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Two dimensional site interaction models of water and alcohols are mixed in various proportions and studied by Monte Carlo simulations, with the purpose to clarify problems related to simulation of real micro-heterogeneous systems. Three alcohols are considered, methanol, pentanol and octanol. The main finding is that, while real alcohols demix with water from butanol onward, their 2D analogs are always fully miscible, while developing increasingly pronounced micro-segregation as the alcohol tail length increases. This is not a consequence of the intrinsically higher fluctuations in 2D, but rather a reorganization of these fluctuations under the charge ordering mechanism. The second finding is that water drives the micro-segregation through strong self-aggregation, but this is not enough to achieve full phase separation because of the water-alcohol contact at the outer rim of the water domains. In this work we examine how this local heterogeneity develops with increasing alcohol alkyl tails, monitored with the study of pair correlation functions, structure factors and Kirkwood-Buff integrals. The absence of clear local self-averaging of the latter provides an illustration of the ten

Prolonged alcohol use results in neuroadaptations that mark more severe and treatment-resistant alcohol use. The goal of this study was to identify functional connectivity brain patterns underlying Alcohol Use Disorder (AUD)-related characteristics in fifty-five adults (31 female) who endorsed heavy alcohol use. We hypothesized that resting-state functional connectivity (rsFC) of the Salience (SN), Frontoparietal (FPN), and Default Mode (DMN) networks would reflect self-reported recent and lifetime alcohol use, laboratory-based alcohol seeking, urgency, and sociodemographic characteristics related to AUD. To test our hypothesis, we combined the triple network model (TNM) of psychopathology with a multivariate data-driven approach, regularized partial least squares (rPLS), to unfold concurrent functional connectivity (FC) patterns and their association with AUD-related characteristics. We observed three concurrent associations of interest: i) drinking and age-related cross communication between the SN and both the FPN and DMN; ii) family history density of AUD and urgency anticorrelations between the SN and FPN; and iii) alcohol seeking and sex-associated SN and DMN interactions. Th

Alcohol Use Disorder (AUD) is a prevalent addictive disorder affecting an estimated 29.5 million Americans. It is characterized by impaired control over alcohol consumption despite negative consequences. The number of diagnostic criteria met by an individual typically determines the severity of AUD. Research into AUD focuses on understanding individual susceptibility differences and developing preventive strategies. Alcohol vapor inhalation has emerged as a promising method for pathophysiological investigations in animals, allowing researchers to control the dose and duration of alcohol exposure. This approach is crucial for studying the escalation of voluntary alcohol-drinking behavior. Current commercial systems for alcohol vapor generation have limitations, including combustion risks and the need to adjust multiple parameters. Other methods, like bubbling or blow-over evaporation, face challenges in maintaining equilibrium and avoiding aerosolization. To address these issues, a new type of ethanol vapor generating system is proposed that relies solely on temperature control, creating a vacuum into which ethanol evaporates under thermodynamic control. This approach eliminates the

This paper presents a unique driving dataset collected in Nigeria via mobile phone sensors to support a machine learning model for detecting alcohol-influenced driving behaviours, with the long-term aim of integrating this model into a mobile application that encourages safer driving behaviours. Driving under the influence of alcohol is a major public safety concern, particularly in low-income countries like Nigeria, where traditional enforcement mechanisms may be limited. The proposed model leverages smartphone sensors such as accelerometers, gyroscopes, and GPS to provide a non-invasive, continuous solution for detecting impaired driving patterns in real time. This study adapts existing data processing and pattern matching methodologies to label real-world driving data collected from Nigerian drivers, which are then used to train the model. A decision tree classifier is developed to detect alcohol influence, based on behavioural and temporal features, achieving a recall of 100%, a precision of 60%, and an F1 score of 75%. The model's overall accuracy was 90.91%, ensuring that no alcohol influenced trips were missed. Key predictive features included speed variability, course devia

Substance use disorders (SUDs) are a serious public health concern in the United States. Alcohol and cannabis are two of the most widely used substances. For adolescent/youth users of alcohol or cannabis, we propose a joint Bayesian learning model to predict their risks of developing alcohol use disorder (AUD) and cannabis use disorder (CUD) in adulthood based on their personal risk factors. The model is trained on nationally representative longitudinal data from Add Health (n = 12503). It consists of sub-models that predict the two SUDs for three groups of users-those who use alcohol only, cannabis only, and both substances - based on shared as well as unique risk factors. The model comprises of ten predictors. We externally validate the model on two independent datasets. The areas under the receiver operating characteristic curves for AUD and CUD, respectively, are: (a) 0.719 and 0.690 based on 5-fold cross-validation, (b) 0.748 and 0.710 based on validation dataset 1, and (c) 0.650 and 0.750 based on validation dataset 2. A simulation study shows that the proposed joint modeling approach generally performs better than separate univariate modeling of the corresponding dependent o

