bluuebunny/crossref_metadata_2025 huggingface dataset:
Microcapsule preparation process research and current status of oilfield application
Authors: Wang Sicai , Zhang Qun , Xiu Jianlong , Ma Yuandong , Huang Lixin , Yi Lina , Fu Haowei
Published: August 2024

Traditional tertiary oil recovery methods are fraught with challenges such as significant reagent adsorption, voluminous injection requirements, limited sweep efficiency, and inadequate intelligent targeting. These issues lead to suboptimal displacement of residual oil, resulting in the inability to mobilize substantial crude oil resources and thus yielding low recovery rates. Microcapsules—spherical particles with micron or nanometer scale diameters—have been extensively utilized across various sectors, including food storage, targeted drug encapsulation, and fragrance containment, owing to their distinct advantages in controlled release, isolation, and targeted delivery. These applications have successfully achieved industrialization and commercialization. In recent years, numerous researchers have explored the application of microcapsule preparation processes to diverse facets of oil extraction, with the aim of further enhancing oil recovery (EOR). This article elucidates the mechanism of action of microcapsules, their preparation methods (encompassing in situ polymerization, interfacial polymerization, spray drying, solvent evaporation, phase separation, and supercritical CO2‐assisted techniques), characterization and evaluation methodologies, among other aspects. It encapsulates the current status and principal challenges associated with the application of microcapsule preparation processes in oilfield development and probes the potential and pivotal research directions for their oilfield applications.
Prediction of power generation and maintenance using AOC‐ResNet50 network
Authors: Chu Yueqiang , Cao Wanpeng , Xiao Cheng , Song Yubin
Published: August 2024

With the continuous expansion of the photovoltaic industry, the application of solar photovoltaic power generation systems is becoming increasingly widespread. Due to the obvious intermittency and volatility of photovoltaic power generation, integration of large‐scale photovoltaic power generation into the power grid can cause certain impacts on the security and stability of the grid. Photovoltaic power prediction is essential to solve this problem, as it can improve the quality of photovoltaic grid connection, optimize grid scheduling, and ensure the safe operation of the grid. In this article, the deep learning method is selected for photovoltaic power prediction. Based on the analysis of the OctConv (Octave Convolution) network structure, the AOctConv (Attention Octave Convolution) convolutional neural network structure is proposed, which is combined with the ResNet50 backbone network to obtain AOC‐ResNet50. It is then applied to the prediction of the generation of photovoltaic power. The prediction performance is compared with the ResNet50 network and the Oct‐ResNet50 network, and it is found that the AOC‐ResNet50 network has the best prediction performance, with an MAE of only 0.176888. Based on the exemplar work, a framework is proposed to illustrate this method. Its general application is discussed.
A two‐stage reactive power optimization method for distribution networks based on a hybrid model and data‐driven approach
Authors: Abbas Ghulam , Zhi Wu , Ali Aamir
Published: August 2024

The uncertainty of distributed energy resources (DERs) and loads in distribution networks poses challenges for reactive power optimization and control timeliness. The computational limitations of the traditional algorithms and the development of artificial intelligence (AI) based technologies have promoted the advancement of hybrid model‐data‐driven algorithms. This article proposes a two‐stage reactive power optimization method for distributed networks (DNs) based on a hybrid model‐data‐driven approach. In the first stage, based on the topology and line parameters of the DN, as well as forecasts of loads and renewable energy outputs, a mixed‐integer second‐order cone programming (MISOCP) algorithm is used to control the on‐load tap changer (OLTC) positions on an hourly day‐ahead basis. In the second stage, leveraging deep learning technology, the real‐time reactive power output of photovoltaics (PV) and wind power units is controlled at a 5‐min time scale throughout the day. Specifically, using traditional solvers, the global optimal reactive power output for PV and wind power units is determined first, corresponding to various load and renewable energy output scenarios. Then, neural networks are trained to map node power to the optimal reactive power outputs of renewable energy units, capturing the complex physical relationships. For the second stage, a transformer network framework with a self‐attention mechanism and multi‐head attention for deep learning training is applied to uncover the intrinsic and physical spatial relationships among high‐dimensional features. The proposed method is tested on a modified IEEE 33‐bus system with multiple distributed renewable energy sources. The case study results demonstrate that the proposed hybrid model‐data‐driven algorithm effectively coordinates day‐ahead and real‐time controls of various devices, achieving real‐time model‐free optimization throughout the day. Compared to traditional deep neural networks (DNNs) and convolutional neural networks (CNNs), the transformer network provides superior reactive power optimization results.
Nonparametric Bayesian reconstruction of Galactic magnetic fields using information field theory
Authors: Tsouros Alexandros , Bendre Abhijit B. , Edenhofer Gordian , Enßlin Torsten , Frank Philipp , Mastorakis Michalis , Pavlidou Vasiliki
Published: August 2024

Context. Ultrahigh-energy cosmic rays (UHECRs) are charged particles with energies surpassing 1018 eV. Their sources remain elusive because they are obscured by deflections caused by the Galactic magnetic field (GMF). This challenge is further complicated by our limited understanding of the 3D structure of the GMF because current GMF observations primarily consist of quantities that are integrated along the line of sight (LOS). Nevertheless, data from upcoming stellar polarization surveys along with Gaia stellar parallax data are expected to yield local GMF measurements.

