Real Diffusion Research Articles

Detecting novel psychoactive substances around the world.

The worldwide spread of novel psychoactive substances (NPS) in the illicit drug market and their continuous increase in number and type, for the purpose of bypassing controlled substance legislation, represents a continuing challenge for forensic scientists, clinicians and enforcement authorities. We aim to provide information regarding the most urgent harms related to NPS consumption in different world regions and the current state of the art for NPS analysis. Unfortunately, the identification of NPS in biological samples is controversial, especially when samples are limited, or the drug is promptly and extensively metabolized. This causes a lack of information on their real diffusion in different parts of the world and in different populations. New technologies and instrumental detection of NPS in alternative samples are offering comprehensive information about NPS use. The lack of detection and underreporting of NPS in biological samples makes it difficult to obtain complete qualitative and quantitative information about NPS prevalence. The most innovative strategies that have been proposed in the last 2 years to assist NPS analysis and possibly facilitate the understanding of the NPS diffusion around the world are presented.

Thermodynamic uncertainty relations in the presence of non-linear friction and memory

A new thermodynamic uncertainty relation (TUR) is derived for systems described by linearly coupled Langevin equations in the presence of non-linear frictional forces. In our scheme, the main variable represents the velocity of a particle, while the other coupled variables describe memory effects which may arise from strongly correlated degrees of freedom with several time-scales and, in general, are associated with thermal baths at different temperatures. The new TUR gives a lower bound for the mean-squared displacement of the position of the particle, including its asymptotic diffusion coefficient. This bound, in several examples worked out here, appears to be a good analytical estimate of the real diffusion coefficient. The new TUR can be also applied in the absence of any external force (with or without thermal equilibrium between the baths), a case which usually goes beyond the scope of original TURs. We show applications to non-linear frictional models with memory, such as the Coulomb and the Prandtl-Tomlinson models, usually representative of friction at the nano-scale and within atomic-force microscopy experiments.

Relationships between intravoxel incoherent motion parameters and expressions of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) in patients with cervical cancer

To determine the associations of intravoxel incoherent motion (IVIM) parameters with expression of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), and evaluate the performance of the combined model established based on IVIM and clinicopathological parameters in predicting PD-L1and PD-1 status of cervical cancer (CC) patients. Seventy-eight consecutive CC patients were enrolled prospectively and underwent magnetic resonance imaging (MRI) including IVIM. IVIM quantitative parameters were measured, compared, and correlated with PD-L1 and PD-1 expression. Independent factors related to PD-L1 and PD-1 positivity were identified and were used to establish the combined model. The combined model's diagnostic performance was evaluated using the receiver operating characteristic (ROC) analysis. The Shapley additive explanation (SHAP) algorithm was used to explain the contribution of each parameter in the combined model. The real diffusion coefficient (D) value was significantly lower in the PD-L1-positive group than in the PD-L1-negative group (0.64±0.12 versus 0.72±0.11, p=0.021). The PD-1-positive and PD-1-negative groups showed similar trends (0.63±0.13 versus 0.73±0.09, p=0.003). Parametrial invasion, lymph node status, pathological grade, FIGO (International Federation of Gynecology and Obstetrics) staging, and D values were independently associated with PD-L1 and PD-1expression. A combined model incorporating these parameters showed good discrimination with the sensitivity, specificity of 90.9%, 82.6% for PD-L1, and 93.5%, 72% for PD-1. According to the SHAP value, FIGO staging and pathological grade were the most influential features of the prediction model. IVIM parameters were found to correlate with PD-L1 and PD-1 expression. The combined model, incorporating parametrial invasion, lymph node status, pathological grade, FIGO staging, and D values, showed good discrimination in predicting PD-L1 and PD-1 status, providing the basis for CC immunotherapy.

Value of Multimodal Diffusion-weighted Imaging in Preoperative Evaluation of Ki-67 Expression in Endometrial Carcinoma.

