Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Trebon fishponds, Czech Republic.

Cyanobacteria blooms in fishponds, driven by climate change and anthropogenic activities, have become a critical concern for aquatic ecosystems worldwide. The diversity in fishpond sizes and fish densities further complicates their monitoring. This study addresses the challenge of accurately predicting cyanobacteria concentrations in turbid waters via remote sensing, hindered by optical complexities and diminished light signals. A comprehensive dataset of 740 sampling points was compiled, encompassing water quality metrics (cyanobacteria levels, total chlorophyll, turbidity, total cell count) and spectral data obtained through AlgaeTorch, alongside Sentinel-2 reflectance data from three Trebon fishponds (UNESCO Man and Biosphere Reserve) in the Czech Republic over 2022-2023. Partial Least Squares Regression (PLSR) and three machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), were developed based on seasonal and annual data volumes. The SVM algorithm demonstrated commendable performance on the one-year data validation dataset from the Svet fishpond for the prediction of cyanobacteria, reflected by the key performance indicators: R2 = 0.88, RMSE = 15.07 µg Chl-a/L, and RPD = 2.82. Meanwhile, SVM displayed steady results in the unified one-year validation dataset from Nadeje, Svet, and Vizír fishponds, with metrics showing R2 = 0.56, RMSE = 39.03 µg Chl-a/L, RPD = 1.50. Thus, Sentinel data proved viable for seasonal cyanobacteria monitoring across different fishponds. Overall, this study presents a novel approach for enhancing the precision of cyanobacteria predictions and long-term ecological monitoring in fishponds, contributing significantly to the water quality management strategies in the Trebon region.

An improved DIIS method using a versatile residual matrix to accelerate SCF starting from a crude guess.

The minimization of the commutator of the Fock and density matrices as the error matrix in the direct inversion of the iterative subspace (CDIIS) developed by Pulay is a powerful self-consistent field (SCF) acceleration technique for the construction of optimum Fock matrix, if initiated with a fair initial guess. In this work, we present an alternative minimized error matrix to the commutator in the CDIIS, namely the residual or the gradient of the energy-functional for a Slater determinant subject to the orthonormality constraints among orbitals, representing the search for a newly improved Fock matrix in the direction of the residual in the direct inversion of the iterative subspace (RDIIS). Implemented in the computational chemistry package GAMESS, the RDIIS is compared with the standard CDIIS and the second order SCF orbital optimization (SOSCF) for tested molecules started with a crude guess. As a result, the RDIIS stably and efficiently performs the SCF convergence acceleration. Furthermore, the RDIIS is considerably independent on the subspace size with the concentrated linear coefficients accounting proportionally for the Fock matrices close to the current iteration.

Dynamics of sensory and decisional biases in perceptual decision making: Insights from the face distortion illusion.

Bias in perceptual decision making can have both sensory and decisional origins. These distinct sources of bias are typically seen as static and stable over time. However, human behavior is dynamic and constantly adapting. Yet it remains unclear how sensory and decisional biases progress in distinct ways over time. We addressed this question by tracking the dynamics of sensory and decisional biases during a task that involves a visual illusion. Observers saw multiple pairs of peripherally presented faces that induce a strong illusion making the faces appear distorted and grotesque. The task was to judge whether one of the last two faces had true physical distortion (experimentally introduced in half of the trials). Initially, participants classified most faces as distorted as exemplified by a liberal response bias. However, over the course of the experiment, this response bias gradually disappeared even though the distortion illusion remained equally strong, as demonstrated by a separate subjective rating task without artificially distorted faces. The results suggest that the sensory bias was progressively countered by an opposite decisional bias. This transition was accompanied by an increase in reaction times and a decrease in confidence relative to a condition that does not induce the visual illusion. All results were replicated in a second experiment with inverted faces. These findings demonstrate that participants dynamically adjust their decisional bias to compensate for sensory biases, and that these two biases together determine how humans make perceptual decisions.

Enhancing fluid signal in driven-equilibrium short-TI inversion-recovery imaging with short TR times: A feasibility study.