Aims. This study is the second entry in our exploration of a Bayesian inference approach to the local GMF that uses synthetic local GMF observations that emulate forthcoming local GMF measurements, and attempts to use them to reconstruct its 3D structure. The ultimate aim is to trace back observed UHECRs and thereby update our knowledge about their possible origin.

Methods. In this proof-of-concept work, we assumed as ground truth a magnetic field produced by a dynamo simulation of the Galactic ISM. We employed methods of Bayesian statistical inference in order to sample the posterior distribution of the GMF within part of the Galaxy. By assuming a known rigidity and arrival direction of an UHECR, we traced its trajectory back through various GMF configurations drawn from the posterior distribution. Our objective was to rigorously evaluate the performance of our algorithm in scenarios that closely mirror the setting of expected future applications. In pursuit of this, we conditioned the posterior to synthetically integrated LOS measurements of the GMF, in addition to synthetic local plane of sky-component measurements.

Results. Our results demonstrate that for all locations of the observed arrival direction on the plane of sky, our algorithm is able to substantially update our knowledge on the original arrival direction of UHECRs with a rigidity of E/Z = 5 × 1019 eV, even without any LOS information. When the integrated data are included in the inference, the regions of the celestial sphere in which the maximum error occurs are greatly reduced. The maximum error is diminished by a factor of about 3 even in these regions in the specific setting we studied. Additionally, we are able to identify the regions in which the largest error is expected to occur.
Implementing new Approaches of Digitization in Conventional Metal Forming Processes: A German perspective
Authors: Liewald Mathias , Schenek Adrian , Deliktas Tahsin , Beck Maxim , Görz Marcel
Published: August 2024

The Institute for Metal Forming Technology (IFU) at the University of Stuttgart / Germany since more than six years strongly strives to future oriented research work focusing on far-reaching concepts for digitization of metal forming processes. Main activities of engaged research groups are integrating sensors and actuators into metal forming machines or dies to analyse process data gained that way. Also, development of advanced methods for production data mining are related to those fields of activities. The paper therefore highlights strategies and practical applications of such digitization concepts. Also, important issues in terms of metal forming production processes will be addressed such as avoidance of scrap during ramp up phases and batch processing. Finally, the practical use of machine learning algorithms will be demonstrated in real trimming and metal forming processes.
Study on the damage behaviour of titanium alloy laser-welded blank during hot gas pressure forming
Authors: Wu Di , Huang Shuaijun , Wang Kehuan , Wen Zehua , Liu Gang
Published: August 2024

The damage behaviour of titanium alloy laser-welded seam during hot gas pressure forming was studied by experiment and simulation. The GTN damage model was used to simulate the hot gas pressure forming process of the welded blank. The evolution of the void volume fraction during the forming process was obtained. Hot gas pressure forming experiments of cup-shaped parts were carried out. The microstructure at different positions of the cup-shaped part was observed by scanning electron microscope. Results show that the damage to the weld seam during hot gas pressure forming was mainly related to the strain. The damage of the inside fillet near the flange develops most rapidly, and it easily cracks due to the large deformation during the free bulging stage. The damage on the bottom centre develops slowly at the free bulging stage. After the bottom of the cup-shaped part contacted the die, the volume fraction of damage on the bottom center continued to increase firstly and then reached to a stable value gradually. Various micro cracks were observed during the hot gas pressure forming. The volume fraction of cracks increased with the increasing strain, and the small cracks gradually grew, expanded, and merged to form larger cracks. It is important to control the maximum strain of the weld seam during the forming to avoid possible harmful damage.
Optimization of process parameters for LPBF forming TC11/SiC single track
Authors: Chen Siyuan , Shu Xuedao , Li Ziyuan , Wang Dongwei , Ren Zhihao
Published: August 2024

Titanium matrix composite parts with excellent mechanical properties can be obtained by laser powder bed fusion (LPBF) by introducing nano SiC ceramic particles into titanium and titanium alloys. In order to cope with the instability of the forming quality of the parts caused by the addition of SiC particles, this paper proposes to explore the quality of single-track melt under different process parameters, to optimize the parameters more accurately to achieve better forming quality. In this paper, the influence of process parameters on the morphology and geometric size of the molten pool is studied, and the optimal molten track morphology parameters are selected for printing experiments. The results show that when the thickness of the powder layer = 30um is the optimal process parameter with the laser power 170 W, the scanning speed 1100 mm/s and the line energy density 0.155 J/mm. At this time, the molten track of TC11/SiC formed by LPBF process is continuous and stable, with good surface morphology.
Use of Multi-pass FSP treatment for improving mechanical properties and corrosion resistance of Mg-2Zn-HA composite
Authors: Kumar Sharma Gaurav , Singh Grewal Navdeep , Kumar Kamal
Published: August 2024

