Abstract In computer vision, zero-shot image restoration—a technique enabling degraded image restoration without large-scale paired training data—has emerged as a pivotal technique for scenarios where data is limited or paired training data is challenging to obtain. However, existing methods face two key limitations: data consistency preservation remains challenging for out-of-domain data, and degradation process alignment is difficult when the degradation mechanism is not mathematically predetermined. To address these issues, this paper presents a novel zero-shot image restoration method (FIR-SDE). Traditional generation-oriented diffusion models (designed for image creation) are replaced with restoration-oriented models (specialized for degradation repair), expanding the range of effectively restorable images. To mitigate the noise offset (discrepancies between real and model-simulated degradation) and to enhance the alignment, a multi-step optimization strategy is employed, which evaluates the distance between real and simulated degraded images via frequency domain distribution. Experiments were conducted on two image restoration tasks (image deraining and inpainting) using three public datasets (AFHQ-dog, CelebA, and FFHQ), with Gaussian blur and motion blur superimposed as noise offsets. Results demonstrate that FIR-SDE method outperforms competitive methods in restoration quality and noise resistance. By eliminating data space constraints and exhibiting robustness against noise offsets, FIR-SDE offers a more flexible and efficient solution to broaden the practical applicability of zero-shot image restoration.
Electronic computers. Computer science, Information technology
Che-Sheng Chu, Yen-Yue Lin, Cathy Chia-Yu Huang
et al.
Background: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation for treatment-resistant obsessive compulsive disorder (OCD). We aim to compare the treatment outcomes of a newly developed dual-site cathodal tDCS method over the orbitofrontal cortex (OFC) and pre-supplementary motor area (pre-SMA) and two previously reported montages (cerebellum-OFC and pre-SMA) in patients with treatment-resistant OCD. Methods: Eighteen OCD patients were randomly assigned to receive twice-daily 2 mA/20 min sessions for 10 consecutive weekdays, with the active cathode placed on the cerebellum-OFC, bilateral pre-SMA, or OFC-pre-SMA tDCS. The primary outcome was the change in the Yale–Brown Obsessive Compulsive Scale (Y-BOCS). The resting electroencephalogram (EEG) was recorded to obtain the default mode network (DMN) via low-resolution electromagnetic tomography. Each patient received one-week and one-month follow-ups after two weeks of stimulation. Results: At the end of the stimulation, the Y-BOCS scores in the cerebellum-OFC, pre-SMA, and OFC-pre-SMA tDCS groups (n = 6 in each group) were decreased by 14.15 ± 13.31, 7.4 ± 9.59, and 20.75 ± 8.70%, respectively, but no significant differences were found among the groups. In the OFC-pre-SMA tDCS group, OC symptoms significantly decreased by a mean of −20.75% immediately after the 20th tDCS session, and the improvement remained at 1 week and 1 month after tDCS. EEG source functional connectivity analyses revealed increased functional connectivity within the frontal network after OFC-pre-SMA tDCS, whereas decreased functional connectivity within the DMN was observed after cerebellum-OFC tDCS. Conclusions: Dual-site cathodal tDCS over the OFC and pre-SMA might be considered a potential montage to treat patients with treatment-resistant OCD. Future studies using randomized sham-controlled designs are needed.
Levent Gülüm, Süheyla Esin Köksal, Emrah Güler
et al.
The objective of this study was to evaluate the physicochemical, bioactive, and technological properties of pasta made from durum wheat semolina that was partially replaced with Acorn flour at levels of 10%, 20%, and 30%. The incorporation of Acorn flour had a substantial impact on the nutritional composition of the pasta, resulting in increases in total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity in comparison with the control sample. The highest values for TPC and TFC were found in the samples containing 20% and 30% Acorn flour (p<0.05), demonstrating the functional potential of this formulation. However, an increase in the quantity of Acorn flour used in the pasta production process resulted in a noticeable darkening of the pasta's colour. This observation is consistent with the findings of previous research conducted on the use of non-traditional flours. While the increased amounts of Acorn flour resulted in enhanced nutritional and antioxidant profiles, the darker appearance and alterations in texture may have implications for sensory and visual acceptability. The present findings are corroborated by extant literature, which demonstrates that functional flours such as buckwheat, chickpea, lentil, chia, and sorghum have exhibited analogous trends in enhancing bioactive compounds and altering technological properties. Incorporation of Acorn flour at levels ranging from 10% to 20% optimises the health benefits of pasta while maintaining its desirable sensory and structural characteristics. Presented research contributes to the valorization of non-wood forest product (NWFP) resources and the development of innovative functional pasta products using sustainable ingredients.