To investigate the value of multimodal diffusion weighted imaging (DWI) in preoperative evaluation of Ki-67 expression of endometrial carcinoma (EC). Patients who had undergone pelvic DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) sequence MRI scan before surgery were retrospectively enrolled. Single index model, double index model, and DKI were used for post-processing of the DWI data, and the apparent diffusion coefficient (ADC), real diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), non-Gaussian mean diffusion kurtosis (MK), mean diffusion coefficient (MD) and anisotropy fraction (FA) were calculated and compared between the Ki-67 high (≥50%) and low (<50%) expression groups. Forty-two patients with a median age of 56 (range 37 - 75) years were enrolled, including 15 patients with a high Ki-67 (≥50%) expression and 27 with a low Ki-67 (<50%) expression. The MK (0.91 ± 0.12 vs. 0.76 ± 0.12) was significantly (P<0.05) higher while MD (0.99 ± 0.17 vs. 1.16 ± 0.22), D (0.55 ± 0.06 vs. 0.62 ± 0.08), and f (0.21 vs. 0.28) were significantly (P<0.05) lower in the high than in the low expression group. The combined model of MK, MD, D, and f-values had the largest area under the curve (AUC) value of 0.869 (95% CI: 0.764-0.974), sensitivity 0.733 and specificity 0.852, followed by the MK value with an AUC value 0.827 (95% CI: 0.700-0.954), sensitivity 0.733 and specificity 0.815. IVIM and DKI have certain diagnostic values for preoperative evaluation of the EC Ki-67 expression, and the combined model has the highest diagnostic efficiency.

Brownian dynamics of Dirac fermions in twisted bilayer graphene

Brownian dynamics of Dirac fermions in twisted bilayer graphene is investigated within the framework of semiclassical relativistic Langevin equations. We find that under the influence of orthogonal, commensurate ac drives in the periodic ratchet potential of a substrate, the charge carriers in the system exhibit pronounced random dynamics, tuned by the twist angle, making twisted bilayer graphene distinct from monolayer graphene. It is shown that as threshold twist angle matches the optimal angle, deterministic running states appear in the limit of weak thermal noise where the diffusion rate is enhanced significantly compared to bare thermal diffusion. Analysis of the real space trajectories and diffusion coefficient illustrates the significant role of thermal noise in the random motion of Dirac fermions. In addition, we find that the Brownian particle shows remarkable ratchet effect as a net current.

Opinion-aware information diffusion model based on multivariate marked Hawkes process

Currently, information diffusion on online platforms plays an important role in social governance. Opinions contained in information have a significant influence on information diffusion. However, both classic and extended diffusion models lack consideration of the influence of opinions. Therefore, in this study, we propose an opinion-aware information diffusion model based on the multivariate marked Hawkes process to simulate the information diffusion process with effect of opinions. In addition, to simulate this process more accurately, we consider various endogenous and exogenous stimuli apart from the opinion. Simulation results show that the diffusion trend prediction evaluation metrics of our model are 31.4% (on average) better than the contemporary models tested. Moreover, the effects of internal and external factors are found to be qualitatively similar to the real information diffusion process; hence, we gain useful inspiration for social network research and public opinion guidance.

Feasibility Study of 3D FACT and IVIM Sequences in the Evaluation of Female Osteoporosis

Background: The aim of this study is to search for the predictive value of 3D fat analysis and calculation technique (FACT) and intravoxel incoherent motion (IVIM) parameters in identifying osteoporosis in women. Methods: We enrolled 48 female subjects who underwent 3.0 T MRI, including 3D FACT and IVIM sequences. Bone mineral density (BMD) values and Fracture Risk Assessment (FRAX) scores were obtained. Proton density fat fraction (PDFF) in the bone marrow and the real diffusion (D) value of intervertebral discs were measured on 3D FACT and IVIM images, respectively. Accuracy and bias were assessed by linear regression analysis and Bland–Altman plots. Intraclass correlation coefficients were used to assess the measurements’ reproducibility. Spearman’s rank correlation was applied to explore the correlation. MRI-based parameters were tested for significant differences among the three groups using ANOVA analyses. A receiver operating characteristic (ROC) analysis was performed. Results: The PDFF of the vertebral body showed a negative correlation with BMD (R = −0.393, p = 0.005) and a positive correlation with the FRAX score (R = 0.706, p &lt; 0.001). The D value of intervertebral discs showed a positive correlation with BMD (R = 0.321, p = 0.024) and a negative correlation with the FRAX score (R = −0.334, p = 0.019). The area under the curve values from the ROC analysis showed that the 3D FACT and IVIM sequences could accurately differentiate between normal and osteoporosis (AUC = 0.88 using the PDFF; AUC = 0.77 using the D value). The PDFF value demonstrated a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 78.6%, 89.5%, 84.6%, and 85.0%, respectively, in its ability to predict osteoporosis. The D value had a sensitivity, specificity, PPV, and NPV of 63.16%, 92.9%, 65.0%, and 77.8%, respectively, for predicting osteoporosis. Conclusions: The 3D FACT- and IVIM-measured PDFF and D values are promising biomarkers in the assessment of bone quality and fracture risk.