Magnesium (Mg) alloys are very popular among the biomaterials for biodegradable bone implants due to their suitable properties matching with that of human cortical bone. However, their poor corrosion resistance in biological fluid is a major constraint to become an ideal choice for bioimplants. The corrosion resistance of Mg-alloys is further retarded with microstructural impurities such as micro-pores, micro cracks, heterogeneous distribution of alloying element etc., which is commonly present in as-cast Mg-alloys. In present study, Friction stir processing (FSP) has been performed on Mg-2Zn alloy to refine the microstructures as well as to develop Mg-Zn-HA composites by using HA powder reinforcement. HA powder reinforcement was added using micro-grooves and multiple FSP passes on as-cast Mg-2Zn alloy having average grain size of 63.86 µm. Filling HA powder in 2-grooves and using 3-pass FSP, a refined microstructure having an average grain size of 7.15 µm and homogeneous distribution of HA powder was obtained for the developed Mg-Zn-HA composite. The Mg-Zn-HA composite developed with 3-pass FSP treatment has shown significant improvement in tensile strength and corrosion resistance as compared with as-cast Mg-alloy.
Remote sensing mission sentinel pro: Analysis of satellite tracking, control, and health monitoring system with solar tracking capability
Authors: Baig Muhammad W. , Shafik Mahmoud
Published: August 2024

Nowadays, satellite systems are experiencing noticeable disruptive issues due to the single functionality, high cost of operations, and limited adaptability. This paper presents a satellite mission control system with RF duplex communication, which gives multiple functionalities and health monitoring systems with solar tracking capability. This aims to present a flexible and affordable solution called the Remote Sensing Mission Sentinel Pro Platform. The quantitative approach is used and implemented to trans-receive data from space and pass it to the ground station. Arduino-based prototype uses the nRF24L01 module with an antenna at the ground station to trans-receive satellite data has been developed. Testing and verifications of the developed platform prototype indicated that satellites could monitor key health parameters, including temperature, humidity, and battery charge capacity.
An advanced product inspection and sorting system using artificial intelligence
Authors: Adekeye Esther Owora , Shafik Mahmoud , Ozioko Oliver
Published: August 2024

The manufacturing sector is experiencing a notable transformation due to the incorporation of Industry 4.0 and the emerging concepts of Industry 5.0. Artificial intelligence (AI) plays a significant role in driving this transformation, particularly in the domain of product inspection and sorting systems. Incorporating digital computer vision, high accuracy and resolution sensors, and bigdata-driven simulations into manufacturing processes, the vision of smart manufacturing becomes tangible. These technologies offer practical solutions for automating product inspection and sorting processes, providing non-destructive and cost-effective alternatives. This ongoing research aims to develop a real-time product inspection and sorting system utilising artificial intelligence, specifically focusing on convolutional neural networks (CNNs) and machine learning algorithms. The proposed approach adopts a dynamic methodology, leveraging the synergistic capabilities of CNNs and machine learning algorithms. To extract features from images, CNN is trained on datasets containing both none-defective and defective product samples. These features are then further refined and classified by machine learning algorithms. Through rigorous training on diverse datasets, the system developed a robust ability to distinguish between none-detective and defective products and achieving an accuracy close to 98.10%
IoT platform for offshore wind turbine blade structure health monitoring
Authors: Zhou Xingguo , Tian Yankang , Qin Yi
Published: August 2024

Wind energy, as renewable energy, is critical in targeting carbon neutrality or net zero emissions in order to address global climate change. Compared with onshore wind turbines, offshore wind turbines enjoy generally higher wind speed, thus producing more electric energy. However, the harsh marine environment, including high winds, wave-induced vibrations and and sea and rain corrosion and erosion, can lead to structural damage, reduced operational efficiency and increased maintenance cost. This paper presents a novel Internet of Things (IoT) platform for structural health monitoring (SHM) of the offshore wind turbine’s key component, the wind turbine blades. This research focuses on developing a comprehensive, real-time monitoring system that utilises advanced sensor networks, edge computing, and advanced predictive algorithms to strengthen on-time maintenance of turbine blades, while avoiding unnecessary and costly regular maintenance.
Characterisation of Bio composites for Bio-Manufacturing: Jute-reinforced Bacterial Cellulose for Construction
Authors: Turhan-Haskara Gozde Damla
Published: August 2024

This research investigates the biological, mechanical and thermal characterisation of the jute-reinforced bacterial cellulose biocomposites to forecast their potential and performance in bio-manufacturing for architectural construction. The experimental trial-and-error-based methodology involves seven stages: Material formulation, manufacturing of biocomposite samples, mechanical testing, scanning electron microscopy analysis, thermogravimetric analysis, and biodegradation assessment. The results indicated that the use of biobased construction materials has a potential to reduce carbon footprint, while the addition of jute fibres resulted in enhanced mechanical properties such as higher elasticity and desirable stiffness compared to pure bacterial cellulose. Moreover, slight distinctions in thermal property analysis and biodegradation assessments across the specimens are observed. The findings contribute valuable data for material selection, design optimization, and structural considerations in the integration of these biopolymers into construction practices. Overall, this research aligns with the broader objective of advancing ecological construction starting from the material formulations, thus addressing the scalability of these materials, considering their potential for large-scale adoption in the construction industry.
Development of an on-machine surface measurement system for an ultra-precision five-axis machine
Authors: Zhong Wenbin , Zeng Wenhan , Yu Guoyu , Jiang Xiangqian
Published: August 2024

