Photocatalytic degradation and dechlorination mechanism of diclofenac using heterojunction Mn-doped tungsten trioxide (Mn-WO) nanoparticles under LED visible light from aqueous solutions.

The aim of this study was to investigate the photocatalytic mineralization and degradation of Diclofenac (DCF) using Mn-WO/LED in a photoreactor setup. The study analyzed the impact of operational variables, such as the initial concentration of DCF, pH level, reaction time, and catalyst dosage, on the degradation of DCF in the Mn-WO/LED process. The characteristics of Mn-WO nanoparticles (NPs) were analyzed using a variety of techniques, including BET, TEM, XRD, TGA, FTIR, and FESEM.

Recent advances and applications of stimuli-responsive nanomaterials for water treatment: A comprehensive review.

The development of stimuli-responsive nanomaterials holds immense promise for enhancing the efficiency and effectiveness of water treatment processes. These smart materials exhibit a remarkable ability to respond to specific external stimuli, such as light, pH, or magnetic fields, and trigger the controlled release of encapsulated pollutants. By precisely regulating the release kinetics, these nanomaterials can effectively target and eliminate contaminants without compromising the integrity of the water system.

A neural modeling approach to study mechanisms underlying the heterogeneity of visual spatial frequency sensitivity in schizophrenia.

Patients with schizophrenia exhibit abnormalities in spatial frequency sensitivity, and it is believed that these abnormalities indicate more widespread dysfunction and dysregulation of bottom-up processing. The early visual system, including the first-order Lateral Geniculate Nucleus of the thalamus (LGN) and the primary visual cortex (V1), are key contributors to spatial frequency sensitivity. Medicated and unmedicated patients with schizophrenia exhibit contrasting changes in spatial frequency sensitivity, thus making it a useful probe for examining potential effects of the disorder and antipsychotic medications in neural processing.

Dynamics of antimicrobial resistance and susceptibility profile in full-scale hospital wastewater treatment plants.

Drug resistance has become a matter of great concern, with many bacteria now resist multiple antibiotics. This study depicts the occurrence of antibiotic-resistant bacteria (ARB) and resistance patterns in five full-scale hospital wastewater treatment plants (WWTPs). Samples of raw influent wastewater, as well as pre- and post-disinfected effluents, were monitored for targeted ARB and resistance genes in September 2022 and February 2023.

Retraction: Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents.

[This retracts the article DOI: 10.1039/D3RA05360A.].

Machine learning-powered estimation of malachite green photocatalytic degradation with NML-BiFeO composites.

This study explores the potential of photocatalytic degradation using novel NML-BiFeO (noble metal-incorporated bismuth ferrite) compounds for eliminating malachite green (MG) dye from wastewater. The effectiveness of various Gaussian process regression (GPR) models in predicting MG degradation is investigated. Four GPR models (Matern, Exponential, Squared Exponential, and Rational Quadratic) were employed to analyze a dataset of 1200 observations encompassing various experimental conditions.

Photoreduction of atrazine from aqueous solution using sulfite/iodide/UV process, degradation, kinetics and by-products pathway.

Due to its widespread use in agriculture, atrazine has entered aquatic environments and thus poses potential risks to public health. Therefore, researchers have done many studies to remove it. Advanced reduction process (ARP) is an emerging technology for degrading organic contaminants from aqueous solutions.

Bioaccumulation of potentially toxic elements in leafy and tuberous vegetables: a comparison based on meta-analysis studies with a cumulative health risk assessment.

Seventy seven research papers published from 1986 to 2018 were observed. These papers investigated PTEs (Pb, Cd, Cu, As, Fe, Zn, Ni, and total Cr) in leafy (mint, spinach, coriander, and lettuce) and tuberous (potato, carrot, radish, and onion) vegetables irrigated by wastewater. The studies observed in our paper were conducted in 19 countries.

Elderly patients benefit from minimally invasive mitral valve surgery: perioperative risk management matters.

Objectives: The goal was to assess the single-centre results of minimally invasive mitral valve surgery (MIMVS) in the elderly population.

