bluuebunny/crossref_metadata_2025 huggingface dataset:
A 3D-Printed Dummy for Training Distal Phalanx Amputation in Mice
Authors: Heuser Miriam , Gonzalez-Uarquin Fernando , Nuber Maximilian , Brockmann Marc A. , Baumgart Jan , Baumgart Nadine
Published: April 2024

The development of realistic dummies for training the distal phalanx amputation (DPA) technique in mouse pups is a promising alternative to reduce and replace animals in training for research and teaching. To test this, we obtained micro-CT data from postnatal day-five mouse pups, meticulously segmented them, and converted them into a 3D mesh format suitable for 3D printing. Once the dummy was printed, it was evaluated during actual training courses in two different groups: in the first group, users received no dummies to train the DPA, and in the second group, users were trained with three dummies. To assess the effectiveness of the dummy, we conducted a survey followed by an expert veterinarian evaluation. Our results showed that DPA is a complex procedure, and it is commonly poorly performed. When implementing the dummies, users who were not provided with dummies to practice only had an 8.3% success rate in DPA, while users provided with three dummies had a 45.5% success rate, respectively. Despite additional research being needed, our dummy offered improved practical training by providing a safe and effective alternative in line with ethical considerations while demonstrating the feasibility of using 3D printing technology to promote the 3Rs in experimental research.
A Narrative Review of the State of the Art of CCR4-Based Therapies in Cutaneous T-Cell Lymphomas: Focus on Mogamulizumab and Future Treatments
Authors: Zengarini Corrado , Guglielmo Alba , Mussi Martina , Motta Giovanna , Agostinelli Claudio , Sabattini Elena , Piraccini Bianca Maria , Pileri Alessandro
Published: April 2024

The CCR4 receptor is a pivotal target in cutaneous T-cell lymphoma (CTCL) therapy due to its role in impairing immune responses against malignant T-cells and expression profiles. Monoclonal antibodies like mogamulizumab effectively bind to CCR4, reducing tumour burden and enhancing patient outcomes by inhibiting the receptor’s interaction with ligands, thereby hindering malignant T-cell migration and survival. Combining CCR4 antibodies with chemotherapy, radiation, and other drugs is being explored for synergistic effects. Additionally, small-molecular inhibitors, old pharmacological agents interacting with CCR4, and CAR-T therapies are under investigation. Challenges include drug resistance, off-target effects, and patient selection, addressed through ongoing trials refining protocols and identifying biomarkers. Despite advancements, real-life data for most of the emerging treatments are needed to temper expectations. In conclusion, CCR4-targeted therapies show promise for CTCL management, but challenges persist. Continued research aims to optimise treatments, enhance outcomes, and transform CTCL management. This review aims to elucidate the biological rationale and the several agents under various stages of development and clinical evaluation with the actual known data.
The Use of Generative Design Methods to Reduce the Parameters of an Actuator Used in the Positioning System of a Continuous Passive Motion (CPM) Device
Authors: Trochimczuk Roman , Zdobytskyi Andriy , Borkowski Piotr
Published: April 2024

This paper presents the results of a computer optimising a multibody system using Generative Design methods to select a lower-cost actuator that meets process requirements with its parameters. Optimisation was performed to reduce the mass of the motion apparatus components of the author’s CPM device, used for the rehabilitation of patients after knee arthroscopy and total or partial knee replacement. An analysis of the kinematics and dynamics of the multibody mechanism, based on a virtual model, was carried out to identify the requirements for selecting an actuator. The main components of the motion apparatus mechanism were subjected to a series of numerical analyses using selected CAD/CAE tools, with the assumed criterion of varying material and component shapes to ensure that the required strength and accuracy of the mechanism links were maintained, assuming the same functionality. The results of the numerical analyses will be the basis for the selection of the optimum solution, for which a new, lower-cost actuator will be selected.
A Dynamic Parameter Tuning Strategy for Decomposition-Based Multi-Objective Evolutionary Algorithms
Authors: Zheng Jie , Ning Jiaxu , Ma Hongfeng , Liu Ziyi
Published: April 2024

The penalty-based boundary cross-aggregation (PBI) method is a common decomposition method of the MOEA/D algorithm, but the strategy of using a fixed penalty parameter in the boundary cross-aggregation function affects the convergence of the populations to a certain extent and is not conducive to the maintenance of the diversity of boundary solutions. To address the above problems, this paper proposes a penalty boundary crossing strategy (DPA) for MOEA/D to adaptively adjust the penalty parameter. The strategy adjusts the penalty parameter values according to the state of uniform distribution of solutions around the weight vectors in the current iteration period, thus helping the optimization process to balance convergence and diversity. In the experimental part, we tested the MOEA/D-DPA algorithm with several MOEA/D improved algorithms on the classical test set. The results show that the MOEA/D with the DPA has better performance than the MOEA/D with the other decomposition strategies.
The Impact of GCP Chip Distribution on Kompsat-3A RPC Bias Compensation
Authors: Jo Hyeonjeong , Lee Changno , Oh Jaehong
Published: April 2024