Ever-increasing demand for complex freeform surfaces machined by ultra-precision five-axis machines necessitates efficient on-machine surface measurement (OMSM) systems. While OMSM offers significant advantages in metrology efficiency and machining accuracy, integrating it with these machines presents a challenge due to complex data synchronization and processing. This paper addresses this challenge by proposing a dedicated controller for synchronized acquisition of sensor measurement data and machine coordinate data. Additionally, a straightforward sensor alignment method is presented. The effectiveness of the proposed OMSM system is demonstrated through successful 2D and 3D measurements, significantly streamlining the traditional time-consuming offline coordinate measuring machine (CMM) and optical profilometer measurements.
Staging of Early-Stage Lung Cancer without Routine PET in Candidates for Segmentectomy
Authors: Lopez-Pastorini Alberto , Tatli Zehra , von Bargen Antonia , Faltenberg Dennis , Beling Hendrik , Koryllos Aris , Galetin Thomas , Stoelben Erich
Published: August 2024

Introduction We aimed to investigate the accuracy of clinical staging without the routine use of positron emission tomography/computed tomography (PET/CT) in patients with cIA1 and cIA2 non-small-cell lung cancer (NSCLC) scheduled for segmentectomy.

Methods A total of 305 consecutive segmentectomies were retrospectively analyzed. Overall survival was calculated using the Kaplan–Meier method. Logistic regression was performed to investigate factors independently associated with pathologic upstaging.

Results The Union for International Cancer Control (UICC) upstaging was found in 86 patients (28%). Upstaged patients had longer operative times (146 ± 46 vs. 131 ± 44 minutes, p = 0.009), a higher number of lymph node resection (17 ± 10 vs. 13 ± 8, p = 0.001), and a higher rate of L1 involvement (34 vs. 16%, p < 0.001) than nonupstaged patients. N1 was found in 10 patients (3%) and N2 in 13 patients (4%). Nodal positive patients had longer operation times (154 ± 50 vs. 133 ± 44 minutes, p = 0.031) and higher rates of R1 (9 vs. 1%, p = 0.006) and L1 (39 vs. 20%, p < 0.026) than patients without nodal involvement. The 3- and 5-year overall survival rates for nonupstaged and upstaged patients were 85 and 67% and 67 and 54%, respectively (p = 0.040). In logistic regression, L1 involvement (odds ratio [OR]: 2.394, p = 0.005) and the number of dissected lymph nodes (OR: 1.037, p = 0.016) were independently associated with upstaging. Patients who received PET as part of clinical staging did not have a significantly lower nodal upstaging.

Conclusion Selective use of PET/CT based on the results of CT may be a viable option for patients with proven or suspected NSCLC up to 2 cm in size.
Evaluation of Cardiac Function in Patients with Supratentorial Tumors and Raised Intracranial Pressure: HABIT-ICP, a Prospective Observational Study Using Transthoracic Echocardiography
Authors: Sethuraman Manikandan , P. Ajay Prasad Hrishi , Ajayan Neeraja , Prathapadas Unnikrishnan , Vimala Smita , S. Ranganatha Praveen C.
Published: August 2024

Objective An acute increase in intracranial pressure (ICP) has been shown to affect cardiac function due to brain ischemia and the associated increased sympathetic activity. However, there is limited literature on the changes in cardiac function in clinical scenarios where there is a gradual and progressive increase in ICP, such as in brain tumors. We aimed to assess and compare the cardiac function in patients with primary supratentorial brain tumors presenting with and without raised ICP for neurosurgery.

Materials and Methods In this prospective observational study, we included 60 patients; Group I (30 patients without features of raised ICP) and Group II (30 patients with features of raised ICP). Transthoracic echocardiography was performed on the day before the surgery and the seventh postoperative day. Hemodynamic, electrocardiographic, and echocardiographic parameters were obtained during pre-, intra-, and postoperative periods and were used for statistical analysis.

Results We found an increased relative wall thickness and an increased incidence of systolic (22%) and diastolic dysfunction (33.3%) in Group II compared with Group I patients. There was an increased incidence of intraoperative adverse events such as postinduction hypotension and vasopressor use in Group II patients. In the postoperative period, there was an improvement in the systolic function; however, the chamber dimensions and diastolic dysfunction did not improve significantly.

Conclusion Our study suggests that raised ICP might contribute to the pathophysiology of sympathetic overactivity and sympathetically driven cardiac dysfunction, which does not entirely revert in the immediate postoperative period.
Frequency-astigmatism asymmetric nonlinear conversion of structured light lasers
Authors: Pan Jing , Wang Hao , Shi Zijian , Shen Yijie , Fu Xing , Liu Qiang
Published: August 2024

Nonlinear optics of structured light carrying orbital angular momentum (OAM) has recently led to intriguing fundamental physical effects in light–matter interactions and advanced applications from classical imaging to quantum informatics. However, the mutual interaction between spatial mode and frequency conversions in nonlinear processes is still elusive. In this work, we go beyond only considering OAM and frequency in nonlinear structured light conversion and investigate the complex mode evolution in cascaded nonlinear frequency conversion and spatial astigmatic mode conversion. In particular, we unveil a generalized law of nonlinear structured light from experiments and theories, that the converted modes are highly related to the sequence of frequency and spatial mode conversions, obeying an inherent (non)commutative rule in which. This effect not only creates extended structured laser modes but serves as regular rules in nonlinear optics.
Performance analyses of active aerodynamic load balancing designs on high-performance vehicles in cornering conditions
Authors: Rijns Steven , Teschner Tom-Robin , Blackburn Kim , Brighton James
Published: August 2024