Reforming alcohol price regulations in wine-producing countries is challenging, as current price regulations reflect the alignment of cultural preferences with economic interests rather than public health concerns. We evaluate and compare the impact of counterfactual alcohol pricing policies on consumer behaviors, firms, and markets in France. We develop a micro-founded partial equilibrium model that accounts for consumer preferences over purchase volumes across alcohol categories and over product quality within categories, and for firms' strategic price-setting. After calibration on household scanner data, we compare the impacts of replacing current taxes by ethanol-based volumetric taxes with a minimum unit price (MUP) policy of 0.50 Euro per standard drink. The results show that the MUP in addition to the current tax outperforms a tax reform in reducing ethanol purchases (-15% vs. -10% for progressive taxation), especially among heavy drinking households (-17%). The MUP increases the profits of small and medium wine firms (+39%) while decreasing the profits of large manufacturers and retailers (-39%) and maintaining tax revenues stable. The results support the MUP as a targeted

Alcohol Use Disorder (AUD) is a major concern for public health organizations worldwide, especially as regards the adolescent population. The consumption of alcohol in adolescents is known to be influenced by seeing friends and even parents drinking alcohol. Building on this fact, a number of studies into alcohol consumption among adolescents have made use of Social Network Analysis (SNA) techniques to study the different social networks (peers, friends, family, etc.) with whom the adolescent is involved. These kinds of studies need an initial phase of data gathering by means of questionnaires and a subsequent analysis phase using the SNA techniques. The process involves a number of manual data handling stages that are time consuming and error-prone. The use of knowledge engineering techniques (including the construction of a domain ontology) to represent the information, allows the automation of all the activities, from the initial data collection to the results of the SNA study. This paper shows how a knowledge model is constructed, and compares the results obtained using the traditional method with this, fully automated model, detailing the main advantages of the latter. In the

We propose a novel dynamical model for blood alcohol concentration that incorporates $ψ$-Caputo fractional derivatives. Using the generalized Laplace transform technique, we successfully derive an analytic solution for both the alcohol concentration in the stomach and the alcohol concentration in the blood of an individual. These analytical formulas provide us a straightforward numerical scheme, which demonstrates the efficacy of the $ψ$-Caputo derivative operator in achieving a better fit to real experimental data on blood alcohol levels available in the literature. In comparison to existing classical and fractional models found in the literature, our model outperforms them significantly. Indeed, by employing a simple yet non-standard kernel function $ψ(t)$, we are able to reduce the error by more than half, resulting in an impressive gain improvement of 59 percent.

Exploring the impact of alcohol additives on combustion and pyrolysis of ammonia/methane is of great importance in the pursuit of sustainable energy technologies. This work employs Reactive Force Field (ReaxFF) molecular dynamics (MD) simulations to investigate the underlying mechanism of how ethanol and methanol additives affect reaction pathways, NOx emissions and bond energy characteristics in ammonia-methane pyrolysis and combustion processes. It shows that adding alcohols altered NOx formation pathways, reducing the diversity of NOx and shifting the equilibrium toward simpler NOx such as NO and NO2. At 2,000 K, alcohol blends, particularly methanol, demonstrated a notable reduction in NO2 formation. At 3,000 K, both ethanol and methanol suppressed NO production, but the influence of methanol was stronger. Nitric acid production, HNO3, was present at lower temperatures but became negligible at higher temperatures because of the thermal breakdown of the higher-order NOx. These trends confirm that alcohol additives realize a probable role in moderating NOx emissions and stabilizing reaction pathways. The pyrolysis in modified reaction pathways, which facilitated the decomposition