The vast potential of high-resolution satellite images, including Kompsat-3A, has been demonstrated across diverse applications, such as mapping and disaster monitoring. However, these images can only be utilized as reliable GIS (geographic information system) data when they possess precise geographical information. To achieve this, sensor model information, represented by RPCs (rational polynomial coefficients), requires bias compensation through GCPs (ground control points). Though having a substantial number of well-distributed GCPs across satellite images is ideal, the acquisition process is often restricted due to cost and inaccessibility. The uniform distribution of GCP chips is not guaranteed, necessitating an investigation into the impact of GCP distribution on the bias compensation process, which is the focus of this study. Experiments were meticulously conducted using Kompsat-3A data using dense GCP information. The dense GCP information was automatically generated from aerial orthoimages through a three-step process. Firstly, the GCP chips were extracted from the aerial images, focusing on feature points. Secondly, these chips were projected onto the target Kompsat-3A data to align them accurately. Lastly, precise satellite image coordinates of the chips were obtained through image matching between the chips and the target Kompsat-3A image. The dense GCPs enabled detailed bias analysis that exhibited skewness in most Kompsat-3A data. This necessitates the implementation of an affine model for proper bias compensation over the entire image space. Next, the study delved into the influence of GCP distribution on RPC bias compensation. To this end, each target satellite image space was divided into nine zones, with the dense GCPs assigned accordingly. The accuracy of bias compensation was analyzed across nine experimental cases, ranging from GCPs occupying only one zone to GCPs covering all nine zones. It was observed that GCPs covering at least four or five zones should be utilized for reliable RPC bias compensation of Kompsat-3A, especially when aiming for a high level of accuracy with an RMSE of one pixel. Finally, it was concluded that GCPs covering three zones yielded satisfactory results as a minimum GCP requirement, but this was contingent upon their distribution not following a straight zone pattern.
A New Training Method for VR Sickness Reduction
Authors: Won Ju-hye , Na Hae Chan , Kim Yoon Sang
Published: April 2024

In this paper, we propose a training method to reduce the VR sickness that occurs while viewing VR content with an HMD on. The proposed approach is a new method that involves pre-exposing users to VR sickness to enable them to adapt to VR sickness. In the proposed method, the training process was designed based on the features of existing studies related to exposure and adaptation to motion sickness and simulator sickness. The effectiveness of the proposed method was evaluated through experiments with 15 subjects (SSQ and VR sickness response were used in the analysis). As a result of the experiment, nausea was significantly decreased by 47%, and oculomotor discomfort was significantly decreased by 34% after the proposed training method. The VR sickness response decreased by 31%; however, this difference was not statistically significant. Furthermore, we analyzed the VR sickness response in two groups: those whose sickness decreased and those whose sickness increased. We confirmed that the decrease group (pre-experiment mean: 1.34 times, post-experiment mean: 0.58 times) had a larger change than the increase group (pre-experiment mean: 0.31 times, post-experiment mean: 0.42 times). Therefore, from the experimental results, it was confirmed that the proposed method is effective in reducing VR sickness.
Data-Driven Identification of Crane Dynamics Using Regularized Genetic Programming
Authors: Kusznir Tom , Smoczek Jarosław , Karwat Bolesław
Published: April 2024

The meaningful problem of improving crane safety, reliability, and efficiency is extensively studied in the literature and targeted via various model-based control approaches. In recent years, crane data-driven modeling has attracted much attention compared to physics-based models, particularly due to its potential in real-time crane control applications, specifically in model predictive control. This paper proposes grammar-guided genetic programming with sparse regression (G3P-SR) to identify the nonlinear dynamics of an underactuated crane system. G3P-SR uses grammars to bias the search space and produces a fixed number of candidate model terms, while a local search method based on an l0-regularized regression results in a sparse solution, thereby also reducing model complexity as well as reducing the probability of overfitting. Identification is performed on experimental data obtained from a laboratory-scale overhead crane. The proposed method is compared with multi-gene genetic programming (MGGP), NARX neural network, and Takagi-Sugeno fuzzy (TSF) ARX models in terms of model complexity, prediction accuracy, and sensitivity. The G3P-SR algorithm evolved a model with a maximum mean square error (MSE) of crane velocity and sway prediction of 1.1860 × 10−4 and 4.8531 × 10−4, respectively, in simulations for different testing data sets, showing better accuracy than the TSF ARX and MGGP models. Only the NARX neural network model with velocity and sway maximum MSEs of 1.4595 × 10−4 and 4.8571 × 10−4 achieves a similar accuracy or an even better one in some testing scenarios, but at the cost of increasing the total number of parameters to be estimated by over 300% and the number of output lags compared to the G3P-SR model. Moreover, the G3P-SR model is proven to be notably less sensitive, exhibiting the least deviation from the nominal trajectory for deviations in the payload mass by approximately a factor of 10.
The Noise Blowing-Up Strategy Creates High Quality High Resolution Adversarial Images against Convolutional Neural Networks
Authors: Topal Ali Osman , Mancellari Enea , Leprévost Franck , Avdusinovic Elmir , Gillet Thomas
Published: April 2024

