Regions Of High Intensity Research Articles

Static and Dynamic Time Filtering Techniques for Hybrid RANS-LES Simulation of Non-Stationary Turbulent Flows

Abstract Unsteady turbulent wall bounded flows can include complex flow physics such as temporally varying mean pressure gradients, intermittent regions of high turbulence intensity, and interaction of different scales of motion. The present study investigates the performance of the dynamic hybrid RANS-LES (DHRL) modeling framework for non-stationary turbulent flows using two variants of an exponential temporal filter for calculating statistics of the resolved turbulent flow. The first adopts a static filter size (static exponential time filtering?SETF) based on the characteristic time scale of imposed mean flow unsteadiness. The second uses a dynamic filter size (dynamic exponential time filtering?DETF) to vary the filter size based on local statistics of the resolved turbulent flow. Both of the time-filtered variants and the baseline (stationary) form of DHRL are compared against an industry standard Reynolds Averaged Navier-Stokes (RANS) model, Monotonically Integrated Large Eddy Simulation (MILES), and a conventional hybrid RANS-LES (HRL) models. Model performance is evaluated based on comparison to previously documented Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) results. Simulations are performed for a fully developed flow in a channel with time-periodic driving pressure gradient. Results highlight the relative merits of each model type and indicate that the use of a time-filtering technique improves the accuracy of the DHRL model for non-stationary flow, and that a dynamic filter offers clear advantages over a static filter.

On the localisation of the high-intensity region of simultaneous space-time foci

On the localisation of the high-intensity region of simultaneous space-time foci

Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears.

Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification. Using a dataset of 1000 clinically diagnosed images, we applied feature extraction techniques, including histogram bins and texture analysis with the gray level co-occurrence matrix (GLCM), alongside support vector machines (SVMs), for image quality assessment. Leukocyte detection employed optimal thresholding segmentation utility (OTSU) thresholding, binary masking, and erosion, followed by the connected components algorithm. Parasite detection used high-intensity region selection and adaptive bounding boxes, followed by a custom convolutional neural network (CNN) for candidate identification. A second CNN classified parasites into trophozoites, schizonts, and gametocytes. The system achieved an F1-score of 95% for image quality evaluation, 88.92% for leukocyte detection, and 82.10% for parasite detection. The F1-score-a metric balancing precision (correctly identified positives) and recall (correctly detected instances out of actual positives)-is especially valuable for assessing models on imbalanced datasets. In parasite stage classification, CNN achieved F1-scores of 85% for trophozoites, 88% for schizonts, and 83% for gametocytes. This study introduces a robust and scalable automated system that addresses critical challenges in malaria diagnosis by integrating advanced image quality assessment and deep learning techniques for parasite detection and classification. This system's adaptability to low-resource settings underscores its potential to improve malaria diagnostics globally.

Deep learning driven silicon wafer defect segmentation and classification.

Integrated Circuits are made of various transistors that are embedded on a silicon wafer, these wafers are difficult to process and hence are prone to defects. Defecting these defects manually is a time consuming and labour-intensive task and hence automation is necessary. Deep Learning approach is better suited in this case as it is able to generalize defects if trained properly and can be a solution to segmentation and classification of defects automatically. The segmentation model mentioned in this study achieved a Mean Absolute Error (MAE) of 0.0036, a Root Mean Squared Error (RMSE) of 0.0576, a Dice Index (DSC) of 0.7731, and an Intersection over Union (IoU) of 0.6590. The classification model achieved 0.9705 Accuracy, 0.9678 Precision, 0.9705 Recall, and 0.9676 F1 Score. In order to make this process a more interactive, an LLM with Q&A capabilities was integrated to solve any doubts and answer any questions regarding defects in wafers. This approach helps automate the detection process thus improving quality of end product.•Successful and precise defect segmentation and classification using Deep Learning was achieved.•High-intensity regions after post-processing.•An LLM offering defect analysis and guidance was streamlined.

