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Background Generally, brain–computer interfaces (BCIs) require calibration before usage to ensure efficient performance. Therefore, each BCI user has to attend a certain number of calibration sessions to be able to use the system. However, such calibration requirements may be difficult to fulfill especially for patients with disabilities. In this paper, we introduce a probabilistic transfer learning approach to reduce the calibration requirements of our EEG–fTCD hybrid BCI designed using motor imagery (MI) and flickering mental rotation (MR)/word generation (WG) paradigms. The proposed approach identifies the top similar datasets from previous BCI users to a small training dataset collected from a current BCI user and uses these datasets to augment the training data of the current BCI user. To achieve such an aim, EEG and fTCD feature vectors of each trial were projected into scalar scores using support vector machines. EEG and fTCD class conditional distributions were learnt separately using the scores of each class. Bhattacharyya distance was used to identify similarities between class conditional distributions obtained using training trials of the current BCI user and those obtained using trials of previous users. Results Experimental results showed that the performance obtained using the proposed transfer learning approach outperforms the performance obtained without transfer learning for both MI and flickering MR/WG paradigms. In particular, it was found that the calibration requirements can be reduced by at least 60.43% for the MI paradigm, while at most a reduction of 17.31% can be achieved for the MR/WG paradigm. Conclusions Data collected using the MI paradigm show better generalization across subjects.

•We investigated subcortical arousal systems during transient shifts in attention.•Massive fMRI datasets covering four sensory modalities were analyzed.•We observed early transient signals in midbrain reticular formation and central thalamus.•Pons, hypothalamus, basal forebrain and basal ganglia show less consistent activity.•Cortical and subcortical modality-specific activity was also observed. Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms. We analyzed massive publicly available fMRI datasets collected while 1561 participants performed visual, auditory, tactile, and taste perception tasks. Our analyses revealed a shared circuit of subcortical arousal systems exhibiting early transient increases in activity in midbrain reticular formation and central thalamus across perceptual modalities, as well as less consistent increases in pons, hypothalamus, basal forebrain, and basal ganglia. Identifying these networks is critical for understanding mechanisms of normal attention and consciousness and may help facilitate subcortical targeting for therapeutic neuromodulation.

Many techniques are used for the treatment of wastewater, including physical, chemical, biological, physiochemical, and biophysical methods. Advanced oxidation processes (AOPs), a chemical approach, are a key procedure for wastewater treatment. AOPs are applied to nonbiodegradable effluents, using less energy and chemicals while producing a completely biodegradable intermediate sample that can then undergo additional treatment to completely remove all organic matter. The AOPs can be chemical, photochemical, sonochemical, or electrochemical. Photochemical reactions accelerate the breaking down of organic pollutants using a photocatalyst that absorbs light and serves as a catalyst for chemical operations. There are a lot of photocatalysts that are used in water purification, such as TiO2, ZnO, ZrO2, CdS, CeO2, ZnS, FeO, Fe2O3, SnO2, and WO3, and most of them are at the nanoscale. This article analyzes and covers the main aspects of using Fe2O3 nanoparticles for the purification of water and wastewater. It covers the application of Fe2O3 nanoparticles in the treatment of water and wastewater and the mechanisms of solar photodegradation of iron oxide (Fe2O3) photocatalysts. It shows the Fe2O3 nanoparticle synthesis methods and introduces the advantages and disadvantages of each technique. The review makes comparisons between the photocatalytic membrane reactor and the suspended system, as well as upcoming challenges and opportunities related to using Fe2O3 nanoparticles in these processes. This provides researchers with a different perspective on the photocatalysis outcomes that might be attained when the Fe2O3 photocatalysts are incorporated into various treatment systems.

Brain-computer interfaces (BCIs) provide alternative means of communication and control for individuals with severe motor or speech impairments. Multimodal BCIs have been introduced recently to enhance the performance of BCIs utilizing single modality. In this paper, we aim to advance the state of the art in multimodal BCIs combining Electroencephalography (EEG) and functional transcranial Doppler ultrasound (fTCD) by introducing advanced analysis approaches that enhance system performance. Our EEG-fTCD BCIs employ two distinct paradigms to infer user intent: motor imagery (MI) and flickering mental rotation (MR)/word generation (WG) paradigms. In the MI paradigm, we introduce the use of Filter Bank Common Spatial Pattern (FBCSP) for the first time in an EEG-fTCD BCI, while in the flickering MR/WG paradigm, we extend FBCSP application to non-motor imagery tasks. Additionally, we extract previously unexplored time-series features from the envelope of fTCD signals, leveraging richer information from cerebral blood flow dynamics. Furthermore, we employ a Bayesian fusion framework that allows EEG and fTCD to contribute unequally to decision-making. The multimodal EEG-fTCD system achieved high classification accuracies across tasks in both paradigms. In the MI paradigm, accuracies of 94.53%, 94.9%, and 96.29% were achieved for left arm MI vs. baseline, right arm MI vs. baseline, and right arm MI vs. left arm MI, respectively – outperforming EEG-only accuracy by 3.87%, 3.80%, and 5.81%, respectively. In the MR/WG paradigm, the system achieved 95.27%, 85.93%, and 96.97% for MR vs. baseline, WG vs. baseline, and MR vs. WG, respectively, showing accuracy improvements of 2.28%, 4.95%, and 1.56%, respectively compared to EEG-only results. Overall, the proposed analysis approach improved classification accuracy for 5 out of 6 binary classification problems within the MI and MR/WG paradigms, with gains ranging from 0.64% to 9% compared to our previous EEG-fTCD studies. Additionally, our results demonstrate that EEG-fTCD BCIs with the proposed analysis techniques outperform multimodal EEG-fNIRS BCIs in both accuracy and speed, improving classification performance by 2.7% to 24.7% and reducing trial durations by 2–38 seconds. These findings highlight the potential of the proposed approach to advance assistive technologies and improve patient quality of life.