Convolutional neural networks (CNNs) serve as powerful tools in computer vision tasks with extensive applications in daily life. However, they are susceptible to adversarial attacks. Still, attacks can be positive for at least two reasons. Firstly, revealing CNNs vulnerabilities prompts efforts to enhance their robustness. Secondly, adversarial images can also be employed to preserve privacy-sensitive information from CNN-based threat models aiming to extract such data from images. For such applications, the construction of high-resolution adversarial images is mandatory in practice. This paper firstly quantifies the speed, adversity, and visual quality challenges involved in the effective construction of high-resolution adversarial images, secondly provides the operational design of a new strategy, called here the noise blowing-up strategy, working for any attack, any scenario, any CNN, any clean image, thirdly validates the strategy via an extensive series of experiments. We performed experiments with 100 high-resolution clean images, exposing them to seven different attacks against 10 CNNs. Our method achieved an overall average success rate of 75% in the targeted scenario and 64% in the untargeted scenario. We revisited the failed cases: a slight modification of our method led to success rates larger than 98.9%. As of today, the noise blowing-up strategy is the first generic approach that successfully solves all three speed, adversity, and visual quality challenges, and therefore effectively constructs high-resolution adversarial images with high-quality requirements.
Enhancing Wireless Sensor Network in Structural Health Monitoring through TCP/IP Socket Programming-Based Mimic Broadcasting: Experimental Validation
Authors: Nilnoree Srikulnath , Taparugssanagorn Attaphongse , Kaemarungsi Kamol , Mizutani Tsukasa
Published: April 2024

This paper presents the implementation of a synchronous Structural Health Monitoring (SHM) framework utilizing wireless, low-cost, and off-the-shelf components. Vibration-based condition monitoring plays a crucial role in assessing the reliability of structural systems by detecting damage through changes in vibration parameters. The adoption of low-cost Micro-Electro-Mechanical Systems (MEMS) sensors in Wireless Sensor Networks (WSNs) has gained traction, emphasizing the need for precise time synchronization to schedule wake-up times of multiple sensor nodes for data collection. To address this challenge, our proposed method introduces a TCP/IP socket programming-based mimic broadcasting mechanism and a scalable sensing network controlled by a central gateway, leveraging the Raspberry Pi Python platform. The system operates using Internet of Things (IoT) concepts and adopts a star topology, where a packet is transmitted from the gateway to initiate measurements simultaneously on multiple sensor nodes. The sensor node comprises a MEMS accelerometer, a real time clock DS3231 module and Raspberry Pi Zero 2W (RPi0-2W), while the gateway employs a Raspberry Pi 4 (RPi4). To ensure accurate time synchronization, all Pi0-2W nodes were configured as Network Time Protocol (NTP) clients, synchronizing with an RPi4 server using chrony, the reliable implementation of the NTP. Through experimental evaluations, the system demonstrates its effectiveness and reliability in achieving initial time synchronization. This study addresses the challenge of achieving precise time alignment between sensor nodes through the utilization of the Dynamic Time Wrapping (DTW) method for Frequency Domain Decomposition (FDD) applications. The contribution of this research significantly enhances the field by improving the accuracy and reliability of time-aligned measurements, with a specific focus on utilizing low-cost sensors. By developing a practical and cost-effective SHM framework, this work advances the accessibility and scalability of structural health monitoring solutions, facilitating more widespread adoption and implementation in various engineering applications
PnV: An Efficient Parallel Consensus Protocol Integrating Proof and Voting
Authors: Wang Han , Li Hui , Fan Ping , Kang Jian , Deng Selwyn , Zhu Xiang
Published: April 2024

Consensus protocols, as crucial components of blockchain technology, play a vital role in ensuring data consistency among distributed nodes. However, the existing voting-based and proof-based consensus protocols encounter scalability issues within the blockchain system. Moreover, most consensus protocols are serialized, which further limits their scalability potential. To address this limitation, parallelization methods have been employed in both types of consensus protocols. Surprisingly, however, novel fusion consensus protocols demonstrate superior scalability compared with these two types but lack the utilization of parallelization techniques. In this paper, we present PnV, an efficient parallel fusion protocol integrating proof-based and voting-based consensus features. It enhances the data structure, consensus process, transaction allocation, and timeout handling mechanisms to enable concurrent block generation by multiple nodes within a consensus round. Experimental results demonstrate that PnV exhibits superior efficiency, excellent scalability, and acceptable delay compared with Proof of Vote (PoV) and BFT-SMART. Moreover, at the system level, the performance of the PnV-based blockchain system optimally surpasses that of the FISCO BCOS platform. Our proposed protocol contributes to advancing blockchain technology by providing a more efficient and practical solution for achieving decentralized consensus in distributed systems.
Insight into Adsorption Kinetics of Cs+, Rb+, Co2+, and Sr2+ on a Zeolites-Based Composite: Comprehensive Diffusional Explanation and Modelling
Authors: Boughriet Abdel , Doyemet Gildas , Poumaye Nicole , Allahdin Oscar , Wartel Michel
Published: April 2024