Domestic violence (DV) is a serious public health issue, with 1 in 3 women and 1 in 4 men experiencing some form of partner-related violence every year. Existing research has shown a strong association between alcohol use and DV at the individual level. Accordingly, alcohol use could also be a predictor for DV at the neighborhood level, helping identify the neighborhoods where DV is more likely to happen. However, it is difficult and costly to collect data that can represent neighborhood-level alcohol use especially for a large geographic area. In this study, we propose to derive information about the alcohol outlet visits of the residents of different neighborhoods from anonymized mobile phone location data, and investigate whether the derived visits can help better predict DV at the neighborhood level. We use mobile phone data from the company SafeGraph, which is freely available to researchers and which contains information about how people visit various points-of-interest including alcohol outlets. In such data, a visit to an alcohol outlet is identified based on the GPS point location of the mobile phone and the building footprint (a polygon) of the alcohol outlet. We present

Determination of the volume content of ethanol in the alcohol products in practice is usually determined by pycnometry, electronic densimetry, or densimetry using a hydrostatic balance in accordance with Commission Regulation No 2870/2000. However, these methods determine directly only density of the tested liquid sample and does not take into account the effects of other volatile components such as aldehydes, esters and higher alcohols. So they are appropriate only for binary water-ethanol solutions in accordance with international table adopted by the International Legal Metrology Organization in its Recommendation No 22. Availability notable concentrations of the higher alcohols and ethers in different alcohol-based products, e. g. in whisky, cognac, brandy, wine as well as in waste alcohol and alcohol beverage production, leads to the significant contribution of these compounds in the value of the density of tested alcohol-containing sample. As a result, determination of the volume of ethanol content for such alcohol products in gives the value of the strength, which may significantly differ from the true one. Using incorrectly calculated volume content of ethyl alcohol leads t

Alcohol consumption has been shown to influence cardiovascular mechanisms in humans, leading to observable alterations in the plasma metabolomic profile. Regression models are commonly employed to investigate these effects, treating metabolomics features as the outcomes and alcohol intake as the exposure. Given the latent dependence structure among the numerous metabolomic features (e.g., co-expression networks with interconnected modules), modeling this structure is crucial for accurately identifying metabolomic features associated with alcohol intake. However, integrating dependence structures into regression models remains difficult in both estimation and inference procedures due to their large or high dimensionality. To bridge this gap, we propose an innovative multivariate regression model that accounts for correlations among outcome features by incorporating an interconnected community structure. Furthermore, we derive closed-form and likelihood-based estimators, accompanied by explicit exact and explicit asymptotic covariance matrix estimators, respectively. Simulation analysis demonstrates that our approach provides accurate estimation of both dependence and regression coef

Non-invasive continuous alcohol monitoring has potential applications in both population research and in clinical management of acute alcohol intoxication or chronic alcoholism. Current wearable monitors based on transdermal alcohol content (TAC) sensing are relatively bulky and have limited quantification accuracy. Here we describe the development of a discreet wearable transdermal alcohol (TAC) sensor in the form of a wristband or armband. This novel sensor can detect vapor-phase alcohol in perspiration from 0.09 ppm (equivalent to 0.09 mg/dL sweat alcohol concentration at 25 °C under Henry's Law equilibrium) to over 500 ppm at one-minute time resolution. The TAC sensor is powered by a 110 mAh lithium battery that lasts for over 7 days. In addition, the sensor can function as a medical "internet-of-things" (IoT) device by connecting to an Android smartphone gateway via Bluetooth Low Energy (BLE) and upload data to a cloud informatics system. Such wearable IoT sensors may enable large-scale alcohol-related research and personalized management. We also present evidence suggesting a hypothesis that perspiration rate is the dominant factor leading to TAC measurement variabilities, wh

Molecular specific photonic localization is a sensitive technique to probe the structural alterations or abnormalities in a cell such as abnormalities due to alcohol or other drugs. Alcohol consumption during pregnancy by mother, or fetal alcoholism, is one of the major factors of mental retardation in children. Fetal alcohol syndrome and alcohol related neurodevelopmental disorder are awful outcomes of the maternal alcohol consumption linked with notable cognitive and behavioral defects. Alcohol consumed by the pregnant mother, being teratogenic, interferes with the fetal health resulting brain damage and other birth defects. This might affect the brain cells at the very nanolevel which cannot be predicted by the present histopathological procedures. We perform quantification of nanoscale spatial structural alterations in two different spatial molecular components, DNA and histone molecular mass densities, in brain cell nuclei of fetal alcohol effected (FAE) pups at postnatal day 60. Confocal images of the brain cells are collected and the degree of morphological alterations in DNA and histone, in terms of mass density fluctuations are obtained using the recently developed molecul

