bluuebunny/crossref_metadata_2025 huggingface dataset:
Interdependent Expansion Planning for Resilient Electricity and Natural Gas Networks
Authors: Pan Weiqi , Li Yang , Guo Zishan , Zhang Yuanshi
Published: April 2024

This study explores enhancing the resilience of electric and natural gas networks against extreme events like windstorms and wildfires by integrating parts of the electric power transmissions into the natural gas pipeline network, which is less vulnerable. We propose a novel integrated energy system planning strategy that can enhance the systems’ ability to respond to such events. Our strategy unfolds in two stages. Initially, we devise expansion strategies for the interdependent networks through a detailed tri-level planning model, including transmission, generation, and market dynamics within a deregulated electricity market setting, formulated as a mixed-integer linear programming (MILP) problem. Subsequently, we assess the impact of extreme events through worst-case scenarios, applying previously determined network configurations. Finally, the integrated expansion planning strategies are evaluated using real-world test systems.
H2 Reduction of Na2SO4 to Na2S Based on Dilute-Phase Fluidization
Authors: He Fang , Chen Yanxin , Zhao Bo , Chen Chang , Huang Song , Peng Shoubin
Published: April 2024

Sodium sulfate (Na2SO4) is used in the ecofriendly production of sodium sulfide (Na2S) through H2 reduction, thereby facilitating the valorization of Na2SO4. However, studies on this technique remain at the laboratory stage. This paper proposes a novel process involving the external circulation of Na2S in a dilute-phase fluidized system to address the low-temperature eutectic formation between Na2S and Na2SO4 during the H2 reduction of Na2SO4 to Na2S. The process aims to increase the reaction temperature of the Na2SO4 while reducing the volume of the liquid phase formed to prevent sintering blockages and enhance the reduction rate. In a proprietary experimental setup, the H2 reduction process in a dilute-phase fluidized system was investigated. The Na2S/Na2SO4 ratio and reaction temperature were determined to be critical factors influencing the Na2SO4 reduction rate. The melting point of the system increased and the amount of liquid phase produced decreased as the Na2S content was increased to more than 60%. The Na2S–Na2SO4 mixture (mass ratio of 80:20) existed as a solid at the reaction temperature of 740 °C. After roasting for 10 s, the Na2SO4 reduction rate reached 93.7% and the Na2S content in the mixture increased to 98.74%.
Application of Intercriteria and Regression Analyses and Artificial Neural Network to Investigate the Relation of Crude Oil Assay Data to Oil Compatibility
Authors: Shiskova Ivelina , Stratiev Dicho , Tavlieva Mariana , Nedelchev Angel , Dinkov Rosen , Kolev Iliyan , van den Berg Frans , Ribagin Simeon , Sotirov Sotir , Nikolova Radoslava , Veli Anife , Georgiev Georgi , Atanassov Krassimir
Published: April 2024

The compatibility of constituents making up a petroleum fluid has been recognized as an important factor for trouble-free operations in the petroleum industry. The fouling of equipment and desalting efficiency deteriorations are the results of dealing with incompatible oils. A great number of studies dedicated to oil compatibility have appeared over the years to address this important issue. The full analysis of examined petroleum fluids has not been juxtaposed yet with the compatibility characteristics in published research that could provide an insight into the reasons for the different values of colloidal stability indices. That was the reason for us investigating 48 crude oil samples pertaining to extra light, light, medium, heavy, and extra heavy petroleum crudes, which were examined for their colloidal stability by measuring solvent power and critical solvent power utilizing the n-heptane dilution test performed by using centrifuge. The solubility power of the investigated crude oils varied between 12.5 and 74.7, while the critical solubility power fluctuated between 3.3 and 37.3. True boiling point (TBP) analysis, high-temperature simulation distillation, SARA analysis, viscosity, density and sulfur distribution of narrow petroleum fractions, and vacuum residue characterization (SARA, density, Conradson carbon, asphaltene density) of the investigated oils were performed. All the experimentally determined data in this research were evaluated by intercriteria and regression analyses. Regression and artificial neural network models were developed predicting the critical solubility power with correlation coefficients R of 0.80 and 0.799, respectively.
Super-Resolution for Land Surface Temperature Retrieval Images via Cross-Scale Diffusion Model Using Reference Images
Authors: Chen Junqi , Jia Lijuan , Zhang Jinchuan , Feng Yilong , Zhao Xiaobin , Tao Ran
Published: April 2024