Kaolinite-rich soils were used to prepare zeolite-based composites via alkaline activation. The porous material was characterized by conducting XRD and microporosity measurements, as well as ESEM microscopy. The Weber and Morris (W-M) model was used for studying adsorption kinetics of radioactive cations on synthesized alkali-activated material. These investigations evidenced the effects of pore structure and the importance of the intrinsic characteristics of hydrated cations (ionic potential; hydrated radius; B-viscosity parameter; molar Gibbs energy of hydration of cation) on W-M kinetic rate constants. The application of diffusion-based models permitted us to assess the key diffusion parameters controlling successive diffusion regimes, and to reveal strong contributions of surface diffusion to adsorption kinetics during the course of the second and third kinetics stages of the W-M model. The magnitude of the surface diffusion coefficient was related to the capacity of hydrated cationic species to lose water molecules when penetrating brick pores. The HSDM model were tested for predicting radionuclide adsorption in a fixed-bed column. A breakthrough curve simulation indicated the predominance of the surface diffusion regime, which was in agreement with mathematical analysis of (batch) adsorption kinetics data. Ionic diffusion was linked to the characteristics of capillary porosity and connectivity of capillary pores in the composite, suggesting the generation of hydrated nuclides and their immobilization in the form of outer-sphere complexes.
Stability Analysis in Multi-VSC (Voltage Source Converter) Systems of Wind Turbines
Authors: Dimitropoulos Dimitrios , Wang Xiongfei , Blaabjerg Frede
Published: April 2024

In this paper, a holistic nonlinear state-space model of a system with multiple converters is developed, where the converters correspond to the wind turbines in a wind farm and are equipped with grid-following control. A novel generalized methodology is developed, based on the number of the system’s converters, to compute the equilibrium points around which the model is linearized. This is a more solid approach compared with selecting operating points for linearizing the model or utilizing EMT simulation tools to estimate the system’s steady state. The dynamics of both the inner and outer control loops of the power converters are included, as well as the dynamics of the electrical elements of the system and the digital time delay, in order to study the dynamic issues in both high- and low-frequency ranges. The system’s stability is assessed through an eigenvalue-based stability analysis. A participation factor analysis is also used to give an insight into the interactions caused by the control topology of the converters. Time domain simulations and the corresponding frequency analysis are performed in order to validate the model for all the control interactions under study.
Practical Steps towards Establishing an Underwater Acoustic Network in the Context of the Marine Internet of Things
Authors: Kebkal Konstantin , Kabanov Aleksey , Kramar Oleg , Dimin Maksim , Abkerimov Timur , Kramar Vadim , Kebkal-Akbari Veronika
Published: April 2024

When several hydroacoustic modems operate simultaneously in an area of mutual coverage, collisions of data packets received from several sources may occur, which lead to information loss. With an increase in the number of simultaneously operating hydroacoustic modems, physical layer algorithms do not provide stable data transmission and the likelihood of collisions increases, which makes the operation of modems ineffective. To ensure effective operation in a hydroacoustic signal propagation environment and to reduce collisions when exchanging data between two modems that do not have the ability to operate synchronously and to reduce the access time to the signal propagation environment, methods of the medium access control layer using link layer protocols are required. Typically, this problem is solved using code separation of hydroacoustic channels. If you need to transfer over a network, this option will not work, since network transfer involves working on the basis of “broadcast” messages, particularly between data source and data sink that remain too far from each other, outside of their mutual audibility. In practical use, it is convenient to place these protocols into a software environment for developing specific user applications for solving network communication problems. This software framework allows for custom modification of existing network algorithms, as well as the inclusion of new network hydroacoustic communication algorithms. To build a predictive model, the DACAP, T-Lohi, Flooding, and ICRP protocols were used in this work. The implementation is performed in Erlang. The paper presents algorithms for implementing these protocols. A comparative analysis of network operation with and without protocols is provided. Efficiency of operation, i.e., data rates and probabilities of data delivery, was assessed.
Acceleration Capacity and Vertical Jump Performance Relationship in Prepubertal Children
Authors: Chanel Baptiste , Babault Nicolas , Cometti Carole
Published: April 2024

