electrochemical Detection of Clostridioides difficile Directly from Stool Samples
Authors: Joshi Lovleen Tina , Brousseau Emmanuel , Morris Trefor , Lees Jonathan , Porch Adrian , Baillie Les
Published: June 2024

The rapid detection of the spore form of Clostridioides difficile has remained a challenge for clinicians. To address this, we have developed a novel, precise, microwave-enhanced approach for near-spontaneous release of DNA from C. difficile spores via a bespoke microwave lysis platform. C. difficile spores were microwave-irradiated for 5 s in a pulsed microwave electric field at 2.45 GHz to lyse the spore and bacteria in each sample, which was then added to a screen-printed electrode and electrochemical DNA biosensor assay system to identify presence of the pathogen’s two toxin genes. The microwave lysis method released both single-stranded and double-stranded genome DNA from the bacterium at quantifiable concentrations between 0.02 μg/mL to 250 μg/mL allowing for subsequent downstream detection in the biosensor. The electrochemical bench-top system comprises of oligonucleotide probes specific to conserved regions within tcdA and tcdB toxin genes of C. difficile and was able to detect 800 spores of C. difficile within 300 µL of unprocessed human stool samples in under 10 min. These results demonstrate the feasibility of using a solid-state power generated, pulsed microwave electric field to lyse and release DNA from human stool infected with C. difficile spores. This rapid microwave lysis method enhanced the rapidity of subsequent electrochemical detection in the development of a rapid point-of-care biosensor platform for C. difficile.
Retrospective Study of Maxillary Sinus Augmentation Using Demineralized Tooth Block Bone for Dental Implant
Authors: Choi Hyunsuk , Sohn Dong-Seok
Published: June 2024

(1) Background: When placing implants in the maxillary posterior region with insufficient alveolar bone, a maxillary sinus elevation is necessary. Autogenous bone, though biologically ideal, poses risks and discomfort due to donor site harvesting. Block-type autogenous tooth bone graft material, made from the patient’s own extracted tooth, offers similar biological stability without these drawbacks. (2) Methods: This study observed the progress of 19 implant patients who were treated with maxillary sinus elevation procedures using block-type autogenous tooth bone graft material at the Daegu Catholic University Medical Center. Extracted teeth were processed into demineralized tooth block bone. After elevating the sinus membrane, implants and the tooth bone graft material were placed in the space, and the bony window was repositioned. Postoperative evaluations through clinical observation and radiographic imaging assessed sinus membrane elevation, alveolar bone height increase, and implant osseointegration. (3) Results: Results showed proportional increases in alveolar bone height to the graft material size, with long-term stability. No postoperative complications occurred, even with sinus membrane perforation, and implants remained stable. (4) Conclusions: The study concludes that maxillary sinus lifts using block-type autogenous tooth bone graft material provide excellent bone induction and biocompatibility, making this a highly beneficial method for both dentists and patients.
The Effect of the TiO2 Anodization Layer in Pedicle Screw Conductivity: An Analytical, Numerical, and Experimental Approach
Authors: Fonseca Pedro , Goethel Márcio Fagundes , Vilas-Boas João Paulo , Gutierres Manuel , Correia Miguel Velhote
Published: June 2024

The electrical stimulation of pedicle screws is a technique used to ensure its correct placement within the vertebrae pedicle. Several authors have studied these screws’ electrical properties with the objective of understanding if they are a potential source of false negatives. As titanium screws are anodized with different thicknesses of a high electrical resistance oxide (TiO2), this study investigated, using analytical, numerical, and experimental methods, how its thickness may affect pedicle screw’s resistance and conductivity. Analytical results have demonstrated that the thickness of the TiO2 layer does result in a significant radial resistance increase (44.21 mΩ/nm, for Ø 4.5 mm), and a decrease of conductivity with layers thicker than 150 nm. The numerical approach denotes that the geometry of the screw further results in a decrease in the pedicle screw conductivity, especially after 125 nm. Additionally, the experimental results demonstrate that there is indeed an effective decrease in conductivity with an increase in the TiO2 layer thickness, which is also reflected in the screw’s total resistance. While the magnitude of the resistance associated with each TiO2 layer thickness may not be enough to compromise the ability to use anodized pedicle screws with a high-voltage electrical stimulator, pedicle screws should be the subject of more frequent electrical characterisation studies.
Synergistic Cellular Responses Conferred by Concurrent Optical and Magnetic Stimulation Are Attenuated by Simultaneous Exposure to Streptomycin: An Antibiotic Dilemma
Authors: Iversen Jan Nikolas , Fröhlich Jürg , Tai Yee Kit , Franco-Obregón Alfredo
Published: June 2024