PURPOSE: Fluid-sensitive turbo spin echo (TSE) MRI with short-TI inversion-recovery preparation for fat suppression (STIR) plays a critical role in the diagnostics of the musculoskeletal system (e.g., close to metal implants). Potential advantages of 3D acquisitions, however, are difficult to exploit due to long acquisition times. Shortening the TR incurs a signal loss, and a driven-equilibrium (DE) extension reduces fluid signal even further. METHODS: The phase of the flip-back pulse was changed by 180° relative to the conventional implementation (i.e., 90° along the positive x-axis (90°x) instead of -90°x). After signal modeling and numerical simulations, the modification was implemented in STIR-TSE sequences and tested on a clinical 3T system. Imaging was performed in the lumbar spine, and long-TR images without DE were acquired as reference. CSF SNR and fluid-muscle contrast were measured and compared between the sequences. Imaging was repeated in a metal implant phantom. RESULTS: A shortening of TR by 43%-57% reduced the CSF SNR by 39%-59%. A conventional DE module further reduced SNR to 26%-40%, whereas the modified DE recovered SNR to 59%-108% compared with the long-TR acquisitions. Fluid-tissue contrast was increased by about 340% with the modified DE module compared with the conventional extension. Similar results were obtained in implant measurements. CONCLUSIONS: The proposed DE element for TSE-STIR sequences has the potential to accelerate the acquisition of fluid-sensitive images. DE-STIR may work most efficiently for 3D acquisitions, in which no temporo-spatial interleaving of inversion and imaging pulses is possible.

A non-invasive AI-based system for precise grading of anosmia in COVID-19 using neuroimaging.

COVID-19 (Coronavirus), an acute respiratory disorder, is caused by SARS-CoV-2 (coronavirus severe acute respiratory syndrome). The high prevalence of COVID-19 infection has drawn attention to a frequent illness symptom: olfactory and gustatory dysfunction. The primary purpose of this manuscript is to create a Computer-Assisted Diagnostic (CAD) system to determine whether a COVID-19 patient has normal, mild, or severe anosmia. To achieve this goal, we used fluid-attenuated inversion recovery (FLAIR) Magnetic Resonance Imaging (FLAIR-MRI) and Diffusion Tensor Imaging (DTI) to extract the appearance, morphological, and diffusivity markers from the olfactory nerve. The proposed system begins with the identification of the olfactory nerve, which is performed by a skilled expert or radiologist. It then proceeds to carry out the subsequent primary steps: (i) extract appearance markers (i.e., 1 s t and 2 n d order markers), morphology/shape markers (i.e., spherical harmonics), and diffusivity markers (i.e., Fractional Anisotropy (FA) & Mean Diffusivity (MD)), (ii) apply markers fusion based on the integrated markers, and (iii) determine the decision and corresponding performance metrics based on the most-promising classifier. The current study is unusual in that it ensemble bags the learned and fine-tuned ML classifiers and diagnoses olfactory bulb (OB) anosmia using majority voting. In the 5-fold approach, it achieved an accuracy of 94.1%, a balanced accuracy (BAC) of 92.18%, precision of 91.6%, recall of 90.61%, specificity of 93.75%, F1 score of 89.82%, and Intersection over Union (IoU) of 82.62%. In the 10-fold approach, stacking continued to demonstrate impressive results with an accuracy of 94.43%, BAC of 93.0%, precision of 92.03%, recall of 91.39%, specificity of 94.61%, F1 score of 91.23%, and IoU of 84.56%. In the leave-one-subject-out (LOSO) approach, the model continues to exhibit notable outcomes, achieving an accuracy of 91.6%, BAC of 90.27%, precision of 88.55%, recall of 87.96%, specificity of 92.59%, F1 score of 87.94%, and IoU of 78.69%. These results indicate that stacking and majority voting are crucial components of the CAD system, contributing significantly to the overall performance improvements. The proposed technology can help doctors assess which patients need more intensive clinical care.

Association of Short-Term Increases in Ambient Fine Particulate Matter With Hospitalization for Asthma or COPD During Wildfire Season and Other Time Periods.