Methods: All patients referred for minimally invasive valve surgery underwent a standardized preoperative screening. We performed a retrospective analysis of 131 consecutive elderly patients (≥75 years) who underwent endoscopic MIMVS through a right mini-thoracotomy.

Mechanisms and factors affecting the removal of minocycline from aqueous solutions using graphene-modified resorcinol formaldehyde aerogels.

In recent years, concerns about the presence of pharmaceutical compounds in wastewater have increased. Various types of residues of tetracycline family antibiotic compounds, which are widely used, are found in environmental waters in relatively low and persistent concentrations, adversely affecting human health and the environment. In this study, a resorcinol formaldehyde (RF) aerogel was prepared using the sol-gel method at resorcinol/catalyst ratio of 400 and resorcinol/water ratio of 2 and drying at ambient pressure for removing antibiotics like minocycline.

A neural modeling approach to study mechanisms underlying the heterogeneity of visual spatial frequency sensitivity in schizophrenia.

Patients with schizophrenia exhibit abnormalities in spatial frequency sensitivity, and it is believed that these abnormalities indicate more widespread dysfunction and dysregulation of bottom-up processing. The early visual system, including the first-order Lateral Geniculate Nucleus of the thalamus (LGN) and the primary visual cortex (V1), are key contributors to spatial frequency sensitivity. Medicated and unmedicated patients with schizophrenia exhibit contrasting changes in spatial frequency sensitivity, thus making it a useful probe for examining potential effects of the disorder and antipsychotic medications in neural processing.

A neural model of modified excitation/inhibition and feedback levels in schizophrenia.

Introduction: The strength of certain visual illusions, including contrast-contrast and apparent motion, is weakened in individuals with schizophrenia. Such phenomena have been interpreted as the impaired integration of inhibitory and excitatory neural responses, and impaired top-down feedback mechanisms.

Methods: To investigate whether and how these factors influence the perceived contrast-contrast and apparent motion illusions in individuals with schizophrenia, we propose a two-layer network, with top-down feedback from layer 2 to layer 1 that can model visual receptive fields (RFs) and their inhibitory and excitatory subfields.

Removal of heavy metals from the aqueous solution by nanomaterials: a review with analysing and categorizing the studies.

With the development of nanotechnology and its application in various sciences, scientists have investigated the use of nanoparticles as adsorbents to remove heavy metals from aqueous solutions all over the world. So far, the results of many of these studies have been published in reputable journals. Obviously, reviewing these articles and summarizing the results of these studies from different aspects will provide new perspectives for the development of this technology for heavy metals removal from water.

Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents.

In recent years, deep eutectic solvents (DESs) have garnered considerable attention for their potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO) solubility in DES is crucial for optimizing these solvent systems and advancing their application in sustainable technologies. In this study, we presented an evolving hybrid Quantitative Structure-Property Relationship and Gaussian Process Regression (QSPR-GPR) model that enables accurate predictions of CO solubility in various DESs.

Perception of rigidity in three- and four-dimensional spaces.

Our brain employs mechanisms to adapt to changing visual conditions. In addition to natural changes in our physiology and those in the environment, our brain is also capable of adapting to "unnatural" changes, such as inverted visual-inputs generated by inverting prisms. In this study, we examined the brain's capability to adapt to hyperspaces.

Sleep spindles in primates: Modeling the effects of distinct laminar thalamocortical connectivity in core, matrix, and reticular thalamic circuits.

Sleep spindles are associated with the beginning of deep sleep and memory consolidation and are disrupted in schizophrenia and autism. In primates, distinct core and matrix thalamocortical (TC) circuits regulate sleep spindle activity through communications that are filtered by the inhibitory thalamic reticular nucleus (TRN); however, little is known about typical TC network interactions and the mechanisms that are disrupted in brain disorders. We developed a primate-specific, circuit-based TC computational model with distinct core and matrix loops that can simulate sleep spindles.

Responses of activated sludge under a short-term exposure to facial scrub microbeads: implications from treatment performance and higher-life microbial population dynamics.