Background/Objectives: Clarithromycin (CLA) is a widely used antibiotic effective against a variety of bacterial strains, making it a common treatment for respiratory, skin, and soft tissue infections. Moreover, extensive studies have confirmed the anticancer activity of CLA against different cancers, particularly when combined with conventional therapies. This study investigates the potential anticancer and antibacterial activities of developed CLA-loaded bovine serum albumin nanoparticles (CLA-BSA NPs), designed with optimized physicochemical properties to enhance drug delivery. Methods: The CLA-BSA NPs were synthesized using the desolvation method, followed by drug loading. Characterization techniques, including Dynamic Light Scattering (DLS), Fourier-Transform Infrared (FTIR) Spectroscopy, X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Thermogravimetric Analysis (TGA). Results: The results confirmed that CLA interacts with BSA NPs through van der Waals forces. The performance of drug–nanocarrier interaction was further assessed through in vitro drug release studies. The release studies demonstrated that CLA had a robust release profile in reductive media, with a cumulative release of 50.9% in acetate buffer (pH 5.0) supplemented with 10 mM glutathione (GSH). Further biological activity assays were also conducted, including cell viability assays (MTT) and antibacterial activity tests. CLA-BSA NPs demonstrated anticancer activity against the lung cancer (A549) cell line, while showing minimal cytotoxicity on normal human dermal fibroblast (HDF) cells. The antibacterial activity was assessed against Streptococcus pyogenes, Bacillus cereus, and Staphylococcus aureus. Among the tested strains, Bacillus cereus exhibited the highest sensitivity, with a minimum inhibitory concentration (MIC) of 0.032 µg/mL, compared to 0.12 µg/mL for Staphylococcus aureus and >32 µg/mL for Streptococcus pyogenes. Conclusions: In conclusion, these findings highlight CLA-BSA NPs as a promising drug delivery system that enhances the anticancer and antibacterial efficacy of CLA.

During visual conscious perception, the earliest responses linked to signal detection are little known. The current study aims to reveal the cortical neural activity changes in the earliest stages of conscious perception using recordings from intracranial electrodes. Epilepsy patients (N=158) were recruited from a multi-center collaboration and completed a visual word recall task. Broadband gamma activity (40–115Hz) was extracted with a band-pass filter and gamma power was calculated across subjects on a common brain surface. Our results show early gamma power increases within 0-50ms after stimulus onset in bilateral visual processing cortex, right frontal cortex (frontal eye fields, ventral medial/frontopolar, orbital frontal) and bilateral medial temporal cortex regardless of whether the word was later recalled. At the same early times, decreases were seen in the left rostral middle frontal gyrus. At later times after stimulus onset, gamma power changes developed in multiple cortical regions. These included sustained changes in visual and other association cortical networks, and transient decreases in the default mode network most prominently at 300–650ms. In agreement with prior work in this verbal memory task, we also saw greater increases in visual and medial temporal regions as well as prominent later (> 300ms) increases in left hemisphere language areas for recalled versus not recalled stimuli. These results suggest an early signal detection network in the frontal, medial temporal, and visual cortex is engaged at the earliest stages of conscious visual perception.