BACKGROUND: Short-term increases in air pollution are associated with poor asthma and COPD outcomes. Short-term elevations in fine particulate matter (PM2.5) due to wildfire smoke are becoming more common. RESEARCH QUESTION: Are short-term increases in PM2.5 and ozone in wildfire season and in winter inversion season associated with a composite of emergency or inpatient hospitalization for asthma and COPD? STUDY DESIGN AND METHODS: Case-crossover analyses evaluated 63,976 and 18,514 patients hospitalized for primary discharge diagnoses of asthma and COPD, respectively, between January 1999 and March 2022. Patients resided on Utah's Wasatch Front where PM2.5 and ozone were measured by Environmental Protection Agency-based monitors. ORs were calculated using Poisson regression adjusted for weather variables. RESULTS: Asthma risk increased on the same day that PM2.5 increased during wildfire season (OR, 1.057 per + 10 µg/m3; 95% CI, 1.019-1.097; P = .003) and winter inversions (OR, 1.023 per +10 µg/m3; 95% CI, 1.010-1.037; P = .0004). Risk decreased after 1 week, but during wildfire season risk rebounded at a 4-week lag (OR, 1.098 per +10 µg/m3; 95% CI, 1.033-1.167). Asthma risk for adults during wildfire season was highest in the first 3 days after PM2.5 increases, but for children, the highest risk was delayed by 3 to 4 weeks. PM2.5 exposure was weakly associated with COPD hospitalization. Ozone exposure was not associated with elevated risks. INTERPRETATION: In a large urban population, short-term increases in PM2.5 during wildfire season were associated with asthma hospitalization, and the effect sizes were greater than for PM2.5 during inversion season.

Cross-correlation adjustment full-waveform inversion with source encoding in ultrasound computed tomography.

Full-waveform inversion (FWI) is one of the leading-edge techniques in ultrasound computed tomography (USCT). FWI reconstructs the images of sound speed by iteratively minimizing the difference between the predicted and measured signals. The challenges of FWI are to improve its stability and reduce its computational cost. In this paper, a new USCT algorithm based on cross-correlation adjustment FWI with source encoding (CCAFWI-SE) is proposed. In this algorithm, the gradient is adjusted using the intermediate signals as the inversion target rather than the measured signals during iteration. The intermediate signals are generated using the travel time difference calculated by cross-correlation. In the case of conventional FWI failure, using the proposed algorithm, the estimated sound speed can converge toward the ground truth. To reduce the computational cost, an intermittent update strategy is implemented. This strategy only requires one time for the calculation of the travel time difference per stage, so that the source encoding can be used. Simulation and laboratory experiments are implemented to validate this approach. The experiment results show it has successfully recovered the sound speed model, while conventional FWI failed when the initial model greatly differed from the ground truth. This verifies that our approach improves the stability of the reconstruction in USCT. In practice, additional computational costs can be reduced by combining our approach with existing methods. The proposed approach increases the robustness of the FWI and expands its application.

Three-pressure prediction method of jointing well-seismic data in JT1 well area of Sichuan Basin in China.

With the high yield of many wells represented by Well JT1 in the Maokou Formation, has catalyzed a surge in exploration activities along the platform margin facies of the Maokou Formation in central Sichuan and further showed the significant exploration potential of the Maokou Formation in the northern slope. However, the fracture cave body of the Maokou Formation exhibits a high degree of development, strong longitudinal and horizontal heterogeneity, large formation pressure differences, and drilling events such as gas kicks and lost circulation occur frequently, which seriously affects the efficient implementation of drilling. Understanding the spatial distribution of the three-pressure in the formation can help better deal with and solve the above problems. Therefore, in order to help the safe, high-quality and rapid drilling of the Maokou Formation in the study area, and enhance the efficiency of oil and gas development, this paper explores the research on the prediction method of the three-pressure of jointing well-seismic data based on the geomechanical experimental data and the actual drilling data. In the process of prediction of pore pressure, this study found that the pore pressure and formation velocity in the study area have an exponential relationship. In order to enhance the applicability of the Filippone's method in the study area and improve the prediction accuracy of pore pressure, the linear relationship between pore pressure and formation velocity in the Filippone's method is modified to an exponential relationship, and a pore pressure prediction model suitable for the work area was established. Based on the Mohr-Coulomb criterion and Huang's model, the prediction models of collapse pressure and fracture pressure applicable to the study area were established, respectively. Then, the elastic parameters were obtained through pre-stack inversion, and the three-pressure bodies were calculated based on the elastic parameter bodies. The results indicate that: (1) The three-pressure prediction method of the jointing well-seismic data in this paper can predict the formation's longitudinal and transverse pressure anomaly zones in advance. (2) The Maokou Formation in the study area is characterized by abnormally high pressure, to balance the pressure of the high-ground formation, high-density drilling fluid is necessary. (3) The prediction results of three-pressure in this paper are highly consistent with the actual drilling engineering events, which verifies the reliability of the three-pressure prediction results presented in this study. The results of the study can provide a basis for decision-making in drilling geological design, such as the determination of drilling fluid density, the evaluation of borehole stability and other engineering problems that require support from three-pressure data.

