AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy.

Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

Strategies to Effectively Utilize Images in Anatomical Teaching and Assessment.

Anatomical images are commonly used in the teaching process to help students understand the spatial orientation of anatomical structures. Previous research has shown that images effectively visualize the relationship between anatomical structures that are difficult to comprehend through verbal or written explanations alone. However, there is a lack of guidelines that specifically address the various methods of utilizing anatomical images and delivering them through multimedia and cognitive load principles. This article aims to provide a concise overview of the proper utilization and delivery of anatomical images and how these images can facilitate student interaction.

Particle Dynamics in a Diblock-Copolymer-Based Dodecagonal Quasicrystal and Its Periodic Approximant by X-Ray Photon Correlation Spectroscopy.

Temperature-dependent x-ray photon correlation spectroscopy (XPCS) measurements are reported for a binary diblock-copolymer blend that self-assembles into an aperiodic dodecagonal quasicrystal and a periodic Frank-Kasper σ phase approximant. The measured structural relaxation times are Bragg scattering wavevector independent and are 5 times faster in the dodecagonal quasicrystal than the σ phase, with minimal temperature dependence. The underlying dynamical relaxations are ascribed to differences in particle motion at the grain boundaries within each of these tetrahedrally close-packed assemblies. These results identify unprecedented particle dynamics measurements of tetrahedrally coordinated micellar block polymers, thus expanding the application of XPCS to ordered soft materials.

Bridging length scales in organic mixed ionic-electronic conductors through internal strain and mesoscale dynamics.

Understanding the structural and dynamic properties of disordered systems at the mesoscale is crucial. This is particularly important in organic mixed ionic-electronic conductors (OMIECs), which undergo significant and complex structural changes when operated in an electrolyte. In this study, we investigate the mesoscale strain, reversibility and dynamics of a model OMIEC material under external electrochemical potential using operando X-ray photon correlation spectroscopy. Our results reveal that strain and structural hysteresis depend on the sample's cycling history, establishing a comprehensive kinetic sequence bridging the macroscopic and microscopic behaviours of OMIECs. Furthermore, we uncover the equilibrium and non-equilibrium dynamics of charge carriers and material-doping states, highlighting the unexpected coupling between charge carrier dynamics and mesoscale order. These findings advance our understanding of the structure-dynamics-function relationships in OMIECs, opening pathways for designing and engineering materials with improved performance and functionality in non-equilibrium states during device operation.

Kratom (Mitragyna speciosa) use in a sample of drug-dependent adolescents in rehabilitation for drug use in Malaysia.

BACKGROUND: Leaves derived from the Kratom (Mitragyna speciosa) tree have been traditionally ingested for their curative properties by diverse groups of the population including people who use drugs (PWUDs) in Southeast Asia. This study investigated the motives for using kratom among drug-dependent adolescents. METHODS: Eighty adolescents who were undergoing mandatory drug rehabilitation volunteered to participate in this mixed-method, cross-sectional study. All respondents answered a semi-structured questionnaire while a few were interviewed in-depth. RESULTS: The majority were males (70%, n = 56/80). The respondents' mean age at admission was 18.2 years (SD = 1.40), and 65% were between 14 and 18 years old. Sixty-three percent (n = 50/80) had used crystal methamphetamine alone, while the rest had co-used crystal methamphetamine with heroin. About three-fifths (60%, n = 48/80) had a history of kratom use. Kratom was commonly used for many perceived benefits such as increasing energy, reducing crystal methamphetamine intake, intensifying euphoria, easing heroin withdrawal, as a heroin substitute and reducing heroin use. In addition, the multivariate analysis indicated that higher odds of kratom use were associated with those who were employed, used only crystal methamphetamine, were recent drug users, and had no prior incarceration history. CONCLUSION: While kratom was being used for its multifold perceived benefits, it also functions as a means to self-treat withdrawal from illicit drug use among drug-dependent adolescents.

Kinetics of Shear-Induced Structural Ordering in Dense Colloids.