Using look-alike avatars may enhance the likeability and realism of avatars in 3D virtual learning environments. This paper explores perception of the features of the look-alike avatar representations of an instructor in virtual environments in two studies. In a pilot study, an instructor was represented as a look-alike, stick, and video avatar, allowing us to investigate students’ perceptions of teaching effectiveness in virtual and augmented reality environments. The main study seeks to determine the influence of three specific features of a look-alike avatar (head shape, texture fidelity and head orientation) on perception of likeability and visual realism, especially when judged by other people. Two textured look-alike avatars were generated using: (i) three-dimensional (3D) stereophotogrammetry; and (ii) 3D face reconstruction from a single full-face image. Participants compared three different head orientations (0°, 45°, 90°) of the look-alike avatars’ textured heads to their corresponding head silhouettes, to emphasize the differences in head shapes. Results suggest that participants prefer geometrically-accurate photorealistic avatars of the instructor due to the accuracy of the head shape and texture fidelity. In line with studies on face recognition, participants ranked the likeability and realism of the look-alike avatars similarly regardless of the head orientation. We discuss the implications of these findings for 3D virtual learning environments.
The study of boundary layer flow (BLF) with heat-mass transfer of binary chemical processes and nanofluids (NF) over a wedge is essential for improving heat transfer and reaction kinetics in applications including processing of material technologies, chemical reactors, and energy-efficient cooling mechanisms. This paper examines the entropy optimized BLF of silver Ag− water based nanofluid with binary chemical species over a wedge surface. The Tiwari-Das model is executed in this model which account the load of Ag− nanomaterials. The flow of NF over a moving wedge subject to favorable and adverse pressure differential is addressed by Naiver-Stokes equation. This model accounts the homogeneous heat reaction, viscous dissipation, joule heating and thermal radiations. The dimensionless equations for flow, for heat, and concentration are formulated and solved numerically using the fourth ordered Rung-Kutta approach. The findings suggest that fluid concentration is lowered with a rise in Schmidt number and homogenous chemical reaction. Thermal distribution improve with heterogonous reaction, magnetic parameter and deteriorate with wedge parameter. The skin friction rises from 25.277 % to 26.455 % with a material load of 3 % and magnetic parameter. The Nusselt decline with a radiative parameter from 10.984 % to 2.9748 % when particle load of 3 % is accounted.
Pavlos Tafidis, Mehdi Gholamnia, Payam Sajadi
et al.
Abstract Air pollution is a significant and pressing environmental and public health concern in urban areas, primarily driven by road transport. By gaining a deeper understanding of how traffic dynamics influence air pollution, policymakers and experts can design targeted interventions to tackle these critical issues. In order to analyse this relationship, a series of regression algorithms were developed utilizing the Google Project Air View (GPAV) and Dublin City’s SCATS data, taking into account various spatiotemporal characteristics such as distance and weather. The analysis showed that Gaussian Process Regression (GPR) mostly outperformed Support Vector Regression (SVR) for air quality prediction, emphasizing its suitability and the importance of considering spatial variability in modelling. The model describes the data best for particulate matter (PM2.5) emissions, with R-squared (R2) values ranging from 0.40 to 0.55 at specific distances from the centre of the study area based on the GPR model. The visualization of pollutant concentrations in the study area also revealed an association with the distance between intersections. While the anticipated direct correlation between vehicular traffic and air pollution was not as pronounced, it underscores the complexity of urban emissions and the multitude of factors influencing air quality. This revelation highlights the need for a multifaceted approach to policymaking, ensuring that interventions address a broader spectrum of emission sources beyond just traffic. This study advances the current knowledge on the dynamic relationship between urban traffic and air pollution, and its findings could provide theoretical support for traffic planning and traffic control applicable to urban centres globally.