The heterogeneity of holistic processing profiles in developmental prosopagnosia: holistic processing is impaired but not absent.

Although it is generally assumed that face recognition relies on holistic processing, whether face recognition deficits observed in Developmental Prosopagnosics (DPs) can be explained by impaired holistic processing is currently under debate. The mixed findings from past studies could be the consequence of DP's heterogeneous deficit nature and the use of different measures of holistic processing-the inversion, part-whole, and composite tasks-which showed a poor association among each other. The present study aimed to gain further insight into the role of holistic processing in DPs. Groups of DPs and neurotypicals completed three tests measuring holistic face processing and non-face objects (i.e., Navon task). At a group level, DPs showed (1) diminished, but not absent, inversion and part-whole effects, (2) comparable magnitudes of the composite face effect and (3) global precedence effect in the Navon task. However, single-case analyses showed that these holistic processing deficits in DPs are heterogeneous.

Constraining Earth's nonlinear mantle viscosity using plate-boundary resolving global inversions.

Variable viscosity in Earth's mantle exerts a fundamental control on mantle convection and plate tectonics, yet rigorously constraining the underlying parameters has remained a challenge. Inverse methods have not been sufficiently robust to handle the severe viscosity gradients and nonlinearities (arising from dislocation creep and plastic failure) while simultaneously resolving the megathrust and bending slabs globally. Using global plate motions as constraints, we overcome these challenges by combining a scalable nonlinear Stokes solver that resolves the key tectonic features with an adjoint-based Bayesian approach. Assuming plate cooling, variations in the thickness of continental lithosphere, slabs, and broad scale lower mantle structure as well as a constant grain size through the bulk of the upper mantle, a good fit to global plate motions is found with a nonlinear upper mantle stress exponent of 2.43 [Formula: see text] 0.25 (mean [Formula: see text] SD). A relatively low yield stress of 151 [Formula: see text] 19 MPa is required for slabs to bend during subduction and transmit a slab pull that generates asymmetrical subduction. The recovered long-term strength of megathrusts (plate interfaces) varies between different subduction zones, with South America having a larger strength and Vanuatu and Central America having lower values with important implications for the stresses driving megathrust earthquakes.

Aligning the domains in cross domain model inversion attack.

Model Inversion Attack reconstructs confidential training dataset from a target deep learning model. Most of the existing methods assume the adversary has an auxiliary dataset that has similar distribution with the private dataset. However, this assumption does not always hold in real-world scenarios. Since the private dataset is unknown, the domain divergence between the auxiliary dataset and the private dataset is inevitable. In this paper, we use Cross Domain Model Inversion Attack to represent the distribution divergence scenario in MIA. With the distribution divergence between the private images and auxiliary images, the distribution between the feature vectors of the private images and those of the auxiliary images is also different. Moreover, the outputted prediction vectors of the auxiliary images are also misclassified. The inversion attack is thus hard to be performed. We perform both the feature vector inversion task and prediction vector inversion task in this cross domain setting. For feature vector inversion, Domain Alignment MIA (DA-MIA) is proposed. While performing the reconstruction task, DA-MIA aligns the feature vectors of auxiliary images with the feature vectors of private images in an adversarial manner to mitigate the domain divergence between them. Thus, semantically meaningful images can be reconstructed. For prediction vector inversion, we further introduce an auxiliary classifier and propose Domain Alignment MIA with Auxiliary Classifier (DA-MIA-AC). The auxiliary classifier is pretrained by the auxiliary dataset and fine-tuned during the adversarial training stage. Thus, the misclassification problem caused by domain divergence can be solved, and the images can be reconstructed correctly. Various experiments are performed to show the advancement of our methods, the results show that DA-MIA can improve the SSIM score of the reconstructed images for up to 191%, DA-MIA-AC can increase the classification accuracy score of the reconstructed images from 9.18% to 81.32% in Cross Domain Model Inversion Attack.

Integrated geochemical and geophysical monitoring for the assessment of natural pollutant mitigation in heavy metal-contaminated areas of South Korea, Deagu.