Real Gas Effect and Bulk Diffusion Characteristics of Shale Mixed Gas Transport in Microscale Fractures.

Shale gas reservoirs are rich in microscale fractures. In this paper, the characteristics of gas percolation in microscale fractures are taken as the research object. By coupling the actual gas equation, the multi-component gas equation, and the bulk gas diffusion equation, analytical solutions of the comprehensive percolation equation are obtained. Through mathematical model research, the following conclusions are obtained: (a) after considering the slip flow of the solid surface, the mass flow rate of multi-component gas under different pressure conditions increases by about 20-10,000%. (b) Different from continuous flow and slip flow, the mass flow rate of bulk gas diffusion decreases with pressure increase. (c) The intersection pressure is 31 MPa. When the pressure increases from 0.5 MPa to the pressure at the intersection point, the mass flow rate of integrated flow increases with decrease of the methane content. (d) When the pressure continues to increase from the intersection point pressure, the mass flow rate of integrated flow decreases with decrease of the methane content.

High-Sensitivity Visualization of Ultrafast Carrier Diffusion by Wide-Field Holographic Microscopy

Ultrafast transient microscopy is a key tool to study the photophysical properties of materials in space and time, but current implementations are limited to ≈1-μm fields of view, offering no statistical information for heterogeneous samples. Recently, we demonstrated wide-field transient imaging based on multiplexed off-axis holography. Here, we perform ultrafast microscopy in parallel around a hundred diffraction-limited excitation spots over a ≈60-μm field of view, which not only automatically samples the photophysical heterogeneity of the sample over a large area but can also be used to obtain a 10-fold increase in signal-to-noise ratio by computing an average spot. We apply our microscope to study the carrier diffusion processes in methylammonium lead bromide perovskites. We observe strong diffusion due to the presence of hot carriers during the first picosecond and slower diffusion afterward. We also describe how many-body kinetics can be misleadingly interpreted as strong diffusion at high excitation densities, while at weak excitation, real diffusion is observed. Therefore, the vast increase in sensitivity offered by this technique benefits the study of carrier transport not only by reducing data acquisition times but also by enabling the measurement of the much smaller signals generated at low carrier densities.

Does perfect filtering really guarantee perfect phase correction for diffusion MRI data?

Owing to its merit of avoiding noise-floor, phase correction is recently used to reconstruct real-valued diffusion MRI data by employing an image filter to estimate the noise-free background phase. However, several studies report an unexpected signal-loss issue for their reconstruction results, with its causing reason still remaining unclear. Although phase correction has achieved promising results in mitigating the signal-loss issue via improving the employed image filter, we have observed counterintuitive results that an advanced filter generates severe artifacts in our previous work. Considering the potential issues with phase correction procedures, in this paper, we argue that even a perfect image filter is insufficient to produce perfect phase correction. To point out the reason why phase correction introduces signal-loss and address this issue, we first propose a complex polar coordinate system (CPCS) to analyze its procedures in detail; second, based on CPCS, we find that phase correction has not sufficiently utilized the background phase, and thus propose a quantitative criterion to fully exploit the background phase; eventually, we propose a phase calibration procedure to remedy current phase correction. Extensive experimental results, including those on synthetic and real diffusion MRI data, demonstrate that our proposed method significantly reduces signal-loss and also eliminates artifacts in FA maps, particularly with improved accuracy on FA.

