Open-Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F).

An open-source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization.

Quantifying local and global mass balance errors in physics-informed neural networks.

Physics-informed neural networks (PINN) have recently become attractive for solving partial differential equations (PDEs) that describe physics laws. By including PDE-based loss functions, physics laws such as mass balance are enforced softly in PINN. This paper investigates how mass balance constraints are satisfied when PINN is used to solve the resulting PDEs.

Safer-use strategies in the context of harm-reduction treatment for people experiencing homelessness and alcohol use disorder.

Background: Two, randomized controlled trials found harm-reduction treatment for AUD (HaRT-A) improves alcohol outcomes for adults experiencing homelessness. HaRT-A, which neither requires nor precludes abstinence, entails tracking alcohol-related harm, harm-reduction goals, and safer-use strategies. This secondary dual study qualitatively describes this last component, safer-use strategies, and their quantitative association with treatment outcomes.

Deep learning with mixup augmentation for improved pore detection during additive manufacturing.

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment.

Moringa, Milk Thistle, and Jujube Seed Cold-Pressed Oils: Characteristic Profiles, Thermal Properties, and Oxidative Stability.

Cold-pressed moringa, milk thistle, and jujube seed oils were investigated in terms of their characteristic profiles, thermal properties, and oxidative stability. The findings proved that the extracted oils were characterized by high nutritional values, which encourages their use in various fields. Results showed significant differences between the obtained oils.

The Relations Among Childhood Maltreatment and Later Intimate Partner Violence Victimization With and Without a Weapon in a Sample of Pregnant Black Individuals.

Black pregnant and postpartum individuals are at risk for intimate partner violence (IPV), and those with a history of childhood maltreatment and IPV are even more likely to be re-victimized during pregnancy. However, it is unknown if specific types of child maltreatment predict later IPV with and without a weapon better than others. The current study sought to (i) document the prevalence of childhood maltreatment and IPV and (ii) examine the relations among types of childhood maltreatment and later IPV with and without a weapon within a sample of Black individuals seeking prenatal care at a large public hospital in the southeastern United States.

User-Guided Enhancements to a Technology-Facilitated Resilience Program to Address Opioid Risks Following Traumatic Injury in Youth: Qualitative Interview Study.

Background: Youth with traumatic injury experience elevated risk for behavioral health disorders, yet posthospital monitoring of patients' behavioral health is rare. The Telehealth Resilience and Recovery Program (TRRP), a technology-facilitated and stepped access-to-care program initiated in hospitals and designed to be integrated seamlessly into trauma center operations, is a program that can potentially address this treatment gap. However, the TRRP was originally developed to address this gap for mental health recovery but not substance use.

Indirect effect of negative evaluations of therapy on the association between racial stress and posttraumatic stress disorder symptoms in pregnant Black persons.

Objective: Black pregnant individuals are at disproportionate risk for posttraumatic stress disorder (PTSD) compared to other groups. A wealth of literature suggests racial stress contributes to this inequity, but cultural and structural mechanisms, such as perceived barriers to mental health treatment, underlying the relationship between racial stress and PTSD symptoms remain understudied. Negative evaluations of psychotherapy and stigma represent potential mechanisms, though no previous studies have examined these associations.

Predictive scale-bridging simulations through active learning.

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-bridging over brute-force increases in the number of mesh elements. For instance, quantitative predictions of transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, are impossible without accounting for molecular-level interactions. Similarly, inertial confinement fusion simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions.

Hepatic ketogenesis regulates lipid homeostasis via ACSL1-mediated fatty acid partitioning.

Liver-derived ketone bodies play a crucial role in fasting energy homeostasis by fueling the brain and peripheral tissues. Ketogenesis also acts as a conduit to remove excess acetyl-CoA generated from fatty acid oxidation and protects against diet-induced hepatic steatosis. Surprisingly, no study has examined the role of ketogenesis in fasting-associated hepatocellular lipid metabolism.

Diagnostic Utility of NLR, PLR and MLR in Early Diagnosis of Gastric Cancer: an Analytical Cross-Sectional Study.

Purpose: Inflammatory markers such as neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR) are linked with the pathogenesis of gastric cancer (GC). However, the clinical significance of the combination of these markers is unclear. Hence, this study was carried out to determine the individual and combined diagnostic accuracy of NLR, PLR and MLR among patients with GC.

A Systematic Review of Antenatal Risk Scoring Systems in India to Predict Adverse Neonatal Outcomes.

Background: The purpose of antenatal care (ANC) is to identify 'at-risk' pregnant women, to provide quality care for all, and maximize the allocation of resources for those who need them the most. To address the synergistic effect of risk factors, clinicians across the globe developed antenatal scoring systems.

Objective: This review aims to investigate various antenatal risk scoring systems developed and used in India to predict adverse neonatal outcome.

A machine learning framework for rapid forecasting and history matching in unconventional reservoirs.