Sprint and jump abilities are considered basic skills that are regularly evaluated in training and school contexts. The correlations between these two skills have previously been established in adults and adolescents, but they have not been fully assessed in children. The present study aimed to explore sprinting and jumping ability in prepubertal boys and girls. Thirty-one prepubertal individuals (aged 8–11 years) were assessed during sprinting for different distances (5, 10, and 20 m) and using different vertical and horizontal jump modalities (squat jump, countermovement jump, broad jump, and hop test). Correlations between the different results were tested. Strong correlations were found between vertical jump and sprint performances, especially over short distances. These results suggested that vertical jump tests are more sensitive than horizontal jumps to reveal acceleration capacity in children.
Factors Affecting Radial Increment Dynamics in Lithuanian Populations of Common Juniper (Juniperus communis L.)
Authors: Vaitkevičiūtė Rasa , Makrickiene Ekaterina , Linkevičius Edgaras
Published: April 2024

Although common juniper (Juniperus communis L.) is a widely spread species and important for the forest biodiversity and economy in many European countries, it remains one of the least studied coniferous species. This research is the first attempt to evaluate the factors affecting the increment of Juniperus communis in Lithuanian populations. The aim of this article is to evaluate the patterns of radial increment in Juniperus communis and to identify the key factors influencing the increment. We collected stem discs from 160 junipers in 8 stands distributed in the different regions of Lithuania and performed the tree-ring analysis. All studied junipers expressed a pronounced eccentricity of the stem. The results of our study revealed four patterns of Juniperus communis’ radial increment, which are strongly dependent on the granulometric properties of the soil and hydrologic conditions. The effect of climatic conditions on the Juniperus communis increment was strongly dependent on the terrain; however, most of the junipers had a positive reaction to the temperatures in April, July, and August and to the precipitation in February.
System Identification and Dynamic Analysis of the Propulsion Shaft Systems Using Response Surface Optimization Technique
Authors: Paudel Aavash Chandra , Doranga Sushil , Li Yueqing , Khanal Mukunda
Published: April 2024

Marine vessels rely heavily on propeller shaft systems to adjust the engine torque and propeller thrust. However, these systems are subjected to various dynamic excitations during operation, such as transverse, longitudinal, and torsional excitations. These excitations can arise from factors like non-uniform stern flow fields, misaligned components, and the whirling motion of the shafts, which can affect the integrity and reliability of the vehicle. To analyze the dynamic response of the propulsion shaft system and ensure its reliability, numerical/analytical models are currently in practice. The finite element method (FEM) is a popular choice, but uncertainties in bearings and connectors stiffness lead to inaccuracies in the Finite Element model, resulting in significant differences between the experimental and theoretical models. This paper proposes the response surface optimization (RSO) technique to estimate unknown bearing stiffness in the propulsion shaft system. The experimental model of the propeller shaft system is constructed using steady-state response with step sine excitation. The RSO technique is then used to update the natural frequencies and vibration amplitude of the FE (Finite Element) model. The updated model shows less than a 10% difference in natural frequencies and vibration amplitude compared to the experimental model, demonstrating that the proposed technique is an efficient tool for marine shaft dynamic analysis.
Wavelet Analysis of Atmospheric Ozone and Ultraviolet Radiation on Solar Cycle-24 over Lumbini, Nepal
Authors: Shrestha Prakash M. , Gupta Suresh P. , Joshi Usha , Schmutzler Morgan , Aryal Rudra , Tiwari Babu Ram , Adhikari Binod , Chapagain Narayan P. , Karki Indra B. , Poudyal Khem N.
Published: April 2024

This research aims to comprehensively examine the clearness index (KT), total ozone column (TOC), and ultraviolet A (UVA) and ultraviolet B radiation (UVB) over Lumbini, Nepal (27°28’ N, 83°16’ E, and 150 m above sea level) throughout the 11 years of solar cycle 24 (2008 to 2018). The Lumbini, a highly polluted region, is important in advancing the identification and analysis of TOC variations across regions with similar geographical and climatic attributes. Data from the Ozone Monitoring Instrument (OMI) of the EOS-AURA satellite of NASA were used to analyze the daily, monthly, seasonal, and annual trends in the clearness index (KT), ultraviolet A (UVA), ultraviolet B (UVB), and TOC from the Comprehensive Environmental Data Archive (CEDA). The study found that the yearly averages for KT, TOC, UVA, and UVB were 0.55 ± 0.13, 272 ± 14 DU, 12.61 ± 3.50 W/m2, and 0.32 ± 0.11 W/m2, respectively. These values provide insights into the long-term variations in atmospheric parameters at Lumbini. The study also applied the continuous wavelet transform (CWT) to analyze KT, TOC, UVA, and UVB temporal variations. The power density peak of 35,000 DU2 in the TOC was observed from the end of 2010 to the end of 2011, within 8.5 years, underscoring the significance of analyzing TOC dynamics over extended durations to understand atmospheric behavior comprehensively.
Inactivation Mechanisms of Escherichia coli in Simulants of Respiratory and Environmental Aerosol Droplets
Authors: Otero-Fernandez Mara , Thomas Richard J. , Oswin Henry , Alexander Robert , Haddrell Allen , Reid Jonathan P.
Published: April 2024