Geothermal resources are efficient, clean, and renewable energy sources. Using high-resolution images captured by remote sensing satellites for temperature retrieval and searching for geothermal anomaly areas is an efficient method. However, obtaining land surface temperature retrieval images requires multiple steps of calculation, which can result in a great loss of image information and resolution. Therefore, the super-resolution reconstruction of LST retrieval images is currently a challenge in geothermal resource exploration. Although the current super-resolution methods for LST retrieval images can appropriately restore image quality, the overall restoration of the surface temperature information in the region is still not ideal. We propose a cross-scale reference image super-resolution model based on a diffusion model using deep learning technology. First, we propose the Pre-Super-Resolution Network (PreNet), which can improve both indices and the visual effect of images. Second, to reduce the white noise in the super-resolution images, we propose the Cross-Scale Reference Image Attention Mechanism (CSRIAM). The introduction of this mechanism greatly reduces noise in the images and improves the overall image quality. Compared to previous methods, we improved both experimental indices such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), etc., and vision quality, and optimized the recovery of geothermal anomalies. Through our experimental results, we found that the CS-Diffusion model has a very strong ability to restore the image quality of the LST retrieval. After restoring its image quality, we can make a positive contribution to subsequent geothermal resource exploration.
Enhancing Aboveground Biomass Prediction through Integration of the SCDR Paradigm into the U-Like Hierarchical Residual Fusion Model
Authors: Zhang Ruofan , Peng Jialiang , Chen Hailin , Peng Hao , Wang Yi , Jiang Ping
Published: April 2024

Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning technique, termed Improved Supervised Contrastive Deep Regression (SCDR), which is adept at effectively capturing the nuanced relationships between samples and labels in the feature space, thereby mitigating this limitation. Simultaneously, we propose the U-like Hierarchical Residual Fusion Network (BioUMixer), a bespoke biomass prediction network tailored for image data. BioUMixer enhances feature extraction from biomass image data, facilitating information exchange and fusion while considering both global and local features within the images. The efficacy of the proposed method is validated on the Pepper_Biomass dataset, which encompasses over 600 original images paired with corresponding biomass labels. The results demonstrate a noteworthy enhancement in deep regression tasks, as evidenced by performance metrics on the Pepper_Biomass dataset, including RMSE = 252.18, MAE = 201.98, and MAPE = 0.107. Additionally, assessment on the publicly accessible GrassClover dataset yields metrics of RMSE = 47.92, MAE = 31.74, and MAPE = 0.192. This study not only introduces a novel approach but also provides compelling empirical evidence supporting the digitization and precision improvement of agricultural technology. The research outcomes align closely with the identified problem and research statement, underscoring the significance of the proposed methodologies in advancing the field of biomass prediction through state-of-the-art deep learning techniques.
The Effects of Supraharmonic Distortion in MV and LV AC Grids
Authors: Mariscotti Andrea , Mingotti Alessandro
Published: April 2024

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to preventing malfunctions and faults in electric assets and connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic—the supraharmonic 2 kHz to 150 kHz range. This range is not populated by easily recognizable harmonic components of the 50 Hz to 60 Hz mains fundamental, but by a combination of intentional emissions, switching non-linearities and byproducts, and various types of resonances. This paper aims to provide a detailed analysis of the impact of supraharmonics (SHs) on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and the heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference with equipment and power line communication (PLC) technology in particular. Under some shareable assumptions, limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with a specific focus on their accuracy.
Multi-Sensor Laser System for Electric Guitar Pitch-Detection
Authors: Pesatori Alessandro , Norgia Michele
Published: April 2024

To attain a direct MIDI output from an electric guitar, we devised and implemented a sophisticated laser sensor system capable of measuring finger positions. This sensor operates on the principle of optical triangulation, employing six lasers and seven position-sensing detectors that are time-multiplexed. The speed and precision of this sensor system meet the necessary criteria for creating an electric guitar with a direct digital output, perfectly satisfying the application’s requirements.
Design and Non-Linearity Optimization of a Vertical Brushless Electric Power Steering Angle Sensor
Authors: Chen Jie , Guo Yanling
Published: April 2024

This paper presents the design and the non-linearity optimization of a new vertical non-contact angle sensor based on the electromagnetic induction principle. The proposed sensor consists of a stator part (with one solenoidal excitation coil and three sinusoidal receiver coils) and a rotor part (with six rectangular metal sheets). The receiver coil was designed based on the differential principle, which eliminates the effect of the excitation coil on the induced voltage of the receiver coil, and essentially decouples the excitation field from the eddy current field. Moreover, the induced voltages in the three receiver coils are three-phase sinusoidal signals with a phase difference of 10°, which are linearized by CLARK transformation. To minimize the sensor non-linearity, the Plackett–Burman technique was used, which identified the stator radius and the rotor blade thickness as the key factors affecting the sensor linearity. Then, the particle swarm algorithm with decreasing inertia weights was utilized to optimize the sensor linearity. A sensor prototype was made and tested in the laboratory, where the experimental results showed that the sensor non-linearity was only 0.648% and 0.645% in the clockwise and counterclockwise directions, respectively. Notably, the non-linearity of the sensor was less than −0.696% at different speeds.
Federated Learning with Pareto Optimality for Resource Efficiency and Fast Model Convergence in Mobile Environments
Authors: Jung June-Pyo , Ko Young-Bae , Lim Sung-Hwa
Published: April 2024