We present a novel workflow for forecasting production in unconventional reservoirs using reduced-order models and machine-learning. Our physics-informed machine-learning workflow addresses the challenges to real-time reservoir management in unconventionals, namely the lack of data (i.e.

Effect of succinylation on the secondary structures, surface, and thermal properties of date palm pollen protein concentrate.

The present study was attempted to investigate the effect of succinylation, as chemical modification, on the functionality of male date palm pollen protein concentrate (MDPPPC). Succinylation was applied at two levels, 4 and 8 mol of succinic acid per mole of lysine. 4 M and 8 M were compared to the native MDPPPC.

Transient flow modeling in fractured media using graphs.

We describe a method to simulate transient fluid flows in fractured media using an approach based on graph theory. Our approach builds on past work where the graph-based approach was successfully used to simulate steady-state fluid flows in fractured media. We find a mean computational speedup of the order of 1400 from an ensemble of a 100 discrete fracture networks in contrast to the O(10^{4}) speedup that was obtained for steady-state flows earlier.

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects.

Accurate ranking of compounds with regards to their binding affinity to a protein using computational methods is of great interest to pharmaceutical research. Physics-based free energy calculations are regarded as the most rigorous way to estimate binding affinity. In recent years, many retrospective studies carried out both in academia and industry have demonstrated its potential.

Modeling and scale-bridging using machine learning: nanoconfinement effects in porous media.

Fine-scale models that represent first-principles physics are challenging to represent at larger scales of interest in many application areas. In nanoporous media such as tight-shale formations, where the typical pore size is less than 50 nm, confinement effects play a significant role in how fluids behave. At these scales, fluids are under confinement, affecting key properties such as density, viscosity, adsorption, etc.

Effect of extraction methods on the physicochemical, structural, functional, and antioxidant properties of the dietary fiber concentrates from male date palm flowers.

The current study evaluates the effect of both aqueous and alkaline extraction methods on the physicochemical, structural, functional, and antioxidant properties of dietary fibers (DF) from male date palm flowers (MDPF). The DF extracted by the alkali treatment (ADF) display a higher DF content as well as lower protein and lipid content than the DF resulting from watery extraction (WDF). The scanning electron microscopy, the Fourier-transform infrared spectroscopy, and the X-ray diffraction show that the alkaline treatment contributes to a slight modification of the structural characteristics of ADF leading to better purity and functional properties.

Synthesis and SAR development of quinoline analogs as novel P2X7 receptor antagonists.

The P2X7 receptor (P2X7R) plays an important role in diverse conditions associated with tissue damage and inflammation, suggesting that the human P2X7R (hP2X7R) is an attractive therapeutic target. In the present study, the synthesis and structure-activity relationship (SAR) of a novel series of quinoline derivatives as P2X7R antagonists are described herein. These compounds exhibited mechanistic activity (YO PRO) in an engineered HEK293 expressing hP2X7R as well as a functional response (IL-1β) in human THP-1 (hTHP-1) cellular assays.

Branching of hydraulic cracks enabling permeability of gas or oil shale with closed natural fractures.

While hydraulic fracturing technology, aka fracking (or fraccing, frac), has become highly developed and astonishingly successful, a consistent formulation of the associated fracture mechanics that would not conflict with some observations is still unavailable. It is attempted here. Classical fracture mechanics, as well as current commercial software, predict vertical cracks to propagate without branching from the perforations of the horizontal well casing, which are typically spaced at 10 m or more.

Desire for Information and Preference for Participation in Treatment Decisions in Patients With Cancer Presenting to the Department of General Surgery in a Tertiary Care Hospital in India.

Purpose: Providing appropriate information to patients about their illness helps them to cope with the diagnosis. Shared decision making is a key concept in managing patients with cancer. There are no data available about the desire for information and preference for participation in treatment decisions among Indian patients with cancer.

Quantifying Topological Uncertainty in Fractured Systems using Graph Theory and Machine Learning.

Fractured systems are ubiquitous in natural and engineered applications as diverse as hydraulic fracturing, underground nuclear test detection, corrosive damage in materials and brittle failure of metals and ceramics. Microstructural information (fracture size, orientation, etc.) plays a key role in governing the dominant physics for these systems but can only be known statistically.

Modeling flow and transport in fracture networks using graphs.

Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers.

Effect of heated-air blanket on the dispersion of squames in an operating room.

High-fidelity, predictive fluid flow simulations of the interactions between the rising thermal plumes from forced air warming blower and the ultra-clean ventilation air in an operating room (OR) are conducted to explore whether this complex flow can impact the dispersion of squames to the surgical site. A large-eddy simulation, accurately capturing the spatiotemporal evolution of the flow in 3 dimensions together with the trajectories of squames, is performed for a realistic OR consisting of an operating table (OT), side tables, surgical lamps, medical staff, and a patient. Two cases are studied with blower-off and blower-on together with Lagrangian trajectories of 3 million squames initially placed on the floor surrounding the OT.