The airborne transmission of disease relies on the ability of microbes to survive aerosol transport and, subsequently, cause infection when interacting with a host. The length of time airborne microorganisms remain infectious in aerosol droplets is a function of numerous variables. We present measurements of mass and heat transfer from liquid aerosol droplets combined with airborne survival data for Escherichia coli MRE162, an ACDP category 1 microorganism used as a model system, under a wide range of environmental conditions, droplet compositions and microbiological conditions. In tandem, these companion measurements demonstrate the importance of understanding the complex relationship between aerosol microphysics and microbe survival. Specifically, our data consist of the correlation of a wide range of physicochemical properties (e.g., evaporation rates, equilibrium water content, droplet morphology, compositional changes in droplet solute and gas phase, etc.), with airborne viability decay to infer the impact of aerosol microphysics on airborne bacterial survival. Thus, a mechanistic approach to support prediction of the survival of microorganisms in the aerosol phase as a function of biological, microphysical, environmental, and experimental (aerosol-generation and sampling) processes is presented. Specific findings include the following: surfactants do not increase bacteria stability in aerosol, while both the bacteria growth phase and bacteria concentration may affect the rate at which bacteria decay in aerosol.
Monitoring Snow Cover in Typical Forested Areas Using a Multi-Spectral Feature Fusion Approach
Authors: Wang Yunlong , Wang Jianshun
Published: April 2024

Accurate snow cover monitoring is greatly significant for research on the hydrology model and regional climate variation, especially in Northeast China where forests cover almost forty percent of the total area. However, effectively monitoring snow cover under the forest canopy is still challenging with either in situ or remote sensing observations. The global SNOWMAP algorithm pertinent to the fixed normalized difference snow index (NDSI) threshold is, therefore, no longer applicable in a typical forested region of Northeast China. In order to achieve the goal of improving the accuracy of monitoring snow cover in areas with forest, utilizing MOD09GA and MOD13A1 products, a new approach of snow mapping was developed in this study, and it exploits the fusion and coupling of spectral features by integrating and analyzing the normalized difference forest snow index (NDFSI), the normalized difference vegetation index (NDVI), and the NDSI index. Then, Landsat 8 OLI images of high resolution were used to evaluate snow cover mapping precision. The experimental results indicated that the NDFSI index combined with the NDVI index showed great potential for extracting the snow cover distribution in forested regions. Compared with the snow distribution obtained from the Landsat 8 images, the average bias and FAR (false alarm ratio) values of snow cover mapping obtained by this algorithm were 1.23 and 13.54%, which were reduced by 1.98 and 29.36%, respectively. The overall accuracy of 81.31% was reached, which is improved by 20.19%. Thus, the snow classification scheme combining multiple spectral features from MODIS data works effectively in improving the precision of automatic snow cover mapping in typical forested areas of Northeast China, which provides essential support and significant perspectives for the next step of establishing a runoff model and rationally regulating forest water resources.
The Observed Changes in Climate Characteristics in the Trebinje Vineyard Area (Bosnia and Herzegovina)
Authors: Banjanin Tijana , Ranković-Vasić Zorica , Glišić Milica , Pržić Zoran
Published: April 2024

The productivity and quality of grapes and wine are significantly influenced by changing climate conditions in vineyard regions worldwide. This study assesses changes in temperature, precipitation, and viticultural indices between the periods of 1971–1990 and 2000–2019 in Trebinje, a vineyard area located in the Herzegovina region of Bosnia and Herzegovina. Between the two periods, mean annual temperature increased by 2 °C and mean vegetational temperature by 2.4 °C, while mean precipitation remained within the range of climatological variability, with annual values increasing by 6% and vegetational values decreasing by 4.6%. Warming resulted in a longer duration of the vegetation season by 23.7 days, a reduced risk of late spring frosts, and an increased risk of very high temperatures during summer. These changes led to the reclassification of Trebinje vineyards’ climate from Region III to Region V, based on the Winkler index values, from a “temperate warm” to a “warm” category, based on the Huglin heliothermic index, and from “cool nights” to “temperate nights” based on the cool nights index. The category of the dryness index remained unchanged between the two periods. The findings emphasize the necessity for a renewal of the viticultural zoning and the development of climate change-adaptation plans for this region.
Estimation of Gumbel Distribution Based on Ordered Maximum Ranked Set Sampling with Unequal Samples
Authors: Hassan Nuran Medhat , Alamri Osama Abdulaziz
Published: April 2024

Sample selection is one of the most important factors in estimating the unknown parameters of distributions, as it saves time, saves effort, and gives the best results. One of the challenges is deciding on a suitable distribution estimate technique and adequate sample selection to provide the best results in comparison with earlier research. The method of moments (MOM) was decided on to estimate the unknown parameters of the Gumbel distribution, but with four changes in the sample selection, which were simple random sample (SRS), ranked set sampling (RSS), maximum ranked set sampling (MRSS), and ordered maximum ranked set sampling (OMRSS) techniques, due to small sample sizes. The MOM is a traditional method for estimation, but it is difficult to use when dealing with RSS modification. RSS modification techniques were used to improve the efficiency of the estimators based on a small sample size compared with the usual SRS estimator. A Monte Carlo simulation study was carried out to compare the estimates based on different sampling. Finally, two datasets were used to demonstrate the adaptability of the Gumbel distribution based on the different sampling techniques.
The Existence of Li–Yorke Chaos in a Discrete-Time Glycolytic Oscillator Model
Authors: Garić-Demirović Mirela , Kulenović Mustafa R. S. , Nurkanović Mehmed , Nurkanović Zehra
Published: April 2024