Mechanistic insights into waterjet-guided laser grooving of silicon: Impact of ablation dynamics, oxide formation, and thermal stress

Waterjet-guided laser machining of silicon offers precision with minimal heat-affected zones (HAZs), but understanding the mechanisms behind laser-material interactions remains essential. This study first utilizes orthogonal experiments to reveal fundamental relationships between processing parameters (scanning cycle, laser fluence, scanning velocity, and waterjet pressure) on groove depth and the depth-to-HAZ ratio. These findings guide the in-depth investigation of laser-material mechanisms. The results indicate that the ablation rate decreases with increasing scanning cycles, a phenomenon primarily attributed to the different absorption rates of 532 nm laser light between silicon and silicon dioxide. This conclusion is supported by x-ray photoelectron spectroscopy(XPS) results, which reveal that the accumulation of silicon dioxide occurs as the scanning cycles increase. Additionally, a near-linear relation between the ablation rate and laser fluence is observed, as the ablated area is continuously exposed to high laser intensity regions. However, increasing laser fluence also leads to diminished processing quality due to greater thermal deformation in non-ablating regions. Last, increased scanning velocity is found to cause rougher surfaces, as insufficient heat diffusion leads to higher thermal stress and results in micro-crack formations. The results provide a detailed understanding of the laser-induced transformations in the material and highlight optimal conditions for reducing thermal damage while maintaining machining efficiency. This study advances the field of laser processing by offering insights into the mechanisms governing oxide formation, thermal cracking, and material deformation during silicon grooving, providing the foundation for future exploration of laser-material interaction dynamics.

Seismic performance of continuous rigid-frame bridges affected by flood-induced scour

River-crossing bridges in high-intensity seismic regions can be vulnerable to the combined action of earthquake and flood hazards; in particular, flood-induced scour of the substructure can have a notable influence on the seismic behavior of bridge structures. Currently, long-span continuous rigid-frame bridges are widely used to cross large rivers worldwide, yet related studies on their seismic performance under flood-induced scour have been lacking. This paper focuses on the effects of time-varying flood-induced scour on the seismic performance of long-span continuous rigid-frame bridges incorporating complex thin-walled reinforced concrete piers with pile group foundations. A detailed finite element (FE) model for a representative bridge structure is developed and the scour depth risk of the bridge is evaluated under several flood events for different return periods. The influence of flood-induced scour on the pile-soil interaction is examined throughout the bridge service life. Detailed seismic fragility assessment is carried out through nonlinear time-history analyses using a large suite of 100 seismic records. Particular focus is given to evaluate the time-varying scour effects on the pile and soil deformations as well as on the component and system level seismic fragility functions. It is shown that the total flood-induced scour depth exhibits a nonlinear increasing trend with the increase in service time, particularly in the initial 10 years of the bridge service life. The deformations of the scoured piles, within a depth of 20 m, are also shown to increase significantly with the increase in service time. The results indicate that the scour has a pronounced effect on both the component and system level seismic fragility functions. Importantly, although the piles (or pile groups) are typically designed to remain elastic under seismic loading, they are shown to be subjected to significant inelastic demands and governing damage levels as a result of time-varying flood-induced scour effect. Overall, this study provides a methodology to assess the time-varying seismic fragility of the scoured long-span rigid-frame bridges with complex thin-walled reinforced concrete piers, which can enhance the multi-hazard time-varying seismic resilience assessment for bridge structures with similar configurations.

Radar Echo Extrapolation Based on Translator Coding and Decoding Conditional Generation Adversarial Network