It is speculated that there might be some linkage between interstellar aldehydes and their corresponding alcohols. Here, an observational study and astrochemical modeling are coupled together to illustrate the connection between them. The ALMA Cycle 4 data of a hot molecular core, G10.47+0.03 is utilized for this study. Various aldehydes (acetaldehyde, propanal, and glycolaldehyde), alcohols (methanol and ethylene glycol), and a ketone (acetone) are identified in this source. The excitation temperatures and the column densities of these species were derived via the rotation diagram method assuming LTE conditions. An extensive investigation is carried out to understand the formation of these species. Six pairs of aldehyde-alcohol: i) methanal and methanol; ii) ethanal and ethanol; iii) propanal and 1-propanol; iv) propenal and allyl alcohol; v) propynal and propargyl alcohol; vi) glycolaldehyde and ethylene glycol; vii) along with one pair of ketone-alcohol (acetone and isopropanol) and viii) ketene-alcohol (ethenone and vinyl alcohol) are considered for this study. Two successive hydrogenation reactions in the ice phase are examined to form these alcohols from aldehydes, ketone, an

Human brain function dynamically adjusts to ever-changing stimuli from the external environment. Studies characterizing brain functional reconfiguration are nevertheless scarce. Here we present a principled mathematical framework to quantify brain functional reconfiguration when engaging and disengaging from a stop signal task (SST). We apply tangent space projection (a Riemannian geometry mapping technique) to transform functional connectomes (FCs) of 54 participants and quantify functional reconfiguration using the correlation distance of the resulting tangent-FCs. Our goal was to compare functional reconfigurations in individuals at risk for alcohol use disorder (AUD). We hypothesized that functional reconfigurations when transitioning to/from a task would be influenced by family history of alcohol use disorder (FHA) and other AUD risk factors. Multilinear regression models showed that engaging and disengaging functional reconfiguration were associated with FHA and recent drinking. When engaging in the SST after a rest condition, functional reconfiguration was negatively associated with recent drinking, while functional reconfiguration when disengaging from the SST was negativel

Generally adopted design strategies for enhancing the photocatalytic activity are aimed at tuning properties such as the visible light response, the exposed crystal facets, and the nanocrystal shape. Here, we present a different approach for designing efficient photocatalysts displaying a substrate-specific reactivity upon defect engineering. The defective anisotropic brookite TiO2 photocatalyst functionalized with Pt nanocrystals are tested for alcohol photoreforming showing up to an 11-fold increase in methanol oxidation rate, compared to the unreduced one, whilst presenting much lower ethanol or isopropanol specific oxidation rates. We demonstrate that the alcohol oxidation and hydrogen evolution reactions are tightly related, and when the substrate-specific alcohol oxidation ability is increased, the hydrogen evolution is significantly boosted. The reduced anisotropic brookite shows up to twenty-six-fold higher specific photoactivity with respect to anatase and brookite with isotropic nanocrystals, reflecting the different type of defective catalytic sites formed depending on the TiO2 polymorph and its crystal shape. Advanced in-situ characterizations and theoretical investigat

In this study, alcohol smell and imagination of alcohol has been shown to change the condition of a human organism.In this study, alcohol smell has been shown to change the condition of a human organism. Based on the test results, the presence of alcohol was observed upon breathing out, but was rarely observed in spits and much rarer in urines. This effect is most evident shortly after an olfactory perception of alcohol and continues for 60 min for some test persons. The test persons also noted the appearance of a subjective feeling of alcohol intoxication. However, the condition developed when the alcohol smell perception differed from the classical alcohol intoxication, i.e., the test subjects only have a few intoxication symptoms, and not one person would have all of them.

We study the interaction of lipid bilayers with short chain alcohols using molecular dynamics on different length scales. We use detailed atomistic modeling and modeling on the length scale where an alcohol is just an amphiphilic dimer. Our strategy is to calibrate a coarse--grained model against the detailed model at selected state points at low alcohol concentration and then perform a wider range of simulations using the coarse--grained model. We get semiquantitative agreement with experiment for the major observables such as order parameter and area per molecule. We find a linear increase of area per molecule with alcohol concentration. The alcohol molecules in both system descriptions are in close contact with the glycerol backbone. Butanol molecules can enter the bilayer to some extent in contrast to the behavior of shorter alcohols. At very high alcohol concentrations we find clearly increased interdigitation between leaflets.