The macroscopic rheological response of a colloidal solution is highly correlated with the local microscopic structure, as revealed by an in situ Rheo-SAXS experiment with a high temporal resolution. Oscillatory shear can induce a strain-controlled ordering-to-disorder transition, resulting in a shear-thickening process that is different from the normal shear-thickening behavior that is driven by hydrodynamics and particle friction. We reveal that there is a complex time-dependent kinetics toward structural ordering under different applied strains. When the strain amplitude reaches a critical value that starts to induce disordering in the system, the pathway toward the dynamic equilibrium can also become highly non-monotonic. Within the same oscillatory cycle, there is a strong correlation of ordering with different phases of the oscillation, with the system oscillating between two dynamic metastable states.

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures.

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

Investigation of the yielding transition in concentrated colloidal systems via rheo-XPCS.

We probe the microstructural yielding dynamics of a concentrated colloidal system by performing creep/recovery tests with simultaneous collection of coherent scattering data via X-ray Photon Correlation Spectroscopy (XPCS). This combination of rheology and scattering allows for time-resolved observations of the microstructural dynamics as yielding occurs, which can be linked back to the applied rheological deformation to form structure-property relations. Under sufficiently small applied creep stresses, examination of the correlation in the flow direction reveals that the scattering response recorrelates with its predeformed state, indicating nearly complete microstructural recovery, and the dynamics of the system under these conditions slows considerably. Conversely, larger creep stresses increase the speed of the dynamics under both applied creep and recovery. The data show a strong connection between the microstructural dynamics and the acquisition of unrecoverable strain. By comparing this relationship to that predicted from homogeneous, affine shearing, we find that the yielding transition in concentrated colloidal systems is highly heterogeneous on the microstructural level.

Microscopic Origins of the Nonlinear Behavior of Particle-Filled Rubber Probed with Dynamic Strain XPCS.

The underlying microscopic response of filler networks in reinforced rubber to dynamic strain is not well understood due to the experimental difficulty of directly measuring filler network behavior in samples undergoing dynamic strain. This difficulty can be overcome with in situ X-ray photon correlation spectroscopy (XPCS) measurements. The contrast between the silica filler and the rubber matrix for X-ray scattering allows us to isolate the filler network behavior from the overall response of the rubber. This in situ XPCS technique probes the microscopic breakdown and reforming of the filler network structure, which are responsible for the nonlinear dependence of modulus on strain, known in the rubber science community as the Payne effect. These microscopic changes in the filler network structure have consequences for the macroscopic material performance, especially for the fuel efficiency of tire tread compounds. Here, we elucidate the behavior with in situ dynamic strain XPCS experiments on industrially relevant, vulcanized rubbers filled (13 vol %) with novel air-milled silica of ultrahigh-surface area (UHSA) (250 m2/g). The addition of a silane coupling agent to rubber containing this silica causes an unexpected and counterintuitive increase in the Payne effect and decrease in energy dissipation. For this rubber, we observe a nearly two-fold enhancement of the storage modulus and virtually equivalent loss tangent compared to a rubber containing a coupling agent and conventional silica. Interpretation of our in situ XPCS results simultaneously with interpretation of traditional dynamic mechanical analysis (DMA) strain sweep experiments reveals that the debonding or yielding of bridged bound rubber layers is key to understanding the behavior of rubber formulations containing the silane coupling agent and high-surface area silica. These results demonstrate that the combination of XPCS and DMA is a powerful method for unraveling the microscale filler response to strain which dictates the dynamic mechanical properties of reinforced soft matter composites. With this combination of techniques, we have elucidated the great promise of UHSA silica when used in concert with a silane coupling agent in filled rubber. Such composites simultaneously exhibit large moduli and low hysteresis under dynamic strain.

Deconstructing Differential Drug Coverage within a Malaysian Media Source.

