Real-time Observation Research Articles

Tropical cyclone tracking for autonomous underwater vehicles based on forecast path correction model

To meet the demand for unmanned observation of tropical cyclones and to improve the tracking efficiency of multiple autonomous underwater vehicles (Multi-AUV), a forecast path correction model is proposed in this paper. Four types of points, which are mainly treated as model computational objects, are defined for abstracting the specific tropical cyclone (TC) tracking process. Necessary methodologies and a simplified model are harnessed and applied to Multi-AUV, facilitating the determination of points essential for solving the computations of the model. A correction algorithm is designed, serving as a guide for the tracking trajectory of Multi-AUV while concurrently ameliorating the errors inherent in conventional TC forecast data generation. The algorithm is proved to be effective. Finally, a simulation process is constructed to verify the effectiveness of the model, and the results conform well to the theory. This model furnishes a comprehensive blueprint for the realization of unmanned real-time observation of TCs.

Mapping clinical interactions in an Australian tertiary hospital emergency department for patients presenting with risk of suicide or self-harm: Network modeling from observational data.

Reliable assessment of suicide and self-harm risk in emergency medicine is critical for effective intervention and treatment of patients affected by mental health disorders. Teams of clinicians face the challenge of rapidly integrating medical history, wide-ranging psychosocial factors, and real-time patient observations to inform diagnosis, treatment, and referral decisions. Patient outcomes therefore depend on the reliable flow of information through networks of clinical staff and information systems. This study aimed to develop a quantitative data-driven research framework for the analysis of information flow in emergency healthcare settings to evaluate clinical practice and operational models for emergency psychiatric care. We deployed 2 observers in a tertiary hospital emergency department during 2018 for a total of 118.5 h to record clinical interactions along patient trajectories for presentations with risk of self-harm or suicide (n = 272 interactions for n = 43 patient trajectories). The study population was reflective of a naturalistic sample of patients presenting to a tertiary emergency department in a metropolitan Australian city. Using the observational data, we constructed a clinical interaction network to model the flow of clinical information at a systems level. Community detection via modularity maximization revealed communities in the network closely aligned with the underlying clinical team structure. The Psychiatric Liaison Nurse (PLN) was identified as the most important agent in the network as quantified by node degree, closeness centrality, and betweenness centrality. Betweenness centrality of the PLN was significantly higher than expected by chance (>95th percentile compared with randomly shuffled networks) and removing the PLN from the network reduced both the global efficiency of the model and the closeness centrality of all doctors. This indicated a potential vulnerability in the system that could negatively impact patient care if the function of the PLN was compromised. We developed an algorithmic strategy to mitigate this risk by targeted strengthening of links between clinical teams using greedy cumulative addition of network edges in the model. Finally, we identified specific interactions along patient trajectories which were most likely to precipitate a psychiatric referral using a machine learning model trained on features from dynamically constructed clinical interaction networks. The main limitation of this study is the use of nonclinical information only (i.e., modeling is based on timing of interactions and agents involved, but not the content or quantity of information transferred during interactions). This study demonstrates a data-driven research framework, new to the best of our knowledge, to assess and reinforce important information pathways that guide clinical decision processes and provide complementary insights for improving clinical practice and operational models in emergency medicine for patients at risk of suicide or self-harm. Our findings suggest that PLNs can play a crucial role in clinical communication, but overreliance on PLNs may pose risks to reliable information flow. Operational models that utilize PLNs may be made more robust to these risks by improving interdisciplinary communication between doctors. Our research framework could also be applied more broadly to investigate service delivery in different healthcare settings or for other medical specialties, patient groups, or demographics.