Federated learning (FL) is an emerging distributed learning technique through which models can be trained using the data collected by user devices in resource-constrained situations while protecting user privacy. However, FL has three main limitations: First, the parameter server (PS), which aggregates the local models that are trained using local user data, is typically far from users. The large distance may burden the path links between the PS and local nodes, thereby increasing the consumption of the network and computing resources. Second, user device resources are limited, but this aspect is not considered in the training of the local model and transmission of the model parameters. Third, the PS-side links tend to become highly loaded as the number of participating clients increases. The links become congested owing to the large size of model parameters. In this study, we propose a resource-efficient FL scheme. We follow the Pareto optimality concept with the biased client selection to limit client participation, thereby ensuring efficient resource consumption and rapid model convergence. In addition, we propose a hierarchical structure with location-based clustering for device-to-device communication using k-means clustering. Simulation results show that with prate at 0.75, the proposed scheme effectively reduced transmitted and received network traffic by 75.89% and 78.77%, respectively, compared to the FedAvg method. It also achieves faster model convergence compared to other FL mechanisms, such as FedAvg and D2D-FedAvg.
An Online Digital Imaging Excitation Sensor for Wind Turbine Gearbox Wear Condition Monitoring Based on Adaptive Deep Learning Method
Authors: Tao Hui , Zhong Yong , Yang Guo , Feng Wei
Published: April 2024

This paper designed and developed an online digital imaging excitation sensor for wind power gearbox wear condition monitoring based on an adaptive deep learning method. A digital imaging excitation sensing image information collection architecture for magnetic particles in lubricating oil was established to characterize the wear condition of mechanical equipment, achieving the real-time online collection of wear particles in lubricating oil. On this basis, a mechanical equipment wear condition diagnosis method based on online wear particle images is proposed, obtaining data from an engineering test platform based on a wind power gearbox. Firstly, a foreground segmentation preprocessing method based on the U-Net network can effectively eliminate the interference of bubbles and dark fields in online wear particle images, providing high-quality segmentation results for subsequent image processing, A total of 1960 wear particle images were collected in the experiment, the average intersection union ratio of the validation set is 0.9299, and the accuracy of the validation set is 0.9799. Secondly, based on the foreground segmentation preprocessing of wear particle images, by using the watered algorithm to obtain the number of particles in each size segment, we obtained the number of magnetic particle grades in three different ranges: 4–38 µm, 39–70 µm, and >70 µm. Thirdly, we proposed a method named multidimensional transformer (MTF) network. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are used to obtain the error, and the maintenance strategy is formulated according to the predicted trend. The experimental results show that the predictive performance of our proposed model is better than that of LSTM and TCN. Finally, the online real-time monitoring system triggered three alarms, and at the same time, our offline sampling data analysis was conducted, the accuracy of online real-time monitoring alarms was verified, and the gearbox of the wind turbine was shut down for maintenance and repair.
Tool Condition Monitoring Using Machine Tool Spindle Current and Long Short-Term Memory Neural Network Model Analysis
Authors: Turšič Niko , Klančnik Simon
Published: April 2024

In cutting processes, tool condition affects the quality of the manufactured parts. As such, an essential component to prevent unplanned downtime and to assure machining quality is having information about the state of the cutting tool. The primary function of it is to alert the operator that the tool has reached or is reaching a level of wear beyond which behaviour is unreliable. In this paper, the tool condition is being monitored by analysing the electric current on the main spindle via an artificial intelligence model utilising an LSTM neural network. In the current study, the tool is monitored while working on a cylindrical raw piece made of AA6013 aluminium alloy with a custom polycrystalline diamond tool for the purposes of monitoring the wear of these tools. Spindle current characteristics were obtained using external measuring equipment to not influence the operation of the machine included in a larger production line. As a novel approach, an artificial intelligence model based on an LSTM neural network is utilised for the analysis of the spindle current obtained during a manufacturing cycle and assessing the tool wear range in real time. The neural network was designed and trained to notice significant characteristics of the captured current signal. The conducted research serves as a proof of concept for the use of an LSTM neural network-based model as a method of monitoring the condition of cutting tools.
A New Planar Potentiometric Sensor for In Situ Measurements
Authors: Lenar Nikola , Piech Robert , Paczosa-Bator Beata
Published: April 2024

A new construction of a potentiometric sensor was introduced for the first time. It relies on the use of two membranes instead of one, as in the well-known coated-disc electrode. For this purpose, a new electrode body was constructed, including not one, but two glassy carbon discs covered with an ion-selective membrane. This solution allows for the sensor properties to be enhanced without using additional materials (layers or additives) on the membrane. The new construction is particularly useful for in situ measurements in environmental samples. Two ion-selective polymeric membranes were used, namely H+ and K+-selective membranes, to confirm the universality of the idea. The tests conducted included chronopotentiometric tests, electrochemical impedance spectroscopy, and potentiometric measurements. The electrical and analytical parameters of the sensors were evaluated and compared for all tested electrodes to evaluate the properties of the planar electrode versus previously known constructions. Research has shown that the application of two membranes instead of one allows for the resistance of an electrode to be lowered and for the electrical capacitance to be elevated. Improving the electrical properties of an electrode resulted in the enhancement of its analytical properties. The pH measurement range of the planar electrode is 2–11, which is much wider in contrast to that of the single-membrane electrode. The linear range of the K+-selective planar electrode is wider than that of the coated-disc electrode and equals 10−6 to 10−1 M. The response time turned out to be a few seconds shorter, and the potential drift was smaller due to the application of an additional membrane in the electrode construction. This research creates a new opportunity to design robust potentiometric sensors, as the presented construction is universal and can be used to obtain electrodes selective to various ions.
Stroke Steadiness as a Determinant Factor of Performance in 100 m Freestyle in Young Swimmers
Authors: López-Plaza Daniel , Quero-Calero Carmen Daniela , Alacid Fernando , Abellán-Aynés Oriol
Published: April 2024