Many researchers have noted that media coverage of drugs can be sensationalized and/or have questionable accuracy. Additionally, it has been alleged that the media often treats all drugs as harmful and can fail to differentiate between different types of drugs. Within this context, the researchers sought to deconstruct how media coverage was similar and/or different according to drug type within a national media outlet in Malaysia. Our sample comprised 487 news articles published over a two-year period. Articles were coded to reflect thematic differences in drug framing. We focus on five drugs widely used in Malaysia (amphetamines, opiates, cannabis, cocaine, and kratom) and assess the most frequent themes, crimes, and locations mentioned in reference to each drug. All drugs were primarily covered in a criminal justice context, and articles highlighted concern about the spread of these drugs and their abuse. Drug coverage varied, particularly in association with violent crimes, specific regions, and discussion of legality. We find evidence of both similarities and differences in how drugs were covered. Variation in coverage demonstrated that certain drugs were deemed a heightened threat, as well as reflected broader social/political processes shaping ongoing debates over treatment approaches and legality.

Gelation and Re-entrance in Mixtures of Soft Colloids and Linear Polymers of Equal Size.

Liquid mixtures composed of colloidal particles and much smaller non-adsorbing linear homopolymers can undergo a gelation transition due to polymer-mediated depletion forces. We now show that the addition of linear polymers to suspensions of soft colloids having the same hydrodynamic size yields a liquid-to-gel-to-re-entrant liquid transition. In particular, the dynamic state diagram of 1,4-polybutadiene star-linear polymer mixtures was determined with the help of linear viscoelastic and small-angle X-ray scattering experiments. While keeping the star polymers below their nominal overlap concentration, a gel was formed upon increasing the linear polymer content. Further addition of linear chains yielded a re-entrant liquid. This unexpected behavior was rationalized by the interplay of three possible phenomena: (i) depletion interactions, driven by the size disparity between the stars and the polymer length scale which is the mesh size of its entanglement network; (ii) colloidal deswelling due to the increased osmotic pressure exerted onto the stars; and (iii) a concomitant progressive suppression of the depletion efficiency on increasing the polymer concentration due to reduced mesh size, hence a smaller range of attraction. Our results unveil an exciting new way to tailor the flow of soft colloids and highlight a largely unexplored path to engineer soft colloidal mixtures.

The effect of dynamically heterogeneous interphases on the particle dynamics of polymer nanocomposites.

The entanglements of dynamically asymmetric polymer layers influence relaxations of nanoparticles in polymer nanocomposites. In this work, the dynamics of polymer-adsorbed and polymer-grafted nanoparticles in a poly(methyl acrylate) matrix polymer was investigated using X-ray photon correlation spectroscopy (XPCS) to understand the role of chain rigidity and chemical heterogeneities in particle dynamics. Locations of dynamic heterogeneities close to nanoparticles and away from particle surfaces were examined with the comparison of adsorbed and grafted nanoparticles. Our results show that the chemical heterogeneities around dispersed nanoparticles transitioned the particle dynamics from Brownian diffusion into hyperdiffusion, and moreover, the high rigidity of chains in the chemically heterogeneous interfacial layers slowed down the particle dynamics. The hyperdiffusion measured both in grafted particles and adsorbed particles was attributed to the dense interfacial mixing of dynamically heterogeneous chains.

An Open-Label Rater-Blinded Randomized Trial of Vilazodone versus Escitalopram in Major Depression.