Precision agricultural technology for advanced monitoring of maize yield under different fertilization and irrigation regimes: A case study in Eastern Hungary (Debrecen)

Precision agricultural (PrA) technology relies on the utilization of special equipment to access real time observations on plant health status, chlorophyll, nitrogen content, and soil moisture content. In this research new PrA technology (i.e., SPAD (Soil Plant Analysis Development), and UAV-based NDVI (Unmanned Aerial Vehicle-based Normalized Difference Vegetation Index) were used to monitor maize yield based on different filed trials in eastern part of Hungary. Our study aimed to examine the utilization of PrA technology specifically SPAD and UAV-based NDVI measurements for monitoring maize GY under irrigated and rainfed experimental setups in Hungary with varied nitrogen treatment for the year 2022. The results showed that the SPAD increased in all treatments (14.7 %; p < 0.05) from V6–V8 in the rainfed treatments, decreased significantly (p < 0.05) by 13.9 % (R1) and 30.6 % (R3). However, implementation of irrigation significantly increased the SPAD values in majority of treatments. Also, results reveal that, under irrigated and rainfed conditions the highest UAV-based NDVI value (0.703, 0.642) was obtained in V12 (A120 treatment) and highest NDVI value (0.728, 0.662) was obtained in Vn (A120 treatment). Remarekedly, irrigation led to significant differences (p < 0.05) of UAV-based NDVI values compared with none irrigated. On the other hand, implementation of 120 kg N ha−1 before sowing led to highest GY, especially under irrigated conditions (8.649 Mg ha−1). The overall mean GY under rainfed treatment was 6.256 Mg ha−1, while under irrigated treatment it increased by 37.2 % and reached 8.581 Mg ha−1 (p < 0.05). In conclusion, PrA technology will support farmers in making informed decisions regarding fertilization strategies and timing, which will in turn maximize yield and minimize risk.

An actively stabilized, miniaturized epi-fluorescence widefield microscope for real-time observation in vivo.

Recent developments in real-time, in vivo micro-imaging have allowed for the visualization of tissue pathological changes, facilitating rapid diagnosis. However, miniaturization, magnification, the field of view, and in vivo image stabilization remain challenging factors to reconcile. A key issue for this technology is ensuring it is user friendly for surgeons, enabling them to use the device manually and obtain instantaneous information necessary for surgical decision-making. This descriptive study introduces a handheld, actively stabilized, miniaturized epi-fluorescence widefield microscope (MEW-M) for real-time observation in vivo with high resolution. The methodology of MEW-M system includes high resolution microscopy miniaturization technology, thousandfold shaking suppression (actively stabilized), ultra-photosensitivity, and tailored image signal processing cell image capture and processing technology, which support for the excellent real-time imaging performance of MEW-M system in brain, mammary, liver, lung, and kidney tissue imaging of rats in vivo. With a single-objective and high-frame-rate imaging, the MEW-M system facilitates roving image acquisition, enabling contiguous analysis of large tissue areas. RESEARCH HIGHLIGHTS: A handheld, actively stabilized MEW-M system was introduced. Excellent real-time, in vivo imaging with high resolution and active stabilization in brain, mammary, liver, lung, and kidney tissue of rats.

Automatic tracking and intelligent observation of tidal bore propagation velocity based on UAV and computer vision

The rapidly developed Unmanned Aerial Vehicles (UAV) and artificial intelligence technology has prompted the real-time and accurate observation measurements of tidal bore, the basis of which is tidal bore propagation velocity. In this article, we construct a tidal observation system framework based on UAV and computer vision in order to obtain the tidal bore propagating velocity datasets. Firstly, we focus on the identification of tidal headlines based on the Sobel edge detection, the improved Otsu image segmentation algorithm and the edge connection algorithm with an accuracy of 91%. And then, the detected tidal headlines could be used to control the flight parameters of UAV in order to stably track tidal bore on the specified route with the deviation range below 0.5, and finally to acquire the tidal bore propagation velocity datasets. Comparing with the propagation velocity of the tidal line measured on site, the error of the results is maintained within 0.1 m/s, which demonstrates the effectiveness of our proposed observation method.