Concurrent optical and magnetic stimulation (COMS) combines extremely low-frequency electromagnetic and light exposure for enhanced wound healing. We investigated the potential mechanistic synergism between the magnetic and light components of COMS by comparing their individual and combined cellular responses. Lone magnetic field exposure produced greater enhancements in cell proliferation than light alone, yet the combined effects of magnetic fields and light were supra-additive of the individual responses. Reactive oxygen species were incrementally reduced by exposure to light, magnetics fields, and their combination, wherein statistical significance was only achieved by the combined COMS modality. By contrast, ATP production was most greatly enhanced by magnetic exposure in combination with light, indicating that mitochondrial respiratory efficiency was improved by the combination of magnetic fields plus light. Protein expression pertaining to cell proliferation was preferentially enhanced by the COMS modality, as were the protein levels of the TRPC1 cation channel that had been previously implicated as part of a calcium–mitochondrial signaling axis invoked by electromagnetic exposure and necessary for proliferation. These results indicate that light facilitates functional synergism with magnetic fields that ultimately impinge on mitochondria-dependent developmental responses. Aminoglycoside antibiotics (AGAs) have been previously shown to inhibit TRPC1-mediated magnetotransduction, whereas their influence over photomodulation has not been explored. Streptomycin applied during exposure to light, magnetic fields, or COMS reduced their respective proliferation enhancements, whereas streptomycin added after the exposure did not. Magnetic field exposure and the COMS modality were capable of partially overcoming the antagonism of proliferation produced by streptomycin treatment, whereas light alone was not. The antagonism of photon-electromagnetic effects by streptomycin implicates TRPC1-mediated calcium entry in both magnetotransduction and photomodulation. Avoiding the prophylactic use of AGAs during COMS therapy will be crucial for maintaining clinical efficacy and is a common concern in most other electromagnetic regenerative paradigms.
The Fluorescent Cell Line SW620-GFP Is a Valuable Model to Monitor Magnetic Hyperthermia
Authors: Rosales Saray , Hernández-Gutiérrez Rodolfo , Oaxaca Alma , López Zaira , Casillas Norberto , Knauth Peter , Quintero Luis H. , Paz José A. , Cholico Francisco , Velásquez Celso , Cano Mario E.
Published: June 2024

In this work, the cell line SW620-GFP has been used in a complete magnetic hyperthermia assay, from the preparation of the ferrofluid with folate-coated iron oxide nanoparticles to in vivo experiments. The physical and chemical characterization of the nanoparticles evidenced their superparamagnetic behaviour, an average diameter of 12 ± 4 nm, a 2 nm coat thickness, and a high-power loss density. The main innovation of the work is the exclusive capability of viable SW620-GFP cells to emit fluorescence, enabling fast analysis of both, cell viability in vitro with an epifluorescence microscope and tumour size and shape in vivo in a non-invasive manner using the iBox technology. Moreover, with this imaging technique, it was possible to demonstrate the successful tumour size reduction in mice applying magnetic hyperthermia three times a week over 3 weeks.
Short-Term Clinical Results of Single-Injection Autologous Bone Marrow Aspirate Concentrate (BMAC) as a Therapeutic Option/Tool in Knee Osteoarthritis
Authors: Subramanyam Krishna , Poornima Subhadra , Kumar Satish , Hasan Qurratulain
Published: June 2024

Purpose: Knee osteoarthritis (KOA) is a very common cartilage disorder affecting millions of people globally and is characterized by pain, stiffness, swelling, loss of articular cartilage, and osteophyte formation, resulting in disability. The presently available treatments for KOA are palliative. Hence, there is a need to explore a non-surgical treatment portfolio. Bone marrow aspirate concentrate (BMAC) is one of the predominant attention-drawing managements/treatments for KOA in recent times due to its potential advantages of disease-modifying and regeneration capacities. Principle: This study aimed to evaluate the role of single-injection autologous BMAC as a therapeutic option in the treatment of KOA and evaluate the functional and clinical outcomes of KOA patients. In this study, 132 patients with KOA (Kellgren and Lawrence (KL) grade II and III) were included as per the inclusion criteria. Autologous bone marrow was aspirated and separated, and concentrated bone marrow aspirate was administered into the knee joint of the affected individual. Results: At the end of the 12th month (end of the follow-up period), 95% of patients showed complete pain relief and improvement in joint function, which shows that the results were promising and encouraging. Unpaired t-test results also indicated that the two-tailed p-value is less than 0.0001, and the difference is extremely statistically significant. No adverse effects were observed in the study patients. Conclusions: BMAC therapy has potential, with satisfactory, efficient, and durable results in KL grades II and III in KOA patients. This can be a safe alternative therapy in the treatment of KOA, especially in the early grades of OA. In summary, to the best of our knowledge, this is the first study from India that evaluated BMAC efficacy both subjectively and objectively in KOA (KL-II and KL-III) patients.