Transportation engineering, Transportation and communications
As a condiment with extensive nutritional value, chili is easy to be contaminated by Aspergillus flavus (A. flavus) during field, transportation, and storage. This study aimed to solve the contamination of dried red chili caused by A. flavus by inhibiting the growth of A. flavus and detoxifying aflatoxin B1 (AFB1). In this study, Bacillus subtilis E11 (B. subtilis) screened from 63 candidate antagonistic bacteria exhibited the strongest antifungal ability, which could not only inhibit 64.27% of A. flavus but could also remove 81.34% of AFB1 at 24 h. Notably, scanning electron microscopy (SEM) showed that B. subtilis E11 cells could resist a higher concentration of AFB1, and the fermentation supernatant of B. subtilis E11 could deform the mycelia of A. flavus. After 10 days of coculture with B. subtilis E11 on dried red chili inoculated with A. flavus, the mycelia of A. flavus were almost completely inhibited, and the yield of AFB1 was significantly reduced. Our study first concentrated on the use of B. subtilis as a biocontrol agent for dried red chili, which could not only enrich the resources of microbial strains for controlling A. flavus but also could provide theoretical guidance to prolong the shelf life of dried red chili.
Methylene blue (MB)- or Curcumin (Cur)-based photodynamic therapy (PDT) has been used as an adjunctive treatment for periodontitis. Its actual clinical efficacy is still in question because the lack of oxygen in a deep periodontal pocket might reduce the PDT efficacy. We aim to investigate the effect of oxygen on PDT efficacy and to examine if the addition of hydrogen peroxide (HP) could improve PDT performance anaerobically. To this end, we cultured 48 h saliva-derived multi-species biofilms and treated the biofilms with 25 µM MB or 40 µM Cur, HP (0.001%, 0.01% and 0.1%), light (L-450 nm or L-660 nm), or combinations thereof under ambient air or strictly anaerobic conditions. MB- and Cur-PDTs significantly reduced biofilm viability in air but not under anaerobic conditions. HP at 0.1% significantly enhanced the killing efficacies of both MB- and Cur-PDTs anaerobically. The killing efficacy of Cur-PDT combined with 0.1% HP was higher anaerobically than in air. However, this was not the case for MB-PDT combined with 0.1% HP. In conclusion, this study demonstrated that the biofilm killing efficacies of MB- and Cur-PDTs diminished when there was no oxygen. HP at 0.1% can enhance the efficacy of PDT performed anaerobically, but the level of enhancement is photosensitizer-dependent.
The residues of progestins in milk are significant risk factors for teenage acne and may cause hormone-dependent cancers in consumers, so the determination of these residues in milk is very important. However, an immunoassay or immunoassay-like method capable of determining multiple progestins in milk has not been reported so far. The present study, for the first time, synthesized a type of magnetic molecularly imprinted microsphere that was capable of simultaneously recognizing five progestins. At the same time, an enzyme labeled conjugate was synthesized by coupling progesterone 3-(o-carboxymethyl)oxime with streptavidinated horseradish peroxidase. The above two reagents were used to develop a semi-homogeneous method for the simultaneous detection of the residues of the five progestins in milk. During the experiments, biotinylated horseradish peroxidase was used to amplify the signal, so the sensitivity to the five drugs (limits of detection 0.04–0.1 pg/mL) was increased 44–75-fold. In addition, the magnetic molecularly imprinted microsphere could be regenerated four times by using simple elution. Through general comparison of its detection spectrum, sensitivity, simplicity, and reusability, the present method exhibited better performance than the previous immunoassays for the detection of progestins, and so it could be used as a routine tool for the screening of progestins residues in milk.