Integrating advanced approaches for climate change impact assessment on water resources in arid regions

This research addresses the growing complexity and urgency of climate change’s impact on water resources in arid regions. It combines advanced climate modelling, machine learning, and hydrological modelling to gain profound insights into temperature variations and precipitation patterns and their impacts on the runoff. Notably, it predicts a continuous rise in both maximum and minimum air temperatures until 2050, with minimum temperatures increasing more rapidly. It highlights a concerning trend of decreasing basin precipitation. Sophisticated hydrological models factor in land use, vegetation, and groundwater, offering nuanced insights into water availability, which signifies a detailed and comprehensive understanding of factors impacting water availability. This includes considerations of spatial variability, temporal dynamics, land use effects, vegetation dynamics, groundwater interactions, and the influence of climate change. The research integrates data from advanced climate models, machine learning, and real-time observations, and refers to continuously updated data from various sources, including weather stations, satellites, ground-based sensors, climate monitoring networks, and stream gauges, for accurate basin discharge simulations (Nash–Sutcliffe efficiency – NSE RCP2.6 = 0.99, root mean square error – RMSE RCP2.6 = 1.1, and coefficient of determination R 2 RCP2:6= 0.95 of representative concentration pathways 2.6 (RCP)). By uniting these approaches, the study offers valuable insights for policymakers, water resource managers, and local communities to adapt to and manage water resources in arid regions.

Operando Nanomechanical Mapping of Amorphous Silicon Thin Film Electrodes in All-Solid-State Lithium-Ion Battery Configuration during Electrochemical Lithiation and Delithiation.

An operando bimodal atomic force microscopy system was constructed to perform nanomechanical mapping of an amorphous Si thin film electrode deposited on a Li6.6La3Zr1.6Ta0.4O12 solid electrolyte sheet during electrochemical lithiation/delithiation. The evolution of Young's modulus maps of the Si electrode was successfully tracked as a function of apparent Li content x in lithium silicide (LixSi) simultaneously with real-time surface topography observation. At the initial stage of lithiation, the average modulus steeply decreased due to the generation of LixSi from intrinsic Si, followed by a moderate modulus reduction until the electrode capacity reached 3300 mAh g-1 (Li content x = 3.46). In the following delithiation, the gradual recovery of the average modulus of LixSi was observed up to 1467 mAh g-1 (Li content x = 1.54) at which delithiation stopped due to the significant volume change induced by phase transformation of LixSi.

Fine Particle Migration in a Gas Hydrate Sand: Single- and Two-Phase Fluid Using a Device for Observation at the Pore Scale

The production of natural gas hydrates will change the cementation strength, porosity, and effective stress in the stratum, which may lead to engineering and geological disasters. Sand production is a phenomenon where sand particles are carried out of the reservoir along with fluids during gas extraction, posing challenges to safe and sustainable production. This study explored the mechanism of fine particle migration in multiphase flow by a microscopic visualization test device. The device can inject a gas–liquid–solid phase at the same time and allow real-time observation. Experimental tests on fine particle migration of single- and two-phase fluid flow were carried out considering different conditions, i.e., fine particle concentration, fine particle size, fluid flow rate, and gas–liquid ratio. The results show that in single-phase fluid flow, the original gas will gradually dissolve in the liquid phase, and finally stay in the test device as bubbles, which can change the pore structures, resulting in the accumulation of fine particles at the gas–liquid interface. In two-phase fluid flow with mixed gas–water fluids, there are two flow modes of gas–liquid flow: mixed flow and separated flow. The interfacial tension at the gas–liquid interface can effectively migrate fine particles when the gas–liquid flows alternately and the sand production rate further increases as the gas–liquid ratio increases. In addition, changes in the concentration of fine particles, particle size, fluid flow rate, and the gas–liquid ratio will affect the migration of fine particles, leading to differences in the final sand production.

Exploring the in vivo anti-cancer potential of Neosetophomone B in leukemic cells using a zebrafish xenograft model

Neosetophomone B (NSP–B) is a unique meroterpenoid fungal secondary metabolite that has previously demonstrated promising anti-cancer properties against various cancer cell lines in vitro. However, its in vivo anti-cancer potential remaines unexplored. To fill this gap in our knowledge, we tested NSP-B's in vivo anti-cancer activity using a zebrafish model, an organism that has gained significant traction in biomedical research due to its genetic similarities with humans and its transparent nature, allowing real-time tumor growth observation. For our experiments, we employed the K562-injected zebrafish xenograft model. Upon treating these zebrafish with NSP-B, we observed a marked reduction in the size and number of tumor xenografts. Delving deeper, our analyses indicated that NSP-B curtailed tumor growth and proliferation of leukemic grafted xenograft within the zebrafish. These results show that NSP-B possesses potent in vivo anti-cancer properties, making it a potential novel therapeutic agent for addressing hematological malignancies.