This study presents a comprehensive investigation into the impact of active aerodynamic load balancing (AALB) on the cornering performance of high-performance vehicles. The research explores the use of active asymmetric aerodynamic devices, specifically split and tilted rear wing concepts, capable of manipulating vertical wheel loads and counteracting effects of lateral load transfer during cornering. The performance potential of AALB is assessed through quasi-steady static coupling of aerodynamic data with a detailed vehicle dynamics model. The findings show that inside bias operating states of the split rear wing and tilted rear wing concepts, which favor loads on the inside tires, can improve cornering velocities up to 0.5% and 2% compared to high symmetric operating states, respectively. Noteworthy, through effective distribution of aerodynamic loads, the inside bias operating states produce less downforce and drag, thereby reducing the propulsion power required to overcome drag by 15%–20%, depending on the cornering condition. The tilted rear wing concept demonstrates the highest AALB capability and most consistent response to its control strategy, accredited to its ability to generate vertical and horizontal aerodynamic force components. It can, therefore, achieve over 1% higher maximum cornering velocities compared to the split rear wing, while also offering efficiency benefits. Overall, the research highlights the effectiveness of AALB in improving cornering performance and efficiency, offering valuable insights for the development of advanced active aerodynamic solutions in automotive design and paving the way for future advancements in the field.
Self-aligned gate electrode for hydrogen-terminated diamond field-effect transistors with a hexagonal boron nitride gate insulator
Authors: Sasama Yosuke , Iwasaki Takuya , Monish Mohammad , Watanabe Kenji , Taniguchi Takashi , Takahide Yamaguchi
Published: August 2024

Diamond electronic devices have attracted significant interest owing to their excellent semiconducting properties. We recently demonstrated that eliminating surface-transfer doping enhances carrier mobility and achieves normally off behavior in diamond field-effect transistors (FETs) with a hexagonal boron nitride (h-BN) gate insulator. In our previous study, the gate electrode was overlapped onto the source/drain electrodes to prevent the increase in access resistance caused by excluding surface-transfer doping. However, it is known that gate overlap increases parasitic capacitance and gate leakage current. In this study, we developed a technique for self-aligning the gate electrode with the edge of h-BN using oblique-angle deposition. The diamond FET with a self-aligned gate electrode exhibits optimal FET characteristics, including high mobility of ≈ 400 cm2V−1s−1, low sheet resistance of 2.4 kΩ, and output characteristics demonstrating pinch-off behavior. Furthermore, the capacitance-voltage characteristics clearly indicate distinct ON and OFF states, validating the efficacy of this technique. This method enables the fabrication of diamond/h-BN FETs with no gate overlap and without increasing access resistance, making it a promising approach for developing high-speed, low-loss diamond FETs with a wide range of applications.
First-principles study on pressure-induced superconductivity and structural design on transition metal diborides
Authors: Zhou Chao , Yu Hongyu , Zhang Zihan , Yu Zekun , Zhu Jinming , Bao Kuo , Cui Tian
Published: August 2024

Recent experiments on α-MoB2 with MgB2-type structure achieved superconductivity at ∼32 K under 90 GPa, the highest among transition-metal diborides, rekindling interest in their superconducting properties. Our study systematically investigates the band structures of AlB2-type transition metal diborides. We found that the superior superconductivity of MoB2, WB2, and TcB2 correlates with their von Hove singularities near the Fermi level (EF), potentially linked to electron–phonon coupling. These three diborides exhibit similar critical temperature (Tc) trends under pressure: rising initially, peaking around 60 GPa, and then declining. While unstable at ambient pressure, their thermodynamic and dynamical stability limits vary significantly, possibly explaining experimental discrepancies. To stabilize MoB2 at ambient pressure, we designed MoXB4 compounds (X = other transition metals) by substituting every other Mo layer in MoB2 with an X layer. This modification aims to stabilize the structure and enhance superconductivity by reducing d-electron concentration at EF. This principle extends to other potential superconducting diborides, such as WB2 and TcB2. Using Nb as an example, we found that Nb atoms in AlB2-type MoNbB4 may exhibit random occupancy, potentially explaining disparities between theoretical predictions and experimental results. Our study offers valuable insights into superconductivity in transition metal diborides, paving the way for future research and applications.
Rapid non-contact viscosity measurement based on optical coherence tomography
Authors: Zhang Yuxian , Zhang Fan , Wang Chongyang , Zhu Jiang
Published: August 2024