The classical kinematic variables in swimming are based on the calculation of mean values. Stroke steadiness determines the relationship between the duration of all consecutive strokes throughout a test. The aims of the current investigation were to examine differences in stroke-to-stroke steadiness according to swimmers’ performance level on both body sides (breathing and non-breathing) and to analyse the interrelationship with kinematics during a 100 m front-crawl test. Thirty-two young, experienced swimmers voluntarily participated in the present study and were divided into two groups, national level (n = 15) and local level (n = 17), according to their competitive status within the national age-rankings. All participants performed a 100 m maximal test in a 50 m pool where they were laterally recorded. Kinematic variables such as mean velocity, stroke rate, stroke length, and stroke index, as well as long-term steadiness and short-term steadiness, were calculated. The two 50 m sections were analysed independently. Significant differences were observed between the two groups in the classical kinematic variables and in stroke steadiness (p < 0.05). In addition, stroke steadiness showed moderately high correlations with velocity (r = [−0.61–(−0.749)]) and stroke index (r = [−0.356–(−0.582)]). Maintaining a more stable inter-stroke period appears to be a determinant of performance in young, high-level national swimmers.
Expectations and Outcomes when Quantifying Energy Improvements Achieved by Building Envelope Retrofitting
Authors: Martín-Consuegra Fernando , Ludueña Camila Andrea , De Frutos Fernando , Frutos Borja , Alonso Carmen , Oteiza Ignacio
Published: April 2024

This paper assesses the energy efficiency of two buildings constructed in the 1960s in Madrid. One of the buildings is refurbished including passive energy efficiency improvements, while the other remains in its original state. The area is one of a series of low-income residential inefficient developments built by the state on the capital’s outskirts in the 1950s. Their buildings require huge amounts of energy to meet occupants’ basic energy needs. This paper quantifies the energy savings and improved comfort achieved by building envelope energy retrofitting. For this purpose, it proposes a comprehensive methodology spanning data monitoring in homes in buildings, occupant surveys and energy simulation models—a standard approach to estimating improvement potential. Our aim is to compare the expected energy savings predicted by energy certificates with monitored data. The paper concludes that the comfort level in the retrofitted building improved tangibly but that the differing behaviours of the building’s occupants make the energy saving difficult to quantify with any precision. The calibrated model targets energy consumption savings after renovation of approximately 25% in heating and 50% in cooling for a typical household of four people with basic comfort needs reasonably met. Regarding heating consumption, the results of the calibrated model are lower than expected savings using the official certificate input data. However, cooling consumption savings were found to be greater than expected.
Temporal Variations in Urban Air Pollution during a 2021 Field Campaign: A Case Study of Ethylene, Benzene, Toluene, and Ozone Levels in Southern Romania
Authors: Petrus Mioara , Popa Cristina , Bratu Ana-Maria
Published: April 2024

This study focused on quantifying the gas concentrations of ethylene, benzene, toluene, and ozone within an urban area in the southern region of Romania. The gas sampling campaign, conducted between March and August 2021, took place in three different locations from the point of view of the architectural structure, and the sampling height was 1.5 m. Sampling occurred on weekdays (Monday through Friday) during daylight hours, with subsequent concentration analysis employing descriptive statistics, diurnal cycles, and seasonal assessments. A highly sensitive and selective detector, employing laser photoacoustic spectroscopy, was utilized to monitor pollutants. The average concentrations (±Standard Deviation) were determined as follows: ethylene at 116.82 ± 82.37 parts per billion (ppb), benzene at 1.13 ± 0.32 ppb, toluene at 5.48 ± 3.27 ppb, and ozone at 154.75 ± 68.02 ppb, with peak levels observed during the summer months. Diurnal patterns were observable for ethylene, benzene, and toluene, exhibiting higher concentrations during the early hours of the day followed by a decrease towards the evening. In contrast, ozone concentrations peaked in the evening compared to the early part of the day. Thus, perceptible effects were demonstrated on gas concentrations as a result of the influence of meteorological variables. Moreover, the high toluene/benzene ratio indicated traffic and industrial emissions as primary sources of these pollutants. Of the four gases monitored, benzene and ozone exceeded regulatory limits, particularly during the summer season, highlighting concerns regarding air quality in the studied urban environment.
A Relaxed Inertial Method for Solving Monotone Inclusion Problems with Applications
Authors: Zong Chunxiang , Tang Yuchao , Zhang Guofeng
Published: April 2024