Realistic tropical cyclone wind and pressure fields can be reconstructed from sparse data using deep learning

Tropical cyclones are responsible for large-scale loss of life and property1–4, motivating accurate risk assessment and forecasting. These objectives require accurate reconstructions of storms’ wind and pressure fields which assimilate real-time observations5–9, but current methods used for these reconstructions remain computationally expensive and limited10. Here, we show that a physics-informed neural network11,12 can be a promising and computationally efficient algorithm for tropical cyclone data assimilation. Using synthetic training data sparsely sampled from hurricanes simulated in a forecast model, a physics-informed neural network is able to reconstruct full realistic 2- and 3-dimensional wind and pressure fields which capture key features of the cyclone. We also demonstrate how a set of sparse, real-time observations, can be used to accurately reconstruct Hurricane Ida. Our results highlight how recent advances in deep learning can augment data assimilation schemes. The methods are also general and can be applied to other flow problems.

Uncovering Phenotypes in Mutant Mice by Determining Embryo, Organ, Tissue, and Cell Developmental Potential.

The death of an embryo during gestation does not necessarily preclude the study of the mutant embryo or the developmental potential of its individual cells, tissues, or organs. Whole-embryo in vitro culture prior to the time of death will allow real-time observation of living embryos and direct comparisons with controls. Organ anlage can be removed from embryos and cultured in vitro beyond the time of death of the whole embryo. In both whole embryos and organ anlage culture, fluorescent protein reporters may be used productively to follow cell types or specific gene expression changes. Some cells, such as hematopoietic cells, and organ anlage, may be suitable for transplantation to wild-type hosts for further analysis of their potential. Additionally, cell lines, including embryonic stem (ES) cells, trophoblast stem (TS) cells, extraembryonic endoderm (XEN) stem cells, and epiblast-derived stem cells (EpiSC), can be derived from mutant embryos to reveal the potential of the mutant cells outside the context of the whole organism. Mutant stem cells or even whole mutant embryos can be used to test potential in chimeras or in teratomas.

Observing bioorthogonal macrocyclizations in the nuclear envelope of live cells using on/on fluorescence lifetime microscopy.

The reactive partnership between azides and strained alkynes is at the forefront of bioorthogonal reactions, with their in situ cellular studies often achieved through the use of off to on fluorophores with fluorescence microscopy. In this work, the first demonstration of a bioorthogonal, macrocycle-forming reaction occurring within the nuclear envelope of live cells has been accomplished, utilising on/on fluorescence lifetime imaging microscopy for real-time continuous observation of the transformation. The fluorescent, macrocyclic BF2 azadipyrromethene was accessible through a double 1,3-dipolar cycloaddition within minutes, between a precursor bis-azido substituted fluorophore and Sondheimer diyne in water or organic solvents. Photophysical properties of both the starting bis-azide BF2 azadipyrromethene and the fluorescent macrocyclic products were obtained, with near identical emission wavelengths and intensities, but different lifetimes. In a novel approach, the progress of the live-cell bioorthogonal macrocyclization was successfully tracked through a fluorescence lifetime change of 0.6 ns from starting material to products, with reaction completion achieved within 45 min. The continuous monitoring and imaging of this bioorthogonal transformation in the nuclear membrane and invaginations, of two different cancer cell lines, has been demonstrated using a combination of fluorescence intensity and lifetime imaging with phasor plot analysis. As there is a discernible difference in fluorescence lifetimes between starting material and products, this approach removes the necessity for off-to-on fluorogenic probes when preparing for bioorthogonal cell-imaging and microscopy.