Viscosity measurement is crucial in biomedical research and clinical diagnosis. Currently, rapid and non-contact methods for measuring viscosity remain challenging. We propose a method based on optical coherence tomography for fast, remote assessment of the liquid viscosity. The viscosity of the liquid sample was quantified according to Poiseuille's law, the flow velocity was determined using optical coherence tomography, and the real-time pressure difference was measured by two manometers. Glycerol–water mixtures with various viscosities were tested to assess the accuracy of the optical coherence tomography (OCT) viscosity measurement. Then, blood samples with different levels of hemodilution and hematocrit were measured to validate the feasibility of the OCT method in the blood viscosity measurement. The results indicate that the proposed method can provide rapid, non-contact liquid viscosity measurement. It could significantly impact research on hemodynamics and diagnosis of blood disorders.
Facile synthesis of stable 1T′-WSe2 for HER application
Authors: Debnath Anup , Sen Nabanita , Das Arnab , Bhattacharjee Souvik , Dey Suman , Satpati Biswarup , Chattopadhyay Kalyan Kumar
Published: August 2024

Researchers are increasingly drawn to WSe2 due to its wide-ranging applications in electronic, optoelectronic, and catalytic materials. Like other transition metal dichalcogenides, it has different polymorphs, viz., 1T, 1T′, and 2H phases. A hexagonal close-packed layer-type structure of 2H-WSe2 is well studied and possesses a semiconducting behavior. However, the literature lacks a detailed study of crystallographic structure, facile synthesis, and different physical properties of 1T′-WSe2 (or 1T-phase). In this article, we synthesized a stable flower-like 1T′-WSe2 nanosheet in a facile solvothermal process. We also tried to explore the structural details using the Rietveld refinement of the powder x-ray diffraction data. The different Raman vibrational modes and phonon calculation based on the density functional theory (DFT) were performed to understand the stability of the 1T′-WSe2 phase. The flower-like 1T′-WSe2 nanosheet shows better catalytic activity for the hydrogen evolution reaction (HER) with an onset potential of −0.21 mV and overpotential 0.47 mV in comparison with the 2H-phase of WSe2 nanosheet. The DFT calculations also support the experimental data on the HER of 1T′-WSe2, establishing the suitability of the 1T′-phase for HER activity with the lowest value of the change in Gibbs free energy of hydrogen adsorption, ΔGH = 0.43 eV, for the monolayer.
Decision tree learning with random forest models using agricultural and ecological field data incorporating multi-factor studies and covariate structure
Authors: Dhanoa M.S. , Sanderson R. , Lister S.J. , Cardenas L.M. , Ellis J.L. , López S. , France J.
Published: August 2024

In this study, the decision learning methods of regression tree and random forest analysis are investigated as complements to standard statistical methods such as analysis of variance and grouped regression. For this purpose, three diverse data sets were used. The first set is large and multidimensional and describes nitrous oxide emissions from sites across different geo-positions in the UK receiving various fertilisation treatments. The second set is based on Gliricidia tree provenances and has a small number of samples and an imbalanced distribution of factor classes. Random forest modelling was found to be a very viable option in the case of the first data set but failed in the case of second. The third data set, based on count observations recording osprey egg incubation times, lends itself to tree and forest modelling. These decision learning methods therefore appear well suited to handling the diverse, multi-dimensional and complex data sets that often arise in carrying out agricultural and ecological field experiments.
Photon traps in nonlinear electrodynamics
Authors: Goulart Érico , Bittencourt Eduardo
Published: August 2024

We demonstrate the existence of photon traps within the framework of nonlinear electrodynamics. The trapping mechanism is based on the fact that, for null background fields, the optical metric reduces to the Kerr–Schild form, which plays a prominent role in the context of black hole physics. We then construct explicit examples where photons are confined in a region of spacetime, such that a distant observer cannot interact with them. Finally, we argue that the trapping scheme is quite universal, being entirely compatible with causality, energy conditions, and hyperbolicity.
Impact of dark sector preheating on CMB observables
Authors: Garcia Marcos A.G. , Pereyra-Flores Aline
Published: August 2024

The prediction of a nearly scale-invariant spectrum of curvature and tensor fluctuations is among the main features of cosmic inflation. The current measurements of the primordial fluctuations in the cosmic microwave background (CMB) provide tight constraints on the amplitude of the scalar and tensor spectra, and the scalar tilt. However, the precise connection between these observables and a given inflationary model, depends on the expansion history between the end of inflation and the beginning of the radiation dominated era, which corresponds to the reheating epoch. This mapping between horizon exit and reentry of fluctuations, parametrized by the number of e-folds N*, can therefore be affected by the presence of a transient epoch of non-perturbative particle production during reheating (preheating). Using a combination of perturbative and lattice computations, we quantify the impact of preheating in a non-equilibrated dark matter sector on the CMB observables, under the assumption of a simultaneous perturbative decay of the inflaton into Standard Model particles. Combined with structure formation constraints, this allows us to impose stringent bounds on the post-inflationary reheating temperature.
Induced gravitational wave interpretation of PTA data: a complete study for general equation of state
Authors: Domènech Guillem , Pi Shi , Wang Ao , Wang Jianing
Published: August 2024