The evaluation and monitoring of sites contaminated with heavy metals are essential for pollution remediation and prevention. In this study, we conducted geophysical and geochemical investigations at a site exhibiting heavy metal contamination downstream from an abandoned mine, with the aim of analyzing the extent of contamination and its temporal variation. We employed geophysical survey methods including electrical resistivity and induced polarization surveys of areas contaminated with heavy metals. Repeated surveys were conducted over time using the electrical resistivity method. Numerical simulations were employed to mitigate and eliminate electrical noise stemming from topography on the site. Additionally, time-lapse inversion was conducted on the resistivity data sets to analyze the changes in resistivity caused by variations in heavy metal contaminants. In the geochemical survey, soil samples were collected from the same locations as the geophysical survey, and chemical properties including pH, water content, electrical conductivity, and cation exchange capacity were analyzed. Our results showed that with the reduction of major sources of As and Zn contamination by 50%, the time-lapse electrical resistivity inversion results indicated that the resistivity of the subsurface materials increased by a factor of two. This paper demonstrated the natural reduction of the heavy metal contaminants at the site due to rainfall, aiming to comprehensively analyze the resultant alteration of both geochemical and geophysical properties.

3D Gravity and magnetic inversion modelling for geothermal assessment and temperature modelling in the central eastern desert and Red Sea, Egypt.

The Central Eastern Desert and Red Sea region have emerged as a significant area of interest for geothermal energy exploration, owing to their unique geological characteristics and active tectonic activity. This research aims to enhance our understanding of the region's geothermal potential through a comprehensive analysis of gravity and magnetic data. By utilizing a 3D gravity inversion model, a detailed examination of subsurface structures and density variations was conducted. Similarly, a 3D magnetic inversion model was employed to investigate subsurface magnetic properties. Integration result from the Pygimli library ensured robustness and accuracy in the inversion results. Furthermore, a temperature model was developed using the WINTERC-G model and inversion techniques, shedding light on the thermal structure and potential anomalies in the study area. The analysis of the Bouguer gravity map, 3D gravity inversion model, and magnetic data inversion yielded significant findings. The Red Sea exhibited higher gravity values compared to the onshore Eastern Desert, attributed to the presence of a thinner and denser oceanic crust as opposed to the less dense continental crust in the Eastern Desert. The 3D gravity inversion model revealed distinct variations in density, particularly high-density zones near the surface of the Red Sea, indicating underlying geological structures and processes. Conversely, density gradually decreased with depth along the onshore line, potentially influenced by a higher concentration of crustal fractures. The magnetic data inversion technique provided additional insights, highlighting areas with demagnetized materials, indicative of elevated temperatures. These findings were consistent with the correlation between high-density areas and low magnetic susceptibility values, reinforcing the proposition of increased heat transfer from the Red Sea. Comparative analysis of temperature profiles further confirmed the presence of elevated temperatures in promising zones, emphasizing the geothermal potential associated with heat transfer from the Red Sea.This research contributes to the understanding of the geothermal resources in the Central Eastern Desert and Red Sea region. The results from gravity and magnetic data inversions, combined with temperature profiles, provide valuable information for future geothermal exploration and utilization efforts. The findings underscore the importance of geothermal energy in achieving sustainability and contribute to the global discourse on renewable energy sources.

Mechanisms of lateral ankle ligament sprains in professional netball: A systematic video analysis.

OBJECTIVES: To undertake a systematic analysis of 17 medical attention and time-loss lateral ankle ligament sprain (LALS) events from televised Australian professional netball games during the 2020-2023 seasons. DESIGN: Case series. METHODS: Three analysts independently assessed the video footage and then convened to review and discuss each case until a consensus was reached. RESULTS: When in possession (7 cases) a player was commonly performing an agility-based manoeuvre to break free from an opponent and reposition themselves to be a passing option (5/7 cases). When out of possession (10 cases) a player was either attempting to intercept a pass (6 cases) or marking an opponent (4 cases). Players tended to land on the anterior one-third of the plantar surface of the foot - forefoot or shoe tip (7 cases). Players often landed on either the ground (7 cases) or the opponent's shoe then the ground (8 cases). In 9 cases the ankle-foot was considered to be in a neutral alignment in the frontal plane at landing. At the estimated index frame the players' weight tended to be all on the foot on the injured side (11 cases) or favouring the foot on the injured side (5 cases). Inversion and adduction was a common injury mechanism. Plantar-flexion was rarely involved. CONCLUSION: Landing on the anterior one-third of the plantar surface of the foot and subsequent weight transference onto the injured limb side was more important than ankle-foot inversion at initial ground contact. Exercises involving external perturbations that challenge the control of frontal and transverse plane ankle-foot motion and improve proprioception, neuromuscular control, and dynamic balance are warranted.