Мониторинг окислительно-восстановительного потенциала подземных вод в режиме реального времени на Култукском полигоне в конце 2023 – начале 2024 г.: сопоставление электрических эффектов с землетрясениями в центральной части Байкальской рифтовой системы

The results of real-time observations of the oxidation-reduction potential (ORP) in groundwater from two wells in the Kultuk area from December 2023 to March 2024 are presented. Variations of this parameter show reorganizations, accompanied by short episodes of single earthquakes and longer intervals of earthquake series in the central part of the Baikal Rift System. A change from low to high ORP values accompanies the general transition from strong to weak earthquakes. The uneven variations in ORP of the monitoring stations are suggested to associate with piezoelectric effects that arise when seismic waves act on quartz of the ordered tectonite structures in different active structures of the South Baikal basin: in its marginal Obruchev fault and in the axial Kultuk tectonic step.

Real-time observation of sub-100-fs charge and energy transfer processes in DNA dinucleotides.

Using as showcase the DNA dinucleotide 5'-dTpdG-3', in which the thymine (T) is located at the 5' end with respect to the guanine (G), we study the photoinduced electronic relaxation of coupled chromophores in solution with an unprecedented refinement. On the one hand, transient absorption spectra are recorded from 20 fs to 45 ps over the 330-650 nm range with a temporal resolution of 30 fs; on the other hand, quantum chemistry calculations determine the ground state geometry of the 4 possible conformers with stacked nucleobases, the associated Franck-Condon states, and map the relaxation pathways leading to excited state minima. Important spectral changes occurring before 100 fs are correlated with concomitant G+ → T- charge transfer and T → G energy transfer processes. The lifetime of the excited charge transfer state is only 5 ps and the absorption spectrum of a long-lived nπ*T state is detected. Our experimental results match the transient spectral properties computed for the anti-syn conformer of 5'-dTpdG-3', which is characterized by the lowest ground state energy and differs from that encountered in B-form duplexes.

Simultaneous fast XAS/SAXS measurements in an energy-dispersive mode.

X-ray absorption spectroscopy (XAS) and small-angle X-ray scattering (SAXS) are common materials characterization tools at synchrotron radiation facilities used in many research fields. Since XAS can provide element-specific chemical states and local atomic structures and SAXS can provide nano-scale structural information, their complementary use is advantageous for a comprehensive understanding of multiscale phenomena. This paper presents a new method for simultaneous XAS/SAXS measurements with synchrotron radiation. The method employs a polychromatic X-ray beam as in the energy-dispersive XAS technique and captures both the transmission XAS spectrum and the SAXS intensity distribution with an area X-ray detector, which eliminates the energy scan in the conventional methods and realizes the simultaneous data acquisition in a shorter time. We succeeded in obtaining the atomic and nano-scale structures of Pt and Pt/Pd nanoparticles with a data acquisition time of 0.1 s, suggesting the potential for real-time observation of multiscale phenomena.

Solution slot-die coating perovskite film crystalline growth observed by &lt;i&gt;in situ&lt;/i&gt; GIWAXS/GISAXS

Solution method is an important means of fabricating optoelectronic devices. During the thin film sample preparation, organic or inorganic perovskite semiconductor material usually needs to be finished in a glove box. However, most of the traditional experimental characterizations under the air environment, it is hard to reflect the reality of the structure and performance between film and device, therefore it is urgently needed to solve the microstructure evolutions of these semiconductor films based on &lt;i&gt;in situ&lt;/i&gt; real-time representation technique. In this work, we report a synchrotron-based grazing incidence wide and small-angle scattering (GIWAXS and GISAXS) &lt;i&gt;in situ&lt;/i&gt; real-time observation technique combined with a mini glove box, thereby realizing the standard glove box environment (H&lt;sub&gt;2&lt;/sub&gt;O, O&lt;sub&gt;2&lt;/sub&gt; content all reached below 1×10&lt;sup&gt;–6&lt;/sup&gt;) under remote control film spin coating or slot-die preparation and various sample post-processing. Meanwhile, this technique can real-time monitor the microstructure and morphology evolution of semiconductor film during fabrication. Based on the &lt;i&gt;in situ&lt;/i&gt; device and GIWAXS, SnO&lt;sub&gt;2&lt;/sub&gt; ETL interface induced perovskite growth crystallization process shows that CQDs additive can result in three-dimensional perovskite, with the random orientation growth changing into highly ordered vertical orientation, meanwhile can effectively restrain the low-dimensional perovskite domain formation, helping to reveal the film microstructure transformation of inner driving force and providing the perovskite device preparation process optimized with experimental and theoretical basis. The conversion efficiency of large-area fully flexible three-dimensional perovskite thin film solar cells prepared by the roll-to-roll total solution slit coating method is increased to 5.23% (the area of a single device is ~15 cm&lt;sup&gt;2&lt;/sup&gt;). Therefore, using the &lt;i&gt;in situ&lt;/i&gt; synchrotron-based glove box device, the microstructure evolution and the associated device preparation conditions of perovskite and organic semiconductor thin films can be controlled, and the thin film growth interface characteristics and film quality can be further controlled, which is the key technology to control the optimization process conditions of semiconductor thin films and devices.