In response to the shortcomings of current spatiotemporal prediction models, which frequently encounter difficulties in temporal feature extraction and the forecasting of medium to high echo intensity regions over extended sequences, this study presents a novel model for radar echo extrapolation that combines a translator encoder-decoder architecture with a spatiotemporal dual-discriminator conditional generative adversarial network (STD-TranslatorNet). Initially, an image reconstruction network is established as the generator, employing a combination of a temporal attention unit (TAU) and an encoder–decoder framework. Within this architecture, both intra-frame static attention and inter-frame dynamic attention mechanisms are utilized to derive attention weights across image channels, thereby effectively capturing the temporal evolution of time series images. This approach enhances the network’s capacity to comprehend local spatial features alongside global temporal dynamics. The encoder–decoder configuration further bolsters the network’s proficiency in feature extraction through image reconstruction. Subsequently, the spatiotemporal dual discriminator is crafted to encapsulate both temporal correlations and spatial attributes within the generated image sequences. This design serves to effectively steer the generator’s output, thereby augmenting the realism of the produced images. Lastly, a composite multi-loss function is proposed to enhance the network’s capability to model intricate spatiotemporal evolving radar echo data, facilitating a more comprehensive assessment of the quality of the generated images, which in turn fortifies the network’s robustness. Experimental findings derived from the standard radar echo dataset (SRAD) reveal that the proposed radar echo extrapolation technique exhibits superior performance, with average critical success index (CSI) and probability of detection (POD) metrics per frame increasing by 6.9% and 7.6%, respectively, in comparison to prior methodologies.

Monolithic gold saturated on nanoporous gold@mirror template for highly reliable and fast surface-enhanced Raman scattering detection

The primary challenge hindering the broad application of surface-enhanced Raman scattering (SERS) is the variability in substrate performance due to site differences, leading to unstable detection results. Thus, the current work reports the constant potential deposition of gold (Au) nanostructure on a hybrid nanoporous gold (npAu)-Au mirror template to generate highly stable monolithic Au-saturated npAu@Au-mirror substrate. By systematically adjusting electrochemical variables, different sizes, shapes, and nanogaps of Au nanostructure are generated with high-intensity electromagnetic field regions (hot junctions) for enhanced SERS response. The resulting reproducible and enhanced SERS response of the Au-saturated npAu@Au-mirror mainly originates from i) the precise control of potential and accumulation time (−0.3 V and t = 100 s) to generate uniform and symmetric particle size, dispersion, and nanogaps formation through the reduction, nucleation, and growth of Au nanoparticles; ii) free selective dealloying and complete immersion of Au50Ag50 to ensure identical conditions across the alloy surface. The metrics for substrate efficiency were evaluated for reproducibility (n = 100, RSD = 14.22%), signal stability (storage time 25 days and variation in batches and multiple synthesis runs) and enhancements (enhancement factor∼1.3 × 107). The substrate was extended for the rapid and direct malachite green detection in fish samples with a detection limit of 1.7 × 10−9 mol L−1 and good recoveries (96.69 ± 2.18%∼98.51 ± 0.63%). The monolithic Au-saturated npAu@Au-mirror substrate might be implemented for routine analysis of other target types in food safety-related applications.

Awake Surgery for Right Frontal Lobe Glioma: Preserving Emotional Recognition and Facilitating Early Return to Work.

Many glioma patients struggle to return to work after surgery because of higher brain dysfunction. Although the right frontal lobe has historically been considered functionally silent, reports of performing awake surgery to evaluate higher brain functions in patients with tumors in this area have increased. We present two cases of patients who underwent awake surgery for malignant glioma in the right frontal lobe to preserve emotional recognition and facilitate an early return to work. Case 1 was a 48-year-old right-handed woman employed as a nursery school teacher and case 2 was a 21-year-old right-handed man employed in sales. Both had contrast-enhancing right frontal lobe tumors exhibiting high signal intensity on fluid attenuated inversion recovery imaging and underwent awake surgery. During the operation, cortical mapping was performed using the Reading the Mind in the Eyes, calculation, and motor tasks. Resection of sites involved in motor and emotional recognition functions was avoided. In case 1, all regions of high signal intensity were completely resected; in case 2, all regions exhibiting enhancement were resected. Both patients were discharged home without neurological deficits and returned to work within 21 days after surgery. It may be important to focus not only on overall survival and progression-free survival in glioma patients, but also on factors associated with life satisfaction, such as time to return to work after surgery and time until work becomes difficult. Awake surgery aimed at preserving higher brain functions is useful and may also improve life satisfaction.