Objectively quantifying subjective phenomena: Measuring the flashed face distortion effect.

Objectively quantifying subjective phenomena like visual illusions is challenging. We address this issue in the context of the Flashed Face Distortion Effect (FFDE), where faces presented in succession appear distorted and grotesque. We first show that the traditional method of quantifying FFDE - via subjective ratings of the level of distortion - is subject to substantial biases. Motivated by this finding, we develop an objective method for quantifying FFDE by introducing two design innovations. First, we create artificially distorted faces and ask subjects to discriminate between undistorted and objectively distorted faces. Second, we employ both an illusion condition, which includes a succession of 15 face flashes, and a control condition, which includes a single face flash and does not induce an illusion. Using these innovations, we quantify the strength of the face distortion illusion by comparing the response bias for identifying distorted faces between the illusion and control conditions. We find that our method successfully quantifies the face distortion, with subjects exhibiting a more liberal response bias in the illusion condition. Finally, we apply our new method to evaluate how the face distortion illusion is modulated by face eccentricity, face inversion, the temporal frequency of the face flashes, and presence of temporal gaps between consecutive faces. Our results demonstrate the utility of our objective method in quantifying the subjective illusion of face distortion. Critically, the method is general and can be applied to other phenomena that are inherently subjective.

Evaluation of T2W FLAIR MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

BACKGROUND: Artificial intelligence (AI) reconstruction techniques have the potential to improve image quality and decrease imaging time. However, these techniques must be assessed for safe and effective use in clinical practice. OBJECTIVE: To assess image quality and diagnostic confidence of AI reconstruction in the pediatric brain on fluid-attenuated inversion recovery (FLAIR) imaging. MATERIALS AND METHODS: This prospective, institutional review board (IRB)-approved study enrolled 50 pediatric patients (median age=12 years, Q1=10 years, Q3=14 years) undergoing clinical brain MRI. T2-weighted (T2W) FLAIR images were reconstructed by both standard clinical and AI reconstruction algorithms (strong denoising). Images were independently rated by two neuroradiologists on a dedicated research picture archiving and communication system (PACS) to indicate whether AI increased, decreased, or had no effect on image quality compared to standard reconstruction. Quantitative analysis of signal intensities was also performed to calculate apparent signal to noise (aSNR) and apparent contrast to noise (aCNR) ratios. RESULTS: AI reconstruction was better than standard in 99% (reader 1, 49/50; reader 2, 50/50) for overall image quality, 99% (reader 1, 49/50; reader 2, 50/50) for subjective SNR, and 98% (reader 1, 49/50; reader 2, 49/50) for diagnostic preference. Quantitative analysis revealed significantly higher gray matter aSNR (30.6±6.5), white matter aSNR (21.4±5.6), and gray-white matter aCNR (7.1±1.6) in AI-reconstructed images compared to standard reconstruction (18±2.7, 14.2±2.8, 4.4±0.8, p<0.001) respectively. CONCLUSION: We conclude that AI reconstruction improved T2W FLAIR image quality in most patients when compared with standard reconstruction in pediatric patients.

Topology-Driven Coulomb Drag in van der Waals Heterostructure with Broken Inversion Symmetry.

As Coulomb drag near charge neutrality (CN) is driven by fluctuations or inhomogeneity in charge density, the topology should play an extremely important role. Interlinking Coulomb drag and topology could reveal how the system's nontrivial topology influences the electron-electron interactions at the quantum level. However, such an aspect is overlooked as most studies focus on symmetric drag systems without topology. To understand this topological aspect, we need to study Coulomb drag in an asymmetric system with a broken inversion symmetry and strong spin-orbit coupling (SOC). Here we experimentally demonstrate the energy-driven Coulomb drag in an asymmetric van der Waals heterostructure composed of black phosphorus and rhenium disulfide characterized by broken inversion symmetry. Temperature-dependent transport measurements near CN provide compelling evidence for the energy-driven Coulomb drag due to electron-hole coupling that is energetically favored in a broken-gap heterojunction, as confirmed by Hall coefficient sign reversal with temperature. Moreover, contrary to the symmetric devices, our results exhibit magnetic-field-free, i.e., topology-driven, Hall drag, revealing an intrinsic coupling between energy and charge modes. This is the manifestation of nonzero Berry curvature, akin to a magnetic field in momentum space, in a Rashba system, which arises from the SOC and broken inversion symmetry of the heterostructure.