We study a relaxed inertial forward–backward–half-forward splitting approach with variable step size to solve a monotone inclusion problem involving a maximal monotone operator, a cocoercive operator, and a monotone Lipschitz operator. The convergence of the sequence of iterations generated by the discretisations of a continuous-time dynamical system is established under suitable conditions. Given the challenges associated with computing the resolvent of the composite operator, the proposed method is employed to tackle the composite monotone inclusion problem. Additionally, a convergence analysis is conducted under certain conditions. To demonstrate the effectiveness of the algorithm, numerical experiments are performed on the image deblurring problem.
Three-Dimensional Visualization of Shunt Valves with Photon Counting CT and Comparison to Traditional X-ray in a Simple Phantom Model
Authors: Klempka Anna , Clausen Sven , Soltane Mohamed Ilyes , Ackermann Eduardo , Groden Christoph
Published: April 2024

This study introduces an application of innovative medical technology, Photon Counting Computer Tomography (PC CT) with novel detectors, for the assessment of shunt valves. PC CT technology offers enhanced visualization capabilities, especially for small structures, and opens up new possibilities for detailed three-dimensional imaging. Shunt valves are implanted under the skin and redirect excess cerebrospinal fluid, for example, to the abdominal cavity through a catheter. They play a vital role in regulating cerebrospinal fluid drainage in various pathologies, which can lead to hydrocephalus. Accurate imaging of shunt valves is essential to assess the rate of drainage, as their precise adjustment is a requirement for optimal patient care. This study focused on two adjustable shunt valves, the proGAV 2.0® and M. blue® (manufactured by Miethke, Potsdam, Germany). A comprehensive comparative analysis of PC CT and traditional X-ray techniques was conducted to explore this cutting-edge technology and it demonstrated that routine PC CT can efficiently assess shunt valves’ adjustments. This technology shows promise in enhancing the accurate management of shunt valves used in settings where head scans are already frequently required, such as in the treatment of hydrocephalus.
Neurotoxicity of Combined Exposure to the Heavy Metals (Pb and As) in Zebrafish (Danio rerio)
Authors: Liu Ming , Deng Ping , Li Guangyu , Liu Haoling , Zuo Junli , Cui Wenwen , Zhang Huixian , Chen Xin , Yao Jingjing , Peng Xitian , Peng Lijun , Liu Jiao , Zheng Wenting , Yan Wei , Luan Ning
Published: April 2024

Lead (Pb) and arsenic (As) are commonly occurring heavy metals in the environment and produce detrimental impacts on the central nervous system. Although they have both been indicated to exhibit neurotoxic properties, it is not known if they have joint effects, and their mechanisms of action are likewise unknown. In this study, zebrafish were exposed to different concentrations of Pb (40 μg/L, 4 mg/L), As (32 μg/L, 3.2 mg/L) and their combinations (40 μg/L + 32 μg/L, 4 mg/L + 3.2 mg/L) for 30 days. The histopathological analyses showed significant brain damage characterized by glial scar formation and ventricular enlargement in all exposed groups. In addition, either Pb or As staining inhibited the swimming speed of zebrafish, which was enhanced by their high concentrations in a mixture. To elucidate the underlying mechanisms, we examined changes in acetylcholinesterase (AChE) activity, neurotransmitter (dopamine, 5-hydroxytryptamine) levels, HPI axis-related hormone (cortisol and epinephrine) contents and neurodevelopment-related gene expression in zebrafish brain. The observations suggest that combined exposure to Pb and As can cause abnormalities in swimming behavior and ultimately exacerbate neurotoxicity in zebrafish by interfering with the cholinergic system, dopamine and 5-hydroxytryptamine signaling, HPI axis function as well as neuronal development. This study provides an important theoretical basis for the mixed exposure of heavy metals and their toxicity to aquatic organisms.
Upper Bound of Barrow Entropy Index from Black Hole Fragmentation
Authors: Xia Jiayi , Ong Yen Chin
Published: April 2024

Both classical and quantum arguments suggest that if Barrow entropy is correct, its index δ must be energy-dependent, which would affect the very early universe. Based on thermodynamic stability that sufficiently large black holes should not fragment, we argue that Barrow entropy correction must be small, except possibly at the Planckian regime. Furthermore, the fact that a solar mass black hole does not fragment implies an upper bound δ≲O(10−3), which surprisingly lies in the same range as the bound obtained from some cosmological considerations assuming fixed δ. This indicates that allowing δ to run does not raise its allowed value. We briefly comment on the case of Kaniadakis entropy.
A New Solution of the Pulsar Equation
Authors: Contopoulos Ioannis , Dimitropoulos Ioannis , Ntotsikas Dimitris , Gourgouliatos Konstantinos N.
Published: April 2024

We present the first new type of solution of the pulsar equation since 1999. In it, the whole magnetosphere is confined inside the light cylinder and an electrically charged layer wraps around it and holds it together. The reason this new solution has never been obtained before is that all current time-dependent simulations are initialized with a vacuum dipole configuration that extends to infinity; thus, their final steady-state solution also extends to infinity. Under special conditions, such a confined configuration may be attained when the neutron star first forms in the interior of a collapsing star during a supernova explosion, or when it accretes from an external wind or disk from a donor star. It is shown that this new maximally closed non-decelerating solution is the limit of a continuous sequence of standard magnetospheres with open and closed field lines when the amount of open field lines gradually drops to zero. The minimum energy solution in this sequence is a standard magnetosphere in which the closed field line region extends up to about 80% of the light cylinder. We estimate that the released energy when the new solution transitions to the minimum energy one is enough to power a fast radio burst.
Combining Cellular Immunization and Phage Display Screening Results in Novel, FcγRI-Specific Antibodies
Authors: Krohn Steffen , Holtrop Tosca , Brandsma Arianne M. , Moerer Petra , Nederend Maaike , Darzentas Nikos , Brüggemann Monika , Klausz Katja , Leusen Jeanette H. W. , Peipp Matthias
Published: April 2024