Effects of Colliding Laser Pulses Polarization on e^{-}e^{+} Cascade Development in Extreme Focusing.

The onset and development of electron-positron cascade in a standing wave formed by multiple colliding laser pulses requires tight focusing in order to achieve the maximum laser intensity. There, steep spatiotemporal gradients in the laser intensity expel seed particles from the high-intensity region and thus can prevent the onset of a cascade. We show that radially polarized laser pulses ensure that the seed electrons are present at the focal plane at the moment of the highest amplitude even in the case of extreme focusing. This feature reduces the required laser power for the onset of a cascade 100 times (80 times) compared to circularly (linearly) polarized laser pulses having the same focal spot radius and duration.

Comprehensive Zoning Strategies for Flood Disasters in China

The frequency of global floods has increased, posing significant threats to economic development and human safety. Existing flood risk zoning studies in disaster prevention lack integration of the natural–economic–social chain and urban resilience factors. This study addresses this gap by constructing flood disaster risk and intensity indices using data from 31 provinces and 295 prefectural-level cities in China from 2011 to 2022. These indices incorporate natural (rainfall), economic (GDP), and social (population, built-up area) indicators to assess the flood likelihood and loss degree, providing comprehensive risk and intensity ratings. The study also examines the impact of resilience factors—environmental (green space), infrastructural (rainwater pipeline density), and natural resource (watershed areas)—on flood intensity. Findings reveal that high-risk regions are mainly in the Yangtze River Basin and southern regions, while high-intensity regions are primarily in the middle and lower Yangtze River and certain northwestern cities. Increasing rainwater pipeline density mitigates flood impacts in high-risk, high-intensity areas, while expanding green spaces and pipelines are effective in high-risk, low-intensity regions. This paper proposes a comprehensive flood hazard zoning mechanism integrating natural, economic, and social factors with urban resilience, offering insights and a scientific basis for urban flood management.

A Study on the Motion Behavior of Metallic Contaminant Particles in Transformer Insulation Oil under Multiphysical Fields.

When using transformer insulation oil as a liquid dielectric, the oil is easily polluted by the solid particles generated in the operation of the transformer, and these metallic impurity particles have a significant impact on the insulation performance inside the power transformer. The force of the metal particles suspended in the flow insulation oil is multidimensional, which will lead to a change in the movement characteristics of the metal particles. Based on this, this study explored the motion rules of suspended metallic impurity particles in mobile insulating oil in different electric field environments and the influencing factors. A multiphysical field model of the solid-liquid two-phase flow of single-particle metallic impurity particles in mobile insulating oil was constructed using the dynamic analysis method, and the particles' motion characteristics in the oil in different electric field environments were simulated. The motion characteristics of metallic impurity particles under conditions of different particle sizes, oil flow velocities, and insulation oil qualities and influencing factors were analyzed to provide theoretical support for the detection of impurity particles in transformer insulation oil and enable accurate estimations of the location of equipment faults. Our results show that there are obvious differences in the trajectory of metallic impurity particles under different electric field distributions. The particles will move towards the region of high field intensity under an electric field, and the metallic impurity particles will not collide with the electrode under an AC field. When the electric field intensity and particle size increase, the trajectory of the metallic impurity particles between electrodes becomes denser, and the number of collisions between particles and electrodes and the motion speed both increase. Under the condition of a higher oil flow velocity, the number of collisions between metal particles and electrodes is reduced, which reduces the possibility of particle agglomeration. When the temperature of the insulation oil changes and the quality deteriorates, its dynamic viscosity changes. With a decrease in the dynamic viscosity of the insulation oil, the movement of the metallic impurity particles between the electrodes becomes denser, the collision times between the particles and electrodes increase, and the maximum motion speed of the particles increases.