We thoroughly study the induced gravitational wave interpretation of the possible gravitational wave background reported by PTA collaborations, considering the unknown equation of state w of the early universe. We perform a Bayesian analysis of the NANOGrav data using the publicly available PTArcade code together with SIGWfast for the numerical integration of the induced gravitational wave spectrum. We focus on two cases: a monochromatic and a log-normal primordial spectrum of fluctuations. For the log-normal spectrum, we show that, while the results are not very sensitive to w when the GW peak is close to the PTA window, radiation domination is out of the 2σ contours when only the infra-red power-law tail contributes. For the monochromatic spectrum, the 2σ bounds yield 0.1 ≲ w ≲ 0.9 so that radiation domination is close to the central value. We also investigate the primordial black hole (PBH) abundance for both monochromatic and log-normal power spectrum. We show that, in general terms, a larger width and stiffer equation of state alleviates the overproduction of PBHs. No PBH overproduction requires w ≲ 0.57 up to 2-σ level for the monochromatic spectrum. Furthermore, including bounds from the cosmic microwave background, we find in general that the mass range of the PBH counterpart is bounded by 10-5
M
⊙ ≲ M
PBH ≲ 10-1
M
⊙. Lastly, we find that the PTA signal can explain the microlensing events reported by OGLE for w ~ 0.7. Our work showcases a complete treatment of induced gravitational waves and primordial black holes for general w for future data analysis.
Incremental Conductance Method in Maximum Power Point Tracking
Authors: Andrasto Tatyantoro , Primadiyono Yohanes , Hidayat Syahroni , Sandyawan Bernadus , Fauzi Ahmad Rizqi , Khairul Azis Mukhammad
Published: August 2024

The power characteristic curve in photovoltaic system is non-linear fluctuating based on changes in solar irradiation and module surface temperature. MPPT is a system of tracking the maximum power point of solar panels at any change in irradiation and temperature. Incremental conductance is one of the maximum power tracking methods that can be applied to the MPPT with the input of solar panel voltage and solar panel current. DC-DC Converter is inseparable from the role of MPPT system. MPPT is integrated by implementing DC-DC Converter synchronous buck topology. The system is validated through computational simulations in simulink. Implementation of MPPT product design based on incremental conductance using Arduino Uno to be applied to a 50Wp single solar panel stand-alone. Measurement parameters are displayed on the LCD and data streamer as a monitoring system. The results of the study were conducted by comparing the two topologies of DC-DC converter on the MPPT system, from the comparison of the two topologies of DC-DC converter effect of Drain-Source resistance and forward voltage internal diode to the output power of solar panels showed that the MPPT system that implements the DC-DC converter synchronous buck is able to. Efficiency by implementing DC-DC converter synchronous buck reached 98.2% while the implementation using DC-DC Conveter buck topology reached 97.2% at 1000W/m2.
Characteristics Visitors of Indonesia Kaya Park, Semarang, Central Java
Authors: Harjanti Intan Muning , Budiati Lilin , Ardanareswari Ayu Sagita
Published: August 2024

The existence of urban parks is expected to be in accordance with the needs and desires of the community, so it is necessary to involve the community in the process of providing urban parks. The purpose of this study is to determine the characteristics of visitors in Indonesia Kaya Park, which are categorized based on socioeconomic and visiting patterns. The approach used is positivistic deductive, quantitative descriptive analysis method. Data collection is done by questionnaire and field observations. The results showed that the characteristics of visitors in Taman Indonesia Kaya based on socio-economics were dominated by visitors coming from Semarang, with female gender, age range 17-25 included in the category of early adolescents, the last level of high school / vocational education, and the type of student work / student. While based on the pattern of visits, the results obtained that the majority of visitors aim to sit / gather / walk, with a frequency of visits as much as 2-4 times, and the length of visit between 1-2 hours, and most visitors go with friends. The reason visitors come is because the place is comfortable and the mode of transportation used by visitors is dominated by motorcycles. The results of this study can be used to determine patterns and behaviour of urban park users in interacting in public spaces.
Influence of HSS drill coatings on surface finish and cylindricity of AA6061/C/ZrO2 composite in CNC drilling operations under dry conditions
Authors: P Haja Syeddu Masooth , V Jayakumar , G Bharathiraja , Mekonnin Keno Teshome
Published: August 2024

This study aims to evaluate the effect of HSS drill tool coatings, namely single-layer TiN, single-layer AlCrN, and double-layer AlTiN + TiSiXN (Durana), on the surface roughness and cylindricity of AA6061 (90 wt%)/C (5 wt%)/ZrO2 (5 wt%) hybrid composite material processed by the stir casting method. The fabricated sample was examined for the uniform particle distribution of reinforcements using Scanning Electron Microscope. The drilling operation was carried out on the fabricated in a CNC machining center by setting the spindle speeds of 800, 1200, and 1600 rpm, depths of cut of 0.5, 1, and 1.5 mm, and feeds of 50, 100, and 150 mm/rev. An orthogonal array (L27) designed by Taguchi’s method was used as the design of the experiment for the optimization of the best cutting parameters and coating. Surface roughness and cylindricity errors were determined for the 27 experimental runs. Field emission scanning electron microscopic (FESEM) examination and Energy Dispersive Spectroscopy (EDS) were used to analyze the surface integrity and elemental composition, respectively. The results revealed that Durana had a significant effect on the surface substrate with minimum surface roughness (Ra) of 1.666 μm and obtained the minimum cylindricity error for the parameters of depth of cut 0.5 mm, spindle speed of 1200 and feed of 100 mm rev−1.
Tuning the structural and mechanical properties of SiC-Li and SiC-Na alloys for aerospace application: an ab initio study
Authors: Otieno Ochieng Victor , Ongwen Nicholas , Otieno Calford
Published: August 2024