Antibodies that specifically bind to individual human fragment crystallizable γ receptors (FcγRs) are of interest as research tools in studying immune cell functions, as well as components in bispecific antibodies for immune cell engagement in cancer therapy. Monoclonal antibodies for human low-affinity FcγRs have been successfully generated by hybridoma technology and are widely used in pre-clinical research. However, the generation of monoclonal antibodies by hybridoma technology that specifically bind to the high-affinity receptor FcγRI is challenging. Monomeric mouse IgG2a, IgG2b, and IgG3 bind human FcγRI with high affinity via the Fc part, leading to an Fc-mediated rather than a fragment for antigen binding (Fab)-mediated selection of monoclonal antibodies. Blocking the Fc-binding site of FcγRI with an excess of human IgG or Fc during screening decreases the risk of Fc-mediated interactions but can also block the potential epitopes of new antibody candidates. Therefore, we replaced hybridoma technology with phage display of a single-chain fragment variable (scFv) antibody library that was generated from mice immunized with FcγRI-positive cells and screened it with a cellular panning approach assisted by next-generation sequencing (NGS). Seven new FcγRI-specific antibody sequences were selected with this methodology, which were produced as Fc-silent antibodies showing FcγRI-restricted specificity.
Green Hydrogen Driven by Wind and Solar—An Australian Case Study
Authors: Currie Glen , Behrens Edward , Bolitho Samuel , Coen Michael , Wilson Thomas
Published: April 2024

The energy transition to wind and solar opens up opportunities for green hydrogen as wind and solar generation tend to bring electricity prices down to very low levels. We evaluate whether green hydrogen can integrate well with wind and solar PVs to improve the South Australian electricity grid. Green hydrogen can use membrane electrolysis plants during periods of surplus renewable energy. This hydrogen can then be electrified or used in industry. The green hydrogen system was analysed to understand the financial viability and technical impact of integrating green hydrogen. We also used system engineering techniques to understand the system holistically, including the technical, social, environmental, and economic impacts. The results show opportunities for the system to provide seasonal storage, grid firming, and reliability services. Financially, it would need changes to electricity rules to be viable, so at present, it would not be viable without subsidy.
Parenting Styles in Emerging Adulthood
Authors: Jensen Michaeline , Navarro Jessica L. , Chase Gregory E. , Wyman Kacey , Lippold Melissa A.
Published: April 2024

Parents/caregivers remain important in the lives of emerging adults in the modern era and understanding the ways in which parents of emerging adults balance responsiveness, demandingness, and autonomy support can help inform evidence-based recommendations around developmentally appropriate protective parenting. The present study identified four “parenting styles” in emerging adulthood in a sample of 680 4-year university and community college students (M = 19.0, ranging from 18 to 25; 70.7% female, 22.6% male) who reported on their primary parent/caregiver’s parenting behaviors. These parenting styles largely overlapped with traditional conceptualizations of parenting styles (two authoritarian profiles, a potentially indulgent profile, and a profile characterized by the average levels of all parenting behaviors measured, which may reflect the modern authoritative parenting style of emerging adults). No hypothesized overparenting profile emerged. The potentially indulgent profile saw the lowest levels of depression, mood, and anxiety symptoms, whereas the potentially indulgent and authoritative profiles saw the most positive wellbeing outcomes. The findings underscore the way in which responsiveness and autonomy support in emerging adulthood appear developmentally appropriate and adaptive, and how helicopter parenting does not appear to be as important as other aspects of parent–emerging adult relationships.
Study of physicians’ preferences for pharmacotherapy of arterial hypertension in pregnant women (the PHYGEST study)
Authors:   FSBEI HE Mari State University, Yoshkar-Ola, Republic of Mari El, Russia, Bontsevich R. A. ,   FSAEI HE Belgorod National Research University, Belgorod,Russia Kazan State Medical Academy — Branch of the FSBEI CPE Russian Medical Academy of Continuous Professional Education,Kazan, Balamutova T. I. ,   OOO «Promedika»=, Belgorod, Russia, Chukhareva N. A. ,   Fomin Clinic of Women's Health, Moscow, Russia, Tsygankova O. V. ,   FSBEI HE Novosibirsk State Medical University, Novosibirsk, Research Institute of Internal and Preventive Medicine — Branch of the Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Science, Novosibirsk, Russia, Batishcheva G. A. ,   FSBEI HE Voronezh State Medical University named after N. N. Burdenko, Voronezh, Russia, Kompaniets O. G. ,   FSBEI HE Kuban State Medical University, Krasnodar,Russia, Ketova G. G. ,   FSBEI HE South Ural State Medical University, Chelyabinsk,  Russia, Bogdanova V. O. ,   National Medical Research Center of Endocrinology,Moscow, Russia; FSBEI HE Pacific State Medical University, Vladivostok, Russia, Nevzorova V. A. ,   FSBEI CPE Russian Medical Academy of Continuous Medical Education, Moscow,  Russia, Martynenko I. M. ,   FSBEI CPE Russian Medical Academy of Continuous Medical Education, Moscow,  Russia, Pakhomov S. P. ,   FSBEI HE Kursk State Medical University of the Ministry of Health of Russia, Kursk, Russia, Maksimov M. L. ,   Kazan State Medical Academy — Branch of the FSBEI CPE Russian Medical Academy of Continuous Professional Education, FSAEI HE Pirogov Russian National Research Medical University of the Ministry of Health of Russia, Moscow,Russia
Published: April 2024