Experimental study on seismic performance of prestressed concrete solid square piles

Prestressed concrete solid square (PCSS) piles exhibit superior lateral bearing capacity and durability compared to pretensioned spun concrete pipe piles, and are more suitable for pile foundation engineering in high-intensity seismic regions and corrosive environments. There is still a lack of research on the seismic performances of the pile body of PCSS piles. This paper presents an experimental study and the associated theoretical and finite element (FE) analyses on the seismic performance of PCSS piles. Three full-scale PCSS pile specimens were tested under lateral cyclic loads with various axial force ratios, and the results are analyzed. Following the tests, a theoretical calculation method is proposed for the bearing capacity of PCSS piles. A FE model for PCSS pile specimens is established and validated against the test observations. Based on this model, a parametric analysis is then conducted. The results show that the PCSS pile specimens all exhibit typical flexural failure. Under a low axial force ratio, the failure mode of PCSS pile specimen is governed by the tensile rupture of prestressing tendons. Under a high axial force ratio, the failure is influenced by the crushing of cover concrete, while the concrete in the core zone remains intact, and there is no outward buckling of prestressing tendons and no rupture of stirrups. Increasing the prestressing tendon ratio can simultaneously improve the bearing and deformation capacity under a lower axial force. Under higher axial force ratios, however, increasing the prestressing tendon ratio or concrete strength can improve the bearing capacity but lead to a decline in deformation capacity. Compared to pretensioned spun high-strength concrete (PHC) piles, PCSS piles exhibit better seismic behavior on aspects of deformation capacity and ductility.

Insights into Afikpo Synclinorium structures: Subsurface analysis and intrusion outlining from airborne magnetic data

The airborne magnetic data over Afikpo Synclinorium were used to highlight subsurface structures and establish the orientations of tectonic features and their influence on the hydrocarbon play of the area. The characteristic trends of the lineaments were achieved through the center for exploration targeting of grid data analysis. The results of the TMI, residual magnetic field, first vertical, horizontal derivative, Analytic signal, and Tilt angle derivative classified the area into regions of high magnetic intensity observed around the northeastern, southwestern, and central portions of the study area. These areas characterized by anomalous signatures of short magnetic wavelengths delineate shallow magnetic sources. Conversely, regions with medium to low magnetic intensities are characterized by long magnetic wavelengths which indicates deep-seated magnetic source(s) and prospect for hydrocarbon (if other play concepts are emplace); due the thick sediment cover at the southern portion of the area (around, southern part of Nguzu, Ohafia, Biakpan, Abriba and Bende areas). The sediment thickness decreases towards north, west, North-east and north-west (dominated by Benue Trough deposit). Depth to the anomaly sources is of two categories, namely, shallow <1.0 km (dominated by NE trending structures) and deep ≥2.5 km. Ground-truthing confirmed the anomalous zone of high magnetic sources in the northeastern and central regions as Tertiary related tectonic-magmatic intrusion. The most prominent intrusion cuts across Amangwu Edda in Afikpo South through Amaeta-Oziza to Cross River State in a fissure form. This intrusion occurrence conformed to the high magnetic signature identified as a dolerite sill within the Afikpo Sub-basin. It stretches over 16 km in length with an average width of about 1.2 km, having its widest part in the northern parts of Mata Hospital Afikpo. The subsurface topographic model indicated that no fewer than 50% of the study area is characterized by sporadically distributed intrusive rocks. The result revealed several structural lineaments with high lineament density at the northcentral corner of the area trending NE-SW with fault lines (slip fault) perpendicular to it, offsetting the Akpoha, Ibii, Amasiri. and Ozara-ukwu ridges. The major drainage systems across the area followed major structural trends perpendicular to the identified major lineaments, passing through the major regional structural displacement pattern of the Basin. The emplacement of these intrusions might have impacted the hydrocarbon potential of the basin.