This paper investigates an autonomous discrete-time glycolytic oscillator model with a unique positive equilibrium point which exhibits chaos in the sense of Li–Yorke in a certain region of the parameters. We use Marotto’s theorem to prove the existence of chaos by finding a snap-back repeller. The illustration of the results is presented by using numerical simulations.
Energy Storage Systems: Technologies and High-Power Applications
Authors: Aghmadi Ahmed , Mohammed Osama A.
Published: April 2024

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies.
Mechanical Measurement Approach to Characterize Venting Behavior during Thermal Runaway of 18650 Format Lithium-Ion Batteries
Authors: Gillich Elisabeth Irene , Steinhardt Marco , Fedoryshyna Yaroslava , Jossen Andreas
Published: April 2024

The propagation of thermal runaway in a battery system is safety-critical in almost every application, such as electric vehicles or home storage. Abuse models can help to undestand propagation mechanisms and assist in designing safe battery systems, but need to be well-parametrized. Most of the heat during thermal runaway is released by venting that is why the characteristic of the vent flow plays an important part in the safety assessment. During venting, the cell generates a recoil force like a rocket, which depends on the flow speed and flow rate of the gas. This principle is used in this work to measure the velocity and mass flow rate of the vent gas. High-power and high-energy 18650 format lithium-ion batteries were overheated and the recoil and weight forces were measured to determine the venting parameter during thermal runaway. Our results show, that the linearized gas flow rate for the high-power and high-energy cell is 22.15gs−1 and 27.92gs−1, respectively. The progress of the gas velocity differs between the two cell types and in case of the high-energy cell, it follows a single peak asymmetrical pattern with a peak of 398.5ms−1, while the high-power cell shows a bumpy pattern with a maximum gas velocity of 260.9ms−1. The developed test bench and gained results can contribute insights in the venting behavior, characterize venting, support safety assessments, simulations and pack design studies.
Short-Term l-arginine Treatment Mitigates Early Damage of Dermal Collagen Induced by Diabetes
Authors: Miler Irena , Rabasovic Mihailo D. , Askrabic Sonja , Stylianou Andreas , Korac Bato , Korac Aleksandra
Published: April 2024

Changes in the structural properties of the skin due to collagen alterations are an important factor in diabetic skin complications. Using a combination of photonic methods as an optic diagnostic tool, we investigated the structural alteration in rat dermal collagen I in diabetes, and after short-term l-arginine treatment. The multiplex approach shows that in the early phase of diabetes, collagen fibers are partially damaged, resulting in the heterogeneity of fibers, e.g., “patchy patterns” of highly ordered/disordered fibers, while l-arginine treatment counteracts to some extent the conformational changes in collagen-induced by diabetes and mitigates the damage. Raman spectroscopy shows intense collagen conformational changes via amides I and II in diabetes, suggesting that diabetes-induced structural changes in collagen originate predominantly from individual collagen molecules rather than supramolecular structures. There is a clear increase in the amounts of newly synthesized proline and hydroxyproline after treatment with l-arginine, reflecting the changed collagen content. This suggests that it might be useful for treating and stopping collagen damage early on in diabetic skin. Our results demonstrate that l-arginine attenuates the early collagen I alteration caused by diabetes and that it could be used to treat and prevent collagen damage in diabetic skin at a very early stage.
Fabrication of Artificial Nerve Conduits Used in a Long Nerve Gap: Current Reviews and Future Studies
Authors: Kakinoki Ryosuke , Hara Yukiko , Yoshimoto Koichi , Kaizawa Yukitoshi , Hashimoto Kazuhiko , Tanaka Hiroki , Kobayashi Takaya , Ohtani Kazuhiro , Noguchi Takashi , Ikeguchi Ryosuke , Akagi Masao , Goto Koji
Published: April 2024

There are many commercially available artificial nerve conduits, used mostly to repair short gaps in sensory nerves. The stages of nerve regeneration in a nerve conduit are fibrin matrix formation between the nerve stumps joined to the conduit, capillary extension and Schwann cell migration from both nerve stumps, and, finally, axon extension from the proximal nerve stump. Artificial nerves connecting transected nerve stumps with a long interstump gap should be biodegradable, soft and pliable; have the ability to maintain an intrachamber fibrin matrix structure that allows capillary invasion of the tubular lumen, inhibition of scar tissue invasion and leakage of intratubular neurochemical factors from the chamber; and be able to accommodate cells that produce neurochemical factors that promote nerve regeneration. Here, we describe current progress in the development of artificial nerve conduits and the future studies needed to create nerve conduits, the nerve regeneration of which is compatible with that of an autologous nerve graft transplanted over a long nerve gap.
Metformin Induces MeCP2 in the Hippocampus of Male Mice with Sex-Specific and Brain-Region-Dependent Molecular Impact
Authors: Arezoumand Khatereh Saei , Roberts Chris-Tiann , Rastegar Mojgan
Published: April 2024