Absence seizures are brief episodes of impaired consciousness, behavioral arrest, and unresponsiveness, with yet-unknown neuronal mechanisms. Here we report that an awake female rat model recapitulates the behavioral, electroencephalographic, and cortical functional magnetic resonance imaging characteristics of human absence seizures. Neuronally, seizures feature overall decreased but rhythmic firing of neurons in cortex and thalamus. Individual cortical and thalamic neurons express one of four distinct patterns of seizure-associated activity, one of which causes a transient initial peak in overall firing at seizure onset, and another which drives sustained decreases in overall firing. 40–60 s before seizure onset there begins a decline in low frequency electroencephalographic activity, neuronal firing, and behavior, but an increase in higher frequency electroencephalography and rhythmicity of neuronal firing. Our findings demonstrate that prolonged brain state changes precede consciousness-impairing seizures, and that during seizures distinct functional groups of cortical and thalamic neurons produce an overall transient firing increase followed by a sustained firing decrease, and increased rhythmicity. Absence seizures impair consciousness by an unknown neuronal mechanism. Here, the authors find that a rat absence seizure model’s behavior and hemodynamics recapitulate previously reported characteristics of human absence seizures, and uncover four distinct patterns of neuronal activity in cortex and thalamus during consciousness-impairing seizures.

Polyethersulfone (PES) membranes are essential in separation processes; however, their inherent hydrophobicity can limit their effectiveness in water-intensive applications. This study aims to enhance PES membranes by modifying them with a NiFe2O4–nanoclay composite nanoparticle to improve both their hydrophilicity and photocatalytic potential as a photocatalytic membrane. The nanoparticles were synthesized using the sol–gel auto-combustion method and incorporated into PES membranes through mixed-matrix embedding (1 wt% and 3 wt%) and surface coating. X-ray diffraction confirmed the cubic spinel structure of the composite nanoparticles, which followed the second order kinetic reaction during the photodegradation–adsorption of crystal violet. The mixed-matrix membranes displayed a remarkable 170% increase in water flux and a 25% improvement in mechanical strength, accompanied by a slight decrease in contact angle at 1 wt% of nanoparticle loading. In contrast, the surface-coated membranes demonstrated a significant reduction in contact angle to 18°, indicating a highly hydrophilic surface and increased roughness. All membranes achieved high dye removal rates of 98–99%, but only the coated membrane system exhibited approximately 50% photocatalytic degradation, following mixed kinetics. These results highlight the critical importance of surface modification in advancing PES membranes, as it significantly reduces fouling and enhances water–material interaction qualities essential for future filtration and photocatalytic applications. Exploring hybrid strategies that combine both embedding and coating approaches may yield even greater synergies in membrane functionality.

•We used human intracranial recordings to investigate auditory conscious perception.•Significant activity for non-perceived sounds was limited to early auditory regions.•Perceived sounds triggered early increased activity in frontal eye fields and thalamus.•A wave of activity followed in frontoparietal association cortex for perceived sounds. Although recent work has made headway in understanding the neural temporospatial dynamics of conscious perception, much of that work has focused on visual paradigms. To determine whether there are shared mechanisms for perceptual consciousness across sensory modalities, here we test within the auditory domain. Participants completed an auditory threshold task while undergoing intracranial electroencephalography. Recordings from >2,800 grey matter electrodes were analyzed for broadband gamma power (a range which reflects local neural activity). For perceived trials, we find nearly simultaneous activity in early auditory regions, the right caudal middle frontal gyrus, and the non-auditory thalamus; followed by a wave of activity that sweeps through auditory association regions into parietal and frontal cortices. For not perceived trials, significant activity is restricted to early auditory regions. These findings show the cortical and subcortical networks involved in auditory perception are similar to those observed with vision, suggesting shared mechanisms for conscious perception.

Polyvinylidene fluoride (PVDF) membranes have become a favored choice for membrane filtration because of their outstanding mechanical characteristics, chemical resistance, thermal stability, and ease of handling. Nevertheless, the hydrophobic nature of PVDF membranes can result in fouling, which diminishes their efficiency over time. This study explores the impact of ZnO-Nanoclay on the properties and performance of mixed matrix membranes made from polyvinylidene fluoride (PVDF) at different loading percentages (0, 1, and 3 wt%). The ZnO-Nanoclay nanoparticles were synthesized using environmentally friendly methods, characterized, and blended into PVDF matrices via a solution-casting technique, resulting in a series of membranes. The synthesized nanoparticles were analyzed using Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). The resulting mixed-matrix membranes underwent comprehensive analyses to assess their structure and surface properties, employing SEM, XRD, Atomic Force Microscopy (AFM), and contact-angle measurements. Furthermore, tensile, antibacterial, and barrier properties were evaluated. Integrating ZnO-Nanoclay into PVDF membranes greatly improves antifouling properties, achieving inhibition rates of 99.92% at a clay-loading percentage of 3 wt% and increasing water-flux rates by 16% compared to pure PVDF membranes at 1 wt%. In addition, ZnO-Nanoclay nanoparticles significantly boost the mechanical properties of PVDF membranes, enhancing maximum strength by 500% at 3 wt% loading. This study examines the interplay between the structure, properties, and performance of mixed-matrix membranes by comparing different PVDF membranes that were mixed with different nanoclay composites, providing significant insights into improving these membranes through the incorporation of nanoclay composites to enhance their overall properties and effectiveness.