Anti-Rumor Dissemination Model Based on Heat Influence and Evolution Game

Aiming at the problem that the existing rumor dissemination models only focus on the characteristics of rumor dissemination and ignore anti-rumor dissemination, an evolution game model, SDIR, based on heat influence is proposed in this paper. Firstly, in order to solve the problem that rumor and anti-rumor information of emergency events disseminate simultaneously in social networks, the model extracts the factors that affect information dissemination: user behavior characteristics, user closeness and heat influence of participating topics. Secondly, anti-rumor information and an evolutionary game mechanism are introduced into the traditional SIR model, binary information is introduced to analyze the anti-rumor dissemination model SDIR, and the four state transitions and dissemination processes of SDIR are discussed. Finally, the SDIR model is experimentally validated in different datasets and dissemination models. The experimental results show that the SDIR model is in line with the actual dissemination law, and it can be proved that high self-identification ability plays a certain role in suppressing rumors; the anti-rumor information effectively inhibits the spread of rumor information to a certain extent. Compared with other models, the SDIR model is closer to the real diffusion range in the dataset.

A Simple Elimination of the Thermal Convection Effect in NMR Diffusiometry Experiments.

Thermal convection is always present when the temperature of an NMR experiment is different from the ambient one. Most often, it falsifies the value of the diffusion coefficient determined by NMR diffusiometry using a PGSE NMR experiment. In spite of common belief, it acts not only at higher temperatures but also at temperatures lower than in the laboratory. Sodium alkyl-sulfate monomers and micelles in D2O solvent were used as model molecules measured at T = 319 K in order to show that thermal convection sometimes remains hidden in experiments. In this paper, we demonstrate that the increase in apparent diffusion coefficient with increasing diffusion time is a definite indicator of thermal convection. Extrapolation to zero diffusion time can also be used to obtain the real diffusion coefficient, likewise applying the less sensitive pulse sequences designed for flow compensation or the expensive hardware, e.g., sapphire or Shigemi NMR tubes, to decrease the temperature gradient. Further, we show experiments illustrating the effect of a long diffusion time in which the periodic changes of the echo intensity with gradient strength appear as predicted by theories.

The frequency of polidrug use in a driving population in Rome

&#x0D; In Italy the illicit substances routinely tested are cannabinoids, cocaine, opiates, amphetamines / methamphetamine, MDMA and similar but these substances are not the most use in our country. In particular, the consumption of ketamine represents an emerging problem. Ketamine is a anesthetic with hallucinogenic and dissociative effects and these are the ones sought for the voluptuary pur-pose, while the amnesic effect are exploited for drug facilitated sexual assault. Our study was car-ried out to assess the positivity for the illicit substances routinely tested and also for ketamine in a population of 182 patients arrived at the emergency room of the Hospital “San Camillo Forlanini” of Rome, for which have been required toxicological tests on the basis of Articles 186 and 187 of the New Highway Code.&#x0D; The choice of this kind of population allows to have an accurate and reliable epidemiological data about the real diffusion of voluptuary use of drugs. The study examines 182 samples subjected to routine toxicological investigations in the period be-tween October 2011 and August 2012. The Authors have researched the presence of ethanol, cannabinoids, cocaine, opiates, amphetamines and benzodiazepines with the use of “ADVIA Chemistry Systems ”, while the ketamine is tested by a single-phase tests on urine [Sure Screen Diagnostic (Di. Ra.Lab)] with a cut-off level of this method is 1000ng/ml. During this period we have considered 182 patients (males 78%, females 22%). The mean age was 34 years (standard deviation 13, minimum 15, maximum 80). Most of the admission were during the last days of the week (Thursday 17%, Friday 15%, Saturday 15% and Sunday 17%). With re-spect to the clinical needs of subjects admitted, 42% were admitted with a red code. Considering a single substance analysis, 46 subjects resulted positive to alcohol (25%), 38 to can-nabinoids (21%), 24 to opioids (13%), 20 to cocaine (11%), 19 to benzodiapezine (10%) and 7 to ketamine (4%). Among those who resulted positive to at least one substance (95, 52% of the sample) 55 subjects re-sulted positive to one substance (58%), 27 to two substances (28%) and 13 to three or more substances (13%). Poly-use was evaluated with an indicator previously proposed by Fabi et al in 2013. This resulted in a polydrug-use score equal to 2.93 (standard deviation 1.7, minimum 1.5, maximum 9.25).&#x0D;