Revealing of long-range soliton interaction induced time and phase dynamics in a mode-locked fiber laser.

By means of the dispersive temporal interferometry technique, we carried out a real-time observation of the time separation and relative phase evolutions of two pulses toward harmonic mode-locking. During the separation stage of the buildup process, the time separation increases, while the relative phase decreases synchronously, and the largest change rates are 0.247 fs/r and -0.017 rad/r, respectively. Meanwhile, the two rates show a linear relation with the former 17.4 times larger than the latter. Moreover, a residual phase change rate of -3.89 × 10-4 rad/r is observed in a steady non-uniform dual-soliton state, while such phase change is absent in a uniform four-soliton state. This study unveils the soliton interaction dynamics in lasers, which not only help to reduce timing jitter in multi-soliton mode-locking, but also bring insight to a temporal tweezing of femtosecond pulse.

Materials evaluation using cell-sized liposomes.

Cell membranes play a vital role in delineating the internal cellular environment from the external surroundings, going beyond mere compartmentalization. Researchers have delved into the structural organization, properties, and functional roles of biological membranes, paving the way for their application in substance identification, detection, and quantification. This review introduces various studies and their implications for future research. It underscores the advantages of employing cell-sized liposomes, which enable real-time observation for rapid detection and analysis of diverse materials. The utility of cell-sized liposomes extends to their size, dynamic shape changes, and phase-separation, offering valuable insights into the evaluation of targeted materials.

Revealing microscopic dynamics: in situ liquid-phase TEM for live observations of soft materials and quantitative analysis via deep learning.

In various domains spanning materials synthesis, chemical catalysis, life sciences, and energy materials, in situ transmission electron microscopy (TEM) methods exert a profound influence. These methodologies enable the real-time observation and manipulation of gas-phase and liquid-phase reactions at the nanoscale, facilitating the exploration of pivotal reaction mechanisms. Fundamental research areas like crystal nucleation, growth, etching, and self-assembly have greatly benefited from these techniques. Additionally, their applications extend across diverse fields such as catalysis, batteries, bioimaging, and drug delivery kinetics. However, the intricate nature of 'soft matter' presents a challenge due to the unique molecular properties and dynamic behavior of these substances that remain insufficiently understood. Investigating soft matter within in situ liquid-phase TEM settings demands further exploration and advancement compared to other research domains. This research harnesses the potential of in situ liquid-phase TEM technology while integrating deep learning methodologies to comprehensively analyze the quantitative aspects of soft matter dynamics. This study centers on diverse phenomena, encompassing surfactant molecule nucleation, block copolymer behavior, confinement-driven self-assembly, and drying processes. Furthermore, deep learning techniques are employed to precisely analyze Ostwald ripening and digestive ripening dynamics. The outcomes of this study not only deepen the understanding of soft matter at its fundamental level but also serve as a pivotal foundation for developing innovative functional materials and cutting-edge devices.

Imaging of Extravasation of Splenocytes in the Dorsal Skinfold Window Chamber.

Infiltration of immune cells into the tumor is one of the major drivers of antitumor immune response, which can direct the outcome of anticancer therapies. In mice, implantation of dorsal skinfold window chamber (DSWC) combined with intravital confocal fluorescence microscopy allows real-time observation of splenocyte extravasation and infiltration into tumors. Here, we describe a detailed procedure of the DSWC implantation, splenocyte isolation and fluorescent labeling, intravenous injection of labeled splenocytes, and imaging of splenocyte extravasation into tumors using confocal fluorescence microscopy.