Background: Vilazodone, a novel selective serotonin reuptake inhibitor and 5-HT1A partial agonist, was approved in 2011 for treatment for major depression. We aimed to compare the efficacy and safety of vilazodone versus escitalopram in patients with major depression at 4 weeks. Methods: Participants (n = 52) were adult major depressive disorder outpatients who were randomized to receive either oral escitalopram (modal endpoint dose 20 mg/day; n = 26) or oral vilazodone (modal endpoint dose 40 mg/day; n = 26). Rater-blinded assessments of depression scores (primary outcome) and clinical severity of illness (secondary outcome) were obtained at baseline, 2 weeks, and 4 weeks. Adverse effects such as weight gain, sexual dysfunction, and diarrhea were recorded at each visit. The primary analysis was performed on the Intention-to-treat sample. Results: No significant difference was noted between groups on depression scores at study endpoint (F = 2.80, df = 1,50, P = 0.10); however, the vilazodone group had significantly lower endpoint clinical severity of illness (F = 7.69, df = 1,50, P = 0.01). At 2 weeks, there were no significant between-group differences on depression scores (F = 0.006, df = 1,50, P = 0.94). Instances of diarrhea (P = 0.001) were significantly higher in the vilazodone group. Conclusion: Clinical ratings of major depression did not differ significantly between vilazodone and escitalopram groups at the end of 4 weeks. Our findings are limited by lack of statistical power to detect smaller differences between groups, should they exist.

Factors associated with drug use during pregnancy and breastfeeding among females who use drugs (FWUDs) in Malaysia.

Females who use drugs (FWUDs) are at risk of continuing illicit substance use during pregnancy and breastfeeding. We investigated the prevalence rates and factors associated with these practices in a sample of 200 FWUDs recruited from a publicly-run drug rehabilitation center. A semi-structured questionnaire was used to collect the data. The majority (86%) was Malay (n = 171/200), currently single (71%, n = 141/200), and 51% had nine years of education. The mean age of respondents was 32.2 years (SD = 8.61). Thirty-eight percent (n = 75/200) reported ever using illicit substances during pregnancy, while 15% (n = 30/200) had used them during breastfeeding. Higher odds of using drugs during pregnancy were associated with having an intimate male drug-using partner and with persons who reported abandoning an infant in the past. Lower odds were linked with women who used heroin with ATS (relative to those who used only ATS), and shorter-term ATS (≤3 years) relative to long term ATS users. At a lower level of significance (p = 0.054), being married also lowered the odds. Higher odds of drug use during breastfeeding were associated with having an intimate male drug-using partner, and previous methadone use history, while lower odds were associated with short-term ATS use and being employed. The findings highlight the need for timely and targeted interventions to inform, engage and promote the participation of FWUDs in pre- and post-natal care services.

Rheology and dynamics of a solvent segregation driven gel (SeedGel).

Bicontinuous structures promise applications in a broad range of research fields, such as energy storage, membrane science, and biomaterials. Kinetically arrested spinodal decomposition is found responsible for stabilizing such structures in different types of materials. A recently developed solvent segregation driven gel (SeedGel) is demonstrated to realize bicontinuous channels thermoreversibly with tunable domain sizes by trapping nanoparticles in a particle domain. As the mechanical properties of SeedGel are very important for its future applications, a model system is characterized by temperature-dependent rheology. The storage modulus shows excellent thermo-reproducibility and interesting temperature dependence with the maximum storage modulus observed at an intermediate temperature range (around 28 °C). SANS measurements are conducted at different temperatures to identify the macroscopic solvent phase separation during the gelation transition, and solvent exchange between solvent and particle domains that is responsible for this behavior. The long-time dynamics of the gel is further studied by X-ray Photon Correlation Spectroscopy (XPCS). The results indicate that particles in the particle domain are in a glassy state and their long-time dynamics are strongly correlated with the temperature dependence of the storage modulus.

Artificial Intelligence Revolutionizing the Field of Medical Education.

Medical education has ventured into a new arena of computer-assisted teaching powered by artificial intelligence (AI). In medical institutions, AI can serve as an intelligent tool facilitating the decision-making process effectively. AI can enhance teaching by assisting in developing new strategies for educators. Similarly, students also benefit from intelligent systems playing the role of competent teachers. Thus, AI-integrated medical education paves new opportunities for advanced teaching and learning experiences and improved outcomes. On the other hand, optical mark recognition and automated scoring are ways AI can also transform into a real-time assessor and evaluator in medical education. This review summarizes the AI tools and their application in medical teaching or learning, assessment, and administrative support. This article can aid medical institutes in planning and implementing AI according to the needs of the educators.