Introduction: Elevated blood pressure in a pregnant woman is associated with serious risks for the mother and fetus. Therefore, the issues of rational antihypertensive pharmacotherapy are always extremely relevant in the scientific community. Purpose of the Study: To determine the preferences of physicians in the issues of pharmacotherapy for pregnant women with arterial hypertension and evaluate the influence of specialists’ length of employment. Materials and Methods: A multicenter study (a pharmacoepidemiologic knowledge assessment) was conducted in 2018–2021 using an anonymous questionnaire with open-ended questions. This paper discusses 5 questions of the questionnaire. Results and Discussion: The preferences of practicing specialists (411 physicians from 8 regions of Russia) for the prescription of basic and additional drugs for the treatment and prevention of hypertension, the impact of the physicians’ length of employment, and the degree of compliance with current clinical guidelines were determined. Conclusions: Certain specific and not fully rational specialists’ preferences were revealed, which confirms the importance of attention to this problem and requires the introduction of additional educational and supervisory efforts in this direction, as well as the continuation of similar studies in the future.
Mentoría en la formación docente como base para el aprendizaje significativo de las competencias investigativas
Authors: Navarro-Navarro Bertha , Sánchez Ortega Jaime Agustín , Rodríguez Rojas Milagritos Leonor
Published: April 2024

En este estudio se asume la mentoría como la relación intencional y de confianza que vincula a mentores y mentorizados para desarrollar competencias del saber. El objetivo fue analizar la mentoría en la formación docente como base para el aprendizaje significativo de las habilidades investigativas. La metodología es de enfoque cualitativo y el paradigma naturalista interpretativo. Para la recolección de la información se utilizó la técnica de la entrevista en profundidad. Los informantes claves fueron siete (7) docentes, trece (13) estudiantes y seis (6) especialistas de las asignaturas relacionadas a la investigación científica. Se evidenció en las opiniones de la comunidad universitaria, en tanto docentes y estudiantes, sobre el vínculo entre mentoría y el aprendizaje significativo para la investigación formativa dista de ser unívoco y refleja que la praxis pedagógica se sustenta en presupuestos no siempre coincidentes con el modelo institucional declarado.
Clases virtuales y aprendizaje del cálculo integral en tiempos de pandemia
Authors: Núñez Mejía Joel , García Vilca Marlene Julissa , Túllume Huayanay Haydeé Verónica
Published: April 2024

La pandemia ha dado lugar a realizar clases virtuales, las cuales son aquellas que se realizan en entornos virtuales y requiere de estrategias para mantener conectados a los estudiantes para lograr su aprendizaje. Esta investigación tiene como finalidad establecer la relación entre las clases virtuales y el aprendizaje del cálculo integral en tiempo de pandemia. La metodología fue propuesta bajo un enfoque cuantitativo, diseño correlacional no experimental; posteriormente de una población de 90 estudiantes de una universidad privada, sólo aceptaron formar parte de la investigación 60 estudiantes de la carrera de ingeniería de sistemas, matriculados en matemática II, que incluye el cálculo integral, a los cuales se aplicó un cuestionario Likert y aplicando el SPSS, el coeficiente de correlación Rho de Spearman fue 0.377, lo que indica que existe correlación entre variables. Finalmente se concluyó que existe relación entre las clases virtuales y el aprendizaje del cálculo integral.
La conciencia fonológica y su relación con la lectura: Revisión sistemática
Authors: Valle-Zevallos María-Johana , Mendez-Vergaray Juan , Flores Edward
Published: April 2024

El estudio se centra en analizar la relación entre el desarrollo de la conciencia fonológica y la competencia lectora en estudiantes durante el período de 2018 a 2022. Se llevó a cabo una revisión sistemática siguiendo el método PRISMA, con búsqueda de artículos en la base de datos SCOPUS utilizando descriptores conciencia fonológica”, “conciencia semántica”, “conciencia silábica”, conciencia morfológica” y “conciencia pragmática” en español e inglés. La investigación se enfocó en las categorías de conciencia fonológica y decodificación lectora. Se seleccionaron 31 artículos para el análisis final. Los resultados revelaron la importancia del desarrollo temprano de la conciencia fonológica, especialmente durante la educación preescolar y los primeros años de educación primaria, para el éxito en la lectura. Se encontró una relación significativa entre la conciencia fonológica y la lectura en estudiantes oyentes, con déficit perceptuales y bilingües. Se destaca la necesidad de implementar programas metalingüísticos para abordar las dificultades lectoras de manera oportuna.
Actitud del docente para retroalimentar en la didáctica pedagógica: Una revisión sistemática
Authors: Campos Campos Ysaias , Santisteban Cajusol César Humberto , Morales Cornetero Lucía Del Rocio
Published: April 2024