In this study, four identical laboratory-scale sequencing batch reactors (SBRs) were continuously operated with different concentrations of microbeads (MBs) (5,000-15,000 MBs/L) to investigate the stress-responses of activated sludge under the MB exposure. It was found that the overall treatment performance (organic removal) of SBRs was fairly affected by short-term exposure to low levels of MBs; however, it was adversely affected as the concentration of MBs increased. The average concentration of mixed liquor suspended solids and heterotrophic bacteria in the reactor fed with 15,000 MBs/L were 16 and 30% less than in the pristine control reactor, respectively.

Insights into the Adsorption Properties of Mixed Matrix Membranes (Pebax 1657--Chitosan-PVDF-Bovine Serum Albumin@ZIF-CO-1) for the Antiviral COVID-19 Treatment Drugs Remdesivir and Nirmatrelvir: An In Silico Study.

The effect of the COVID-19 pandemic on the accumulation of environmental pollutants has been significant. In that way, waste management systems have faced problems, and the amount of hazardous and medical wastes has increased. As pharmaceuticals associated with the treatment of COVID-19 enter the environment, aquatic and terrestrial ecosystems have been negatively impacted, potentially disrupting natural processes and harming aquatic life.

A neural model of modified excitation/inhibition and feedback levels in schizophrenia.

The strength of certain visual illusions is weakened in individuals with schizophrenia. Such phenomena have been interpreted as the impaired integration of inhibitory and excitatory neural responses, and impaired top-down feedback mechanisms. To investigate whether and how these factors influence the perceived illusions in individuals with schizophrenia, we propose a two-layer network that can model visual receptive fields (RFs), their inhibitory and excitatory subfields, and the top-down feedback.

Left ventricular assist device implantation and clinical outcomes in the Netherlands.

Background: Left ventricular assist device (LVAD) therapy is an established treatment for advanced heart failure with reduced ejection fraction. We evaluated the characteristics and clinical outcomes of patients implanted with an LVAD in the Netherlands.

Methods: Patients implanted with an LVAD in the Netherlands between 2016 and 2020 were included in the analysis.

Visual illusion susceptibility in autism: A neural model.

While atypical sensory perception is reported among individuals with autism spectrum disorder (ASD), the underlying neural mechanisms of autism that give rise to disruptions in sensory perception remain unclear. We developed a neural model with key physiological, functional and neuroanatomical parameters to investigate mechanisms underlying the range of representations of visual illusions related to orientation perception in typically developed subjects compared to individuals with ASD. Our results showed that two theorized autistic traits, excitation/inhibition imbalance and weakening of top-down modulation, could be potential candidates for reduced susceptibility to some visual illusions.

Impact of optogenetic pulse design on CA3 learning and replay: A neural model.

Optogenetic manipulation of hippocampal circuitry is an important tool for investigating learning . Numerous approaches to pulse design have been employed to elicit desirable circuit and behavioral outcomes. Here, we systematically test the outcome of different single-pulse waveforms in a rate-based model of hippocampal memory function at the level of mnemonic replay extension and synaptic weight formation in CA3 and CA1.

Cardiac arrest resulting from an unidentified foreign object, later identified as a balloon cover, within the left anterior descending coronary artery.

A 31-year-old man with a history of hypertrophic cardiomyopathy and alcohol septal ablation one week before was presented after an out of hospital cardiac arrest in the setting of an anterior wall ST-elevation myocardial infarction. Immediate coronary angiography showed an unidentified foreign object within the left anterior descending coronary artery (LAD), later identified as the cover of a balloon that had been unintentionally inserted and abandoned within the LAD during the alcohol septum ablation one week earlier. Intracoronary imaging confirmed the presence of endothelial damage and thrombus formation within the LAD explaining acute myocardial infarction.

ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks.

can significantly reduce the DNN computation and storage by decreasing the bitwidth of network encodings. However, without arduous manual effort, this deep quantization can lead to significant accuracy loss, leaving it in a position of questionable utility. We propose a systematic approach to tackle this problem, by automating the process of discovering the bitwidths through an end-to-end deep reinforcement learning framework (ReLeQ).