Student Experiential Activities: A Novel Strategy to Teach Neuroanatomy in Lectures.

Introduction Activity-based teaching is a widely used pedagogical tool for enhancing anatomy learning. However, involving the learner in experiential activities in lectures is an unexplored area in medical research. The present study aims to determine whether incorporating student experiential activities into lectures impacts student's learning of neuroanatomy. Materials and methods We used a pre-test/post-test experimental study design to compare the learning outcome between the experiential activity based lecture and traditional lectures. We divided 150 students into control (75 students) and intervention groups (75 students). To assess the baseline knowledge on the subject, the students attended 20 clinical scenario-based multiple-choice questions two weeks before the lectures. Then, both groups attended two lecture sessions on the functional areas of the brain. In the control group, the students drew the boundaries of a particular cerebral area and labeled its function and clinical symptoms. In the intervention group, the learners participated in experiential activities while following the instructions. The lecturer used their response as a scaffold to explain the function and clinical correlation of a specific part of the cerebral cortex. The same test questions were given to the students one week after the final lecture session to evaluate their level of understanding. We analyzed the scores of 111 students (57 students in the control group and 54 students in the interventional group) who attended the two lectures and pre- and post-test sessions. Students also completed a validated 10-item feedback questionnaire regarding their perception of the teaching sessions. Results The mean score improvement for the control and intervention groups was 4.86 ± 1.53 and 6.39 ± 2.93, respectively. The score improvement of the activity group was significantly higher than that of the control group (p = 0.006; d = 0.65). The perception scores of interest, knowledge attainment, and satisfaction were significantly higher in the intervention group compared to the control group. Conclusion The findings of this study suggest that experiential activities facilitate better comprehension of abstract neuroanatomical concepts as compared to traditional didactic teaching.

Barriers to enrolling in voluntary treatment programs in Malaysia: a study of women who use methamphetamine (WWUM).

Women with substance use disorders (SUDs) have been widely reported to face barriers in seeking treatment. We sought to identify barriers that prevented women who use methamphetamine (WWUM) from accessing the decade-old Voluntary Treatment Centers (VTCs) in Malaysia. A total of 153 WWUM who were undergoing rehabilitation for methamphetamine use at a compulsory drug detention center (CDDC) were recruited for this cross-sectional study. Data were collected by canvasing a structured questionnaire through face-to-face meetings. Of the total sample, 131 (86%) were Malays, with a mean age of 32.1 years. The commonly cited treatment barriers were the belief that methamphetamine use was not problematic (42%), not knowing how to seek treatment (38%), feeling embarrassed to seek treatment (33%), the lack of family support (24%), and the long waiting time for enrollment (23%). Logistic analyses indicated that a longer duration of use increased the odds of not acknowledging methamphetamine use as a problem while older participants had lower odds of holding a similar view. A longer duration of use also increased the odds of claiming treatment was not needed but lowered the odds of asserting a lack of confidence in treatment. Furthermore, Malays had higher odds of lacking family support in seeking treatment while being employed lowered the odds of not wanting treatment. Addressing these concerns will hopefully encourage higher participation of WWUM in voluntary treatment programs.

Linking scientific instruments and computation: Patterns, technologies, and experiences.

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subsets of such massive data streams, such as by explicitly discarding some data elements or by directing instruments to relevant areas of experimental space. Thus, methods are required for configuring and running distributed computing pipelines-what we call flows-that link instruments, computers (e.g., for analysis, simulation, artificial intelligence [AI] model training), edge computing (e.g., for analysis), data stores, metadata catalogs, and high-speed networks. We review common patterns associated with such flows and describe methods for instantiating these patterns. We present experiences with the application of these methods to the processing of data from five different scientific instruments, each of which engages powerful computers for data inversion,model training, or other purposes. We also discuss implications of such methods for operators and users of scientific facilities.