Effect of endoscopic full-thickness resection assisted by distal serosal turnover with floss traction for gastric submucosal masses.

BACKGROUND: Complex and high-risk surgical complications pose pressing challenges in the clinical implementation and advancement of endoscopic full-thickness resection (EFTR). Successful perforation repair under endoscopy, thereby avoiding surgical intervention and postoperative complications such as peritonitis, are pivotal for effective EFTR. AIM: To investigate the effectiveness and safety of EFTR assisted by distal serosal inversion under floss traction in gastric submucosal tumors. METHODS: A retrospective analysis of patients with gastric and duodenal submucosal tumors treated with EFTR assisted by the distal serosa inversion under dental floss traction from January 2023 to January 2024 was conducted. The total operation time, tumor dissection time, wound closure time, intraoperative bleeding volume, length of hospital stay and incidence of complications were analyzed. RESULTS: There were 93 patients, aged 55.1 ± 12.1 years. Complete tumor resection was achieved in all cases, resulting in a 100% success rate. The average total operation time was 67.4 ± 27.0 min, with tumor dissection taking 43.6 ± 20.4 min. Wound closure times varied, with gastric body closure time of 24.5 ± 14.1 min and gastric fundus closure time of 16.6 ± 8.7 min, showing a significant difference (P < 0.05). Intraoperative blood loss was 2.3 ± 4.0 mL, and average length of hospital stay was 5.7 ± 1.9 d. There was no secondary perforation after suturing in all cases. The incidence of delayed bleeding was 2.2%, and the incidence of abdominal infection was 3.2%. No patient required other surgical intervention during and after the operation. CONCLUSION: Distal serosal inversion under dental-floss-assisted EFTR significantly reduced wound closure time and intraoperative blood loss, making it a viable approach for gastric submucosal tumors.

Structural Variants and Implicated Processes Associated with Familial Tourette Syndrome.

Gilles de la Tourette syndrome (GTS) is a neurodevelopmental psychiatric disorder with complex and elusive etiology with a significant role of genetic factors. The aim of this study was to identify structural variants that could be associated with familial GTS. The study group comprised 17 multiplex families with 80 patients. Structural variants were identified from whole-genome sequencing data and followed by co-segregation and bioinformatic analyses. The localization of these variants was used to select candidate genes and create gene sets, which were subsequently processed in gene ontology and pathway enrichment analysis. Seventy putative pathogenic variants shared among affected individuals within one family but not present in the control group were identified. Only four private or rare deletions were exonic in LDLRAD4, B2M, USH2A, and ZNF765 genes. Notably, the USH2A gene is involved in cochlear development and sensory perception of sound, a process that was associated previously with familial GTS. In addition, two rare variants and three not present in the control group were co-segregating with the disease in two families, and uncommon insertions in GOLM1 and DISC1 were co-segregating in three families each. Enrichment analysis showed that identified structural variants affected synaptic vesicle endocytosis, cell leading-edge organization, and signaling for neurite outgrowth. The results further support the involvement of the regulation of neurotransmission, neuronal migration, and sound-sensing in GTS.

Effect of Dielectric Constant on the Zeta Potential of Spherical Electric Double Layers.

Zeta potential refers to the electrokinetic potential present in colloidal systems, exerting significant influence on the diverse properties of nano-drug delivery systems. The impact of the dielectric constant on the zeta potential and charge inversion of highly charged colloidal particles immersed in a variety of solvents spanning from polar, such as water, to nonpolar solvents and in the presence of multivalent salts was investigated through primitive Monte Carlo (MC) model simulations. Zeta potential, ξ, is decreased with the decreasing dielectric constant of the solvent and upon further increase in the salinity and the valency of the salt. At elevated levels of salt, the colloidal particles become overcharged in all solvents. As a result, their apparent charge becomes opposite in sign to the stoichiometric charge. This reversal of charge intensifies until reaching a saturation point with further increase in salinity.