Precipitation nowcasting method based on Spatial-Temporal Dual Discriminators

Abstract The prediction of radar echo sequence images is a spatiotemporal sequence forecasting problem, which is one of the main challenges in precipitation nowcasting. Addressing issues such as poor extraction of spatiotemporal features by previous models and blurry image sequence predictions, this study proposes a Spatial-Temporal dual Discriminator Precipitation Nowcasting Model (STD-SNGAN) based on spectral normalization generative adversarial networks (SNGAN). The model utilizes multi-scale convolution modules (Inception) to extract spatial features from radar echo images and convolutional gated recurrent units (ConvGRU) to extract temporal features between feature maps. By introducing a hidden feature sampler to enhance the extraction capability of the convolutional gated recurrent units and designing spatial-temporal dual discriminators to constrain the generator’s predicted samples, the spatiotemporal forecasting ability is enhanced. Experimental results demonstrate that the proposed STD-SNGAN model outperforms other algorithms in critical success index (CSI) and probability of detection (POD) for high echo intensity and long-term regions.

Phosphoglyceride crystal deposition with suspected malignant ovarian tumor: a case report and literature review.

Phosphoglyceride crystal deposition disease is a rare condition occurring in soft tissues, resulting in scarring and affecting the bones, making preoperative differentiation from malignant tumors challenging. Here, we describe a case of phosphoglyceride crystal deposition disease initially suspected to be a malignant ovarian tumor before surgery. A 50-year-old woman with a history of three cesarean sections presented with lower abdominal pain. Transvaginal ultrasonography revealed a 54 × 58mm tumor in the lower right abdomen. Pelvic contrast-enhanced magnetic resonance imaging showed a thickened cystic wall with diffusion restriction, a low signal intensity region on T1-weighted images, and a slightly high signal intensity region on T2-weighted images. The tumor markers, cancer antigen 125 and carbohydrate antigen 19-9 levels, were within normal ranges; however, positron emitting tomography-computed tomography revealed fluorodeoxyglucose accumulation (SUVmax 31.28) in the tumor wall. Suspecting a malignant ovarian tumor, a laparoscopy was performed to observe the abdominal cavity. A 10cm white solid tumor was identified in the midline of the lower abdominal wall, leading to an open surgery recommendation. The tumor, adhering to the pubic bone, was excised. The tumor measured 9 × 7cm, with the cut surface showing a yellow brownish solid periphery and central region with liquefied degeneration. Histologically, radial basophilic deposits, dense infiltration of macrophages, multinucleated giant cells, and foam-like tissue spheres were observed. The central region exhibited cholesterol clefts, fibrin exudation, and necrosis, leading to a diagnosis of phosphoglyceride crystal deposition disease. This disease is rare, occurring in patients with atypical fluorodeoxyglucose accumulation on positron emission tomography-computed tomography or with a history of tissue damage, such as abdominal surgery.

Green signalling under environmental pressure: Does local government environmental regulatory pressure promote corporate environmental information disclosure?

Corporate environmental information disclosure (EID) is an important green signal. While prior literature well documents that the leading officials’ accountability audit of natural resources assets (AANRA) can effectively enhance the environmental regulatory pressure of local governments, little is known about whether this pressure can promote corporate EID. Utilizing panel data of 2,073 Chinese industrial listed enterprises from 2008–2021, we employ a staggered difference-in-difference-in-differences approach and identify the causal effect of AANRA on corporate EID. The results show that the EID quality of heavily polluting enterprises in AANRA cities increases by 3.28 % after the implementation of AANRA, and this effect persists. Meanwhile, AANRA does not trigger selective disclosure of enterprises, and its improvement of negative EID is more effective. Our mechanism analysis suggests that AANRA improves corporate EID through environmental incentive effect, environmental, social and governance (ESG) engagement effect and cost constraint effect. Moreover, the effect of AANRA varies with firms, industries, and regions, and it is more pronounced in non-state-owned firms, small firms, growing and mature firms, highly competitive firms, high-tech firms, and firms located in the eastern region, high audit intensity region and better institutional region. Our findings highlight the role of government environmental regulatory pressure in corporate EID, providing new insights into green transformation for enterprises in developing countries like China.