Aluminum (Al) and its alloys are popular in the aerospace industry due to their high strength-to-weight ratio, corrosion resistance, and ductility. However, these properties (extreme ductility and malleability) can compromise corrosion resistance, making them susceptible to dents and scratches. Silicon Carbide (SiC) is a promising alternative to Al and it alloys due to its higher Youngs modulus and excellent wear resistance, although it has the drawbacks of brittleness and higher density. This study investigated the structural and mechanical properties of SiC alloyed with lithium (SiC-Li) or sodium (SiC-Na) using ab initio calculations with the aim of tuning the structural and mechanical properties of SiC. Modeling was done using Burai software, which offers a friendly graphical user interface for Quantum ESPRESSO, thus facilitating the creation of input files, visualization of crystal structures and analysis of results. The results from this study showed that the addition of Li and Na lowered the density as well as the mechanical properties of SiC but still being favorably better than those of Al and its alloys, suggesting that the modeled alloys could potentially replace the traditional Al and its alloys in the aerospace industry. Further experimental studies are needed to validate these findings and to explore the possibility of simultaneous alloying of SiC with both Li and Na for enhanced performance.
Development and functional testing of battery management system algorithm for an electric bicycle using hardware in the loop testbench
Authors: Siddharth M , A Rammohan
Published: August 2024

An embedded Battery Management System (BMS) ensures the effective functionality and longevity of the vehicle battery systems. Testing the BMS using the Hardware in Loop (HIL) approach effectively increases safety and reduces product development time in the manufacturing sector. This research aims to develop an efficient battery management system with two-level protection for electric bicycles and test its functionality in the HIL configuration. The bicycle traction model and battery management system were first developed using a model-based design. Further, the model is tested and validated using battery emulators in the HIL methodology. The battery management system receives input data, such as current, voltage, and temperature, and monitors these parameters. The first level of protection involves the vehicle user receiving the warning when the monitoring parameters values exceed the given first safety threshold. As per the second safety threshold values, the BMS trips off the charging or discharging process when the voltage is 51V, the charge current is 5A, the discharge current is -5A and the IC temperature is 80 degrees. Also, BMS balances the cells in 3.84 min using passive balancing. Additionally, the BMS delivers a controlled current of 2.5A for safe battery charging. This methodology increases safety by reducing the potential risks of testing the BMS algorithms in the actual electric bicycle.
Exotic families of embeddings
Authors: Auckly Dave , Ruberman Daniel
Published: August 2024

We construct a number of topologically trivial but smoothly non-trivial families of embeddings of

3
3

-manifolds in

4
4

-manifolds. These include embeddings of homology spheres in

S
4

S^4

that are not isotopic but have diffeomorphic complements, and families (parameterized by high-dimensional spheres) of embeddings of any

3
3

-manifold that embeds in a blown-up

K
3

K3

surface. In each case, the families are constructed so as to be topologically trivial in an appropriate sense. We also illustrate a general technique for converting a non-trivial family of embeddings into a non-trivial family of submanifolds.
Blowup formulas for Segre and Verlinde numbers of surfaces and higher rank Donaldson invariants
Authors: Göttsche Lothar
Published: August 2024

We formulate conjectural blowup formulas for Segre and Verlinde numbers on moduli spaces of sheaves on projective surfaces

S
S

with

p
g

(
S
)
>
0

p_g(S)>0

and

b
1

(
S
)
=
0

b_1(S)=0

. As application we give a give a conjectural formula for the Donaldson invariants of

S
S

in arbitrary rank, generalizing the famous structure formula for Donaldson invariants of Kronheimer and Mrowka. Furthermore we give conjectural formulas for the

K
K

-theoretic Donaldson invariants, as well as for some Donaldson invariants with fundamental matters.
A splitting formula in instanton Floer homology
Authors: Anvari Nima
Published: August 2024

In a recent paper, Lin, Ruberman and Saveliev proved a splitting formula expressing the Seiberg-Witten invariant

λ

S
W

(
X
)

\lambda _{SW}(X)

of a smooth

4
4

-manifold with rational homology of

S
1

×

S
3

S^1\times S^3

in terms of the Frøyshov invariant

h
(
X
)

h(X)

and a Lefschetz number in reduced monopole Floer homology. In this note we observe that a similar splitting formula holds in reduced instanton Floer homology.
The Second Reconstruction, 1954–1971
Authors: Wiecek William M
Published: August 2024

This chapter considers the attempts to achieve some measure of equality between whites and African Americans through constitutional and legal change amid the civil rights era. It explains that the second Reconstruction ended servitude based on de jure discrimination, which correlates to how the first Reconstruction ended slavery. However, both Reconstruction eras did not exactly succeed in establishing comprehensive racial equality and came to a premature end. The chapter highlights that the US Supreme Court was the godparent of the civil rights era, citing that the second Reconstruction would not have happened without the Warren Court. It also notes the challenges to state statutes that prohibit interracial sex or marriage.