La actitud docente relacionada con la retroalimentación es una unión inseparable en el quehacer pedagógico, donde docentes y estudiantes cumplen roles complementarios para generar aprendizajes exitosos; por ello, el estudio tiene por objetivo analizar la actitud docente para asumir la retroalimentación en la didáctica pedagógica. Asimismo, se empleó la metodología de revisión sistemática, la búsqueda y selección de información se realizó en bases de datos y plataformas como Scopus, Scielo, GoogleScholar. Los resultados de búsquedas quedaron establecidos en 12 fuentes según criterios de inclusión y exclusión. se concluye en que la retroalimentación es una estrategia de gran importancia para el proceso educativo, y toma relevancia cuando el docente asume actitudes positivas frente a su trabajo pedagógico. Dichas actitudes deben ser formadas y fortalecidas desde los centros de estudios superiores para ser volcados en las aulas.
La psicomotricidad en el desarrollo de la lectoescritura en educación inicial. Revisión documental
Authors: Viera Prada Lily Isabel
Published: April 2024

La psicomotricidad en el desarrollo de las habilidades para leer y escribir es un planteamiento de amplia aceptación en el proceso educativo. El trabajo de investigación se planteó como objetivo analizar los estudios sobre la vinculación existente entre la psicomotricidad con el desarrollo de los procesos de lectura y escritura. La metodología tuvo un enfoque cualitativo, utilizando la guía PRISMA para la identificación, selección y análisis variado de investigaciones disponibles entre 2012 hasta 2022, en las bases de datos Scopus, Google Scholar, Concytec, ESBCO y ProQuest. Como conclusión se evidenció la trascendencia de la psicomotricidad para el aprendizaje de la lectoescritura, especialmente en el nivel de educación inicial, influenciando el crecimiento integral del ser humano, tanto individual como socialmente.
Exploring the Nexus between the Blue Economy and Information Technologies: A Systematic Literature Review of Information Systems in Pacific Fisheries and Aquaculture
Authors: Doce Lumer Jude Parreño , Catedrilla Jypzie Malacad , Dela Vega Christine Jan Blabagno , Limpin Laiza Lemery , Ambalong Khalil Anton , Trillo Jose II T.
Published: April 2024

The blue economy has garnered significant importance over the years as a major driver for sustainable economic growth in the Pacific region through the efficient utilization of marine resources. While a thorough examination of the whole gamut of information about information and communication technologies (ICT) gains momentum, establishing a cohesive perspective on pivotal findings within blue economy research, particularly in fisheries and aquaculture, becomes essential for maximizing the potential of this interdisciplinary field. Consequently, Information Systems (IS) researchers, through a comprehensive review of pertinent literature, can contribute significantly to this emerging body of knowledge. Our review, which encompasses 32 papers published from 2012 to 2022, focuses on the application of information technologies to Pacific fisheries and aquaculture. The prevailing literature enhances our understanding of the adoption and utilization of ICTs (i.e. Geographic Information Systems (GIS), remote sensing and satellite imaging, database management systems and other emerging technologies) within the blue economy. In this paper, we provide discussions on recent technological advancements and future research directions to encourage IS researchers to develop an effective cumulative tradition of research.
X-ray Diffraction Line Profile Analysis of Natural Calcite Minerals found in Southern Philippines by Williamson-Hall Method
Authors: Dardo Raymond Benedict C. , Jagus Rommel J. , Imura Masataka , Banal Ryan G.
Published: April 2024

This study employs the Williamson–Hall (W–H) models to examine the microstrains and crystallite sizes of CaCO3 occurring as calcite in limestone samples found in General Santos City and Sarangani Province, Southern Philippines. Using both the Uniform Deformation Model (UDM) and Uniform Stress  Deformation (USDM) models, computations for average sizes were established to be identical, implying minimal strain influence. The consistency of resulting measurements extends to the microstrain, revealing uniform results for all samples. Correlation between crystallite sizes and microstrains in the calcite crystals was observed, where high-purity calcites exhibited larger crystallite sizes and microstrains. The crystallite sizes decrease with microstrains for calcites with higher Mg concentration, a finding that can be attributed to lattice distortion and the formation of defects. The release of stress forms these defects, thereby resulting in a reduction of microstrains. Moreover, the distinctly variable responses to strain exhibited by the samples could be influenced by either their anisotropic properties or other additional components. The W–H models, used jointly with UDM and USDM consistently predicted crystallite sizes, and thus offer valuable insights into the uniform stress responses of calcites. These promising results notwithstanding, USDM is shown to be especially relevant for anisotropic samples owing to the display deviations of crystallite sizes, a key feature of anisotropic natural calcites. The microscopic analysis is expected to provide additional understanding regarding the state of the limestone samples.