Possible origin of the spatiotemporal evolution of the 2008 earthquake swarm in Northwest-Bohemia, Czech Republic

The phenomenon ‘earthquake swarm’ is well known from numerous locations on Earth but its mechanism and trigger process are still an enigma. The influence of fluids on fluid-driven seismicity is generally well accepted but the temporal behaviour and the migration of activated phases is still an open question. We attempt to answer these open questions by combining the results of research on induced-seismicity with new reliable analyses of full moment tensors (FMTs) of the swarm earthquakes of 2008 to 2018 in Northwest-Bohemia, Czech Republic by Vavryčuk et al. (2017, 2021). The FMTs reveal evidence of compressive fracturing as the prevailing focal mechanism during the swarms. Our proposed hypotheses considered these earthquakes as the origin of subsequent pore pressure pulses in the respective active swarm phase. The diffusion of these pore pressure pulses, which could trigger the nearby earthquakes as well as the successive swarm phase in the vicinity after a respective diffusion process in space and time, are the target of this studies. Missing information regarding the real diffusion distances are compiled by a strict statistical approach of a one-to-one analysis of the swarm earthquakes. The analyses suggest that parts of the swarm earthquakes could be triggered by pore pressure diffusion with an estimated diffusivity range of approximately D = 0.01 to 3.0 m2/s. In exceptional cases, which make about 5% of all cases, we have to consider also diffusivities up to 15 m2/s. Examples of hydraulic diffusivities observed in our region of interest confirm this range. Such a process can also be assumed during further swarms in the years 2011 to 2018 because of the continuous and predominant occurrence of compressive fracturing as a focal mechanism beside pure shear and tensile fracturing. Our results could explain for the first time the missing link regarding the temporal and spatial migration of the subsequent swarm phases in our studied region at Nový Kostel (Northwest-Bohemia, Czech Republic).

CTtrack: A CNN+Transformer-based framework for fiber orientation estimation & tractography

In recent years, multiple data-driven fiber orientation distribution function (fODF) estimation algorithms and automatic tractography pipelines have been proposed to address the limitations of traditional methods. However, these approaches lack precision and generalizability. To tackle these shortcomings, we introduce CTtrack, a CNN+Transformer-based pipeline to estimate fODFs and perform tractography. In this approach, a convolutional neural network (CNN) module is employed to project the resampled diffusion-weighted magnetic resonance imaging (DW-MRI) data to a lower dimension. Then, a transformer model estimates the fiber orientation distribution functions using the projected data within a local block around each voxel. The proposed model represents the extracted fODFs by spherical harmonics coefficients. The predicted fiber ODFs can be used for both deterministic and probabilistic tractography. Our pipeline was tested in terms of the precision and robustness in estimating fODFs and performing tractography using both simulated and real diffusion data. The Tractometer tool was employed to compare our method with the classical and data-driven tractography approaches. The qualitative and quantitative assessments illustrate the competitive performance of our framework compared to other available algorithms.

HeDAN: Heterogeneous diffusion attention network for popularity prediction of online content

Popularity prediction of online content over social media platforms is a valuable and challenging issue, the core of which lies in how to capture predictive factors from available data. However, existing studies either treat each cascade independently, which neglects the correlation among different cascades, or lack a comprehensive consideration of user behavioral proximity and preference with respect to different messages. Motivated by the above observation, this article proposes a graph neural network-based framework named HeDAN (heterogeneous diffusion attention network), which comprehensively considers various factors affecting information diffusion to provide more accurate prediction results. Specifically, we first construct a heterogeneous diffusion graph with two types of nodes (user and message) and three types of relations (friendship, interaction, and interest). Among them, friendship reflects the strength of social relationships between users, interaction reflects the behavioral proximity between users, and interest reflects user preference for information. Next, a graph neural network model with a hierarchical attention mechanism is proposed to learn from these relations. Specifically, at the node level, we utilize the graph attention network to learn the subgraph structure and generate the representations of users and messages under each specific relationship. At the semantic level, we distinguish the importance of different nodes in different relations via the multi-head self-attention mechanism and fuse them into the final prediction representation. Extensive experimental results on three real diffusion datasets show the superior performance of HeDAN over the state-of-the-art baselines.