Rett Syndrome (RTT) is a progressive X-linked neurodevelopmental disorder with no cure. RTT patients show disease-associated symptoms within 18 months of age that include developmental regression, progressive loss of useful hand movements, and breathing difficulties, along with neurological impairments, seizures, tremor, and mental disability. Rett Syndrome is also associated with metabolic abnormalities, and the anti-diabetic drug metformin is suggested to be a potential drug of choice with low or no side-effects. Previously, we showed that in vitro exposure of metformin in a human brain cell line induces MECP2E1 transcripts, the dominant isoform of the MECP2 gene in the brain, mutations in which causes RTT. Here, we report the molecular impact of metformin in mice. Protein analysis of specific brain regions in the male and female mice by immunoblotting indicated that metformin induces MeCP2 in the hippocampus, in a sex-dependent manner. Additional experiments confirm that the regulatory role of metformin on the MeCP2 target “BDNF” is brain region-dependent and sex-specific. Measurement of the ribosomal protein S6 (in both phosphorylated and unphosphorylated forms) confirms the sex-dependent role of metformin in the liver. Our results can help foster a better understanding of the molecular impact of metformin in different brain regions of male and female adult mice, while providing some insight towards its potential in therapeutic strategies for the treatment of Rett Syndrome.
Numerical Simulation of the Advantages of the Figure-Eight Flapping Motion of an Insect on Aerodynamics under Low Reynolds Number Conditions
Authors: Yoshida Masato , Fukui Tomohiro
Published: April 2024

In proceeding with the advanced development of small unmanned aerial vehicles (UAVs), which are small flying machines, understanding the flight of insects is important because UAVs that use flight are attracting attention. The figure-eight trajectory of the wing tips is often observed in the flight of insects. In this study, we investigated the more efficient figure-eight motion patterns in generating lift during the hovering motion and the relationship between figure-eight motion and Reynolds number. For this purpose, we compared the ratios of the cycle-averaged lift coefficient to the power coefficient generated from each motion by varying the elevation motion angle, which is the rotational motion that represents the figure-eight motion, and the Reynolds number. The result showed that the motion with a smaller initial phase of the elevation motion angle (φe0≤90°) could generate lift more efficiently at all Reynolds numbers. In addition, the figure-eight motion was more effective when the Reynolds number was low.
Strontium and Copper Co-Doped Multifunctional Calcium Phosphates: Biomimetic and Antibacterial Materials for Bone Implants
Authors: Lebedev Vladimir N. , Kharovskaya Mariya I. , Lazoryak Bogdan I. , Solovieva Anastasiya O. , Fadeeva Inna V. , Amirov Abdulkarim A. , Koliushenkov Maksim A. , Orudzhev Farid F. , Baryshnikova Oksana V. , Yankova Viktoriya G. , Rau Julietta V. , Deyneko Dina V.
Published: April 2024

β-tricalcium phosphate (β-TCP) is a promising material in regenerative traumatology for the creation of bone implants. Previously, it was established that doping the structure with certain cations can reduce the growth of bacterial activity. Recently, much attention has been paid to co-doped β-TCP, that is explained by their ability, on the one hand, to reduce cytotoxicity for cells of the human organism, on the other hand, to achieve a successful antibacterial effect. Sr, Cu-co-doped solid solutions of the composition Ca9.5–xSrxCu(PO4)7 was obtained by the method of solid-phase reactions. The Rietveld method of structural refinement revealed the presence of Sr2+ ions in four crystal sites: M1, M2, M3, and M4. The M5 site is completely occupied by Cu2+. Isomorphic substitution of Ca2+ → (Sr2+and Cu2+) expands the concentration limits of the existence of the solid solution with the β-TCP structure. No additional phases were formed up to x = 4.5 in Ca9.5–xSrxCu(PO4)7. Biocompatibility tests were performed on cell lines of human bone marrow mesenchymal stromal cells (hMSC), human fibroblasts (MRC-5) and osteoblasts (U-2OS). It was demonstrated that cytotoxicity exhibited a concentration dependence, along with an increase in osteogenesis and cell proliferation. Ca9.5–xSrxCu(PO4)7 powders showed significant inhibitory activity against pathogenic strains Escherichia coli and Staphylococcus aureus. Piezoelectric properties of Ca9.5–xSrxCu(PO4)7 were investigated. Possible ways to achieve high piezoelectric response are discussed. The combination of bioactive properties of Ca9.5–xSrxCu(PO4)7 renders them multifunctional materials suitable for bone substitutes.