Light Reflections Detection And Correction For Robotic Volumetric PIV

Laser light reflection mitigation in Particle Image Velocimetry (PIV) is crucial for accurate flow field measurements. While numerous methods exist for planar PIV, fewer have been developed for volumetric PIV systems, and in particular for coaxial setups like robotic volumetric PIV. Light reflections in volumetric PIV experiments result in high-intensity regions that corrupt particle detection and analysis. This study presents a novel approach for treating light reflections in robotic volumetric PIV experiments. The proposed method uses image filtering and masking techniques in the wavenumber space to separate particle images from reflection regions. The process involves decomposing the image signal into low- and high-wavenumber components using the 2D discrete Fourier transform (DFT) to then use a high-pass filter to attenuate the intensity of the reflection regions. Finally, a step of automated adaptive masking is applied to remove residual reflection areas that the filtering is not able to eliminate. The proposed approach is tested on experimental data obtained from experiments performed using robotic volumetric PIV on two different geometries: a side-view mirror and a rotating two-blade propeller. Comparison between raw and pre-processed images, as well as particle tracking results, is presented. The results from this data comparison show successful removal of reflection-induced artifacts in instantaneous images by using the spatial Fourier filter automated masking approach. The developed image pre-processing strategy effectively removes unsteady light reflection regions in robotic volumetric PIV images, preventing the appearance of spurious particle tracks and improving the accuracy of flow field measurements. The spatial gaps introduced by the masking procedure can be easily filled in via measurements from multiple directions, which are promptly achieved via the robotic volumetric PIV approach.

Optical properties of meso-tetra(sulphonatophenyl) porphyrins (TPPS 4) and their Fe 3+, Mn 3+, Zn 2+ complexes with different pH values studied using by picosecond pulse trains

Applying picosecond pulse trains propagating in meso-tetra(sulphonatophenyl) porphyrins and their Fe 3+, Mn 3+, Zn 2+ complexes, we studied the nonlinear dynamics at different pH values. The pulse train at wavelength 532nm is comprised of 20 subpulses with 70ps width and 13ns spacing. We simplified the energy structures of porphyrins and metalloporphyrins to five-level models. In solving coupled rate equations and two-dimensional paraxial field, we used Crank-Nicholson numerical method to do the calculations. The results revealed that in irregular metalloporphyrins with central paramagnetic ion Mn 3+ or Fe 3+, the central ion would act as electron acceptor, which leads to charge transfer of unpaired metal electron to the porphyrin ring π conjugated system, and strengthen the spin–orbit coupling of electronic systems and weaken the transition prohibition between electronic states in porphyrins. However regular metalloporphyrins with central diamagnetic ion Zn 2+ has similar optical properties to free base porphyrins, and Zn 2+ TPPS 4 has much longer excited state lifetimes and slower intersystem crossing. In solutions, hydrogen bond would be formed to porphyrin, which can change the transitions of π electrons and thus the charge transfer can be strengthened in the porphyrin ring. In weak intensity region with linear absorption, nonprotonated porphyrins with high pH value show better optical limiting (OL) effect. Conversely in high intensity region, protonated porphyrins with low pH value show better OL effect. Besides, increasing interaction distances of porphyrins and metalloporphyrins with laser pulses is another important factor to raise the OL effects.

Tourism's contribution to human development and the reduction of poverty and inequality: Empirical evidence at a regional level in Spain

AbstractScientific literature has begun to analyze the capacity of tourism as a development instrument, although until now, it has relied on a country level focus. This innovative work analyzes the relationship between tourism and development at a regional level, establishing the hypothesis that tourism affects different dimensions of development (human development, poverty, and income inequality) and, furthermore, that differences exist at a regional level within the same country. Regional data from Spain are used for the 2004–2021 period, applying the Dumitrescu and Hurlin causality test to analyze the relationships between these variables in global terms while also disaggregating between touristic and non‐touristic regions. The results only verify that tourism has a positive effect on improving human development in regions of high tourism intensity. These results suggest the need for tourism policies that are linked to the regional administrative level.