Oral fluid analysis to monitor recent exposure to synthetic cannabinoids in a high‐risk subpopulation

Among novel psychoactive substances, synthetic cannabinoid receptor agonists (SCRA) seem to have the widest diffusion in the population with no limitation to any particular demographic group. Information on drug consumption relies mostly on anonymized surveys and less on clinical or analytical data; notwithstanding, the huge efforts constantly made to enroll subjects to gather epidemiological data. In the present study, we collected 66 oral fluid samples from volunteers in a drug rehabilitation center in 2019 and early 2020. A liquid chromatography-mass spectrometry method previously developed and validated by our Unit was applied to detect SCRA (n= 10) in oral fluid. Results proved the presence of synthetic cannabinoids at a positivity rate of almost 20%, with detection frequency HU211(5/13) > UR144/JWH122 (3/13) > JWH019/JWH081/AM2201 (1/13). Concentrations were in the range < LOQ -0.36 ng/ml. Synthetic cannabinoids consumption had not been declared by any volunteer. This study enabled for the unprecedent detection of synthetic cannabinoids use in the territory of Parma (Italy) in a high-risk subpopulation. The identified SCRA proved the persistence into the market of the "first-generation" JWH family into the Italian territory and the marketing of relatively new ones (AM-2201). Public health consequences represented by NPS consumption are still scarce; therefore, further studies are needed to understand the real diffusion in the population.

Korean Management, Corporate Culture, and Systems of Labour Control Between South Korea and North America

This paper is an attempt at synthesizing an empirical and a theoretical critique of the cultural model of industrial organization, by focussing on Korean industrial organization and industrial relations in Korea, and on a large Korean industrial organization that was based in Quebec. As a counter weight to the cultural argument, the paper shows that mechanisms established to socially integrate workers into the organization in Korea are weak, and that management has had to rely instead on authoritarianism and on the State to ensure worker compliance. The paper then presents and discusses the social organization of a Korean industrial transplant; while there was a managerial discourse of participation and diffusion of power, the gap between this discourse and the real diffusion of power was such that a sizable minority of employees did not comply with managerial objectives.

Robust estimation and variable selection for function‐on‐scalar regression

Function‐on‐scalar regression is commonly used to model the dynamic behaviour of a set of scalar predictors of interest on the functional response. In this article, we develop a robust variable selection procedure for function‐on‐scalar regression with a large number of scalar predictors based on exponential squared loss combined with the group smoothly clipped absolute deviation regularization method. The proposed procedure simultaneously selects relevant predictors and provides estimates for the functional coefficients, and achieves robustness and efficiency using tuning parameters selected by a data‐driven procedure. Under reasonable conditions, we establish the asymptotic properties of the proposed estimators, including estimation consistency and the oracle property. The finite‐sample performance of the proposed method is investigated with simulation studies. The proposed method is also demonstrated with a real diffusion tensor imaging data example.

Влияние циклической термической обработки на структуру слоистого композиционного материала из стали марок 08кп и 08Х18Н10

The article researches the effect of five cycles of heating to a temperature of 1000 °C and two cycles of heating to a temperature of 1100 °C on the structure of a layered composite material consisted of 100 alternating layers of 08kp and 08Kh18N10 steels (one layer thickness is ~22 μm). As a result of the nickel and chromium diffusion during thermocycling, the thickness of the layers changed and an interlayer with a structure different from the structure of neighboring layers was formed. Heating to 1100 °C also has led to a partial disarrangement of the layered material structure. It was found that the real diffusion path of alloying elements during heat treatment significantly exceeds the calculated one, and chromium atoms are redistributed between the layers of the material much more actively than nickel atoms.