Suraj Chakravarthi Raja, Won Suk You, Kian Jalaleddini
et al.
Tendon transfer surgery is often used to restore hand grasp function following high median-ulnar nerve palsy. This surgery typically reroutes and sutures the tendon of the extensor carpi radialis longus (ECRL) muscle to all four flexor digitorum profundus (FDP) tendons of the hand, coupling them together. This makes it difficult to grasp irregularly shaped objects. We propose inserting a novel implantable passive device between the FDP tendons to surgically construct a differential mechanism, enabling the fingers to individually adapt to the irregular contours during grasping. These passive implants with no moving parts are fabricated from biocompatible materials. We tested the implants’ ability to create differential flexion between the index and middle fingers when actuated by a single muscle in two human cadaver hands using a computerized closed-loop control paradigm. In these cadaveric models, the implants enabled significantly more differential flexion between the index and middle fingers for a wide range of donor tendon tensions. The implants also redistributed fingertip forces between fingers. When grasping uneven objects, the difference in contact forces between fingers reduced by nearly 23% compared to the current suture-based surgery. These results suggest that self-adaptive grasp is possible in tendon transfers that drive multiple distal flexor tendons.
Mohammad Alkhaleefah, Tan-Hsu Tan, Chuan-Hsun Chang
et al.
Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layers. Moreover, the cross-entropy loss function of the original SegNet has been replaced by the intersection over union (IoU) loss function in order to make the proposed model more robust against noise during the training process. As part of data preprocessing, a histogram equalization technique, called contrast limit adapt histogram equalization (CLAHE), is applied to all datasets to enhance the compressed regions and smooth the distribution of the pixels. Additionally, two image augmentation methods, namely rotation and flipping, are used to increase the amount of training data and to prevent overfitting. The proposed model has been evaluated on two publicly available datasets, specifically INbreast and the curated breast imaging subset of digital database for screening mammography (CBIS-DDSM). The proposed model has also been evaluated using a private dataset obtained from Cheng Hsin General Hospital in Taiwan. The experimental results show that the proposed Connected-SegNets model outperforms the state-of-the-art methods in terms of Dice score and IoU score. The proposed Connected-SegNets produces a maximum Dice score of 96.34% on the INbreast dataset, 92.86% on the CBIS-DDSM dataset, and 92.25% on the private dataset. Furthermore, the experimental results show that the proposed model achieves the highest IoU score of 91.21%, 87.34%, and 83.71% on INbreast, CBIS-DDSM, and the private dataset, respectively.
Monocrystalline barium fluoride (BaF<sub>2</sub>) slab targets were irradiated by focused 46.9-nm laser radiation at various fluence levels above the ablation threshold. Well-developed ablation patterns with sharp edges were studied by AFM (atomic force microscopy). Their inner surfaces were uniformly covered by periodic structures. The spatial period of the ripples depends on the laser fluence. When the sample is rotated by 45°, the orientation of the grating-like structure changes accordingly. Thus, the grating vector of the periodic structure seems to be coupled to the crystallographic planes of the single crystal. This means that the XUV-laser induced ripples reported here differ from LIPSS (laser-induced periodic surface structures) associated with interference phenomena occurring on illuminated surfaces. Therefore, other mechanisms are discussed to explain the formation of the periodic nanostructures reported in this article.
Gonzalo R. Tortella, Amedea B. Seabra, Jorge Padrão
et al.
The COVID-19 pandemic has had a negative impact on education. The restrictions imposed have undoubtedly led to impairment of the psychological well-being of both teachers and students, and of the way they experience interpersonal relationships. As reported previously in the literature, adverse effects such as loneliness, anxiety, and stress have resulted in a decrease in the cognitive performance of school and higher education students. Therefore, the objective of this work is to present a general overview of the reported adverse effects of the COVID-19 pandemic which may potentially influence the learning performance of students. Some neuroscientific findings related to memory and cognition, such as neuroplasticity and long-term potentiation, are also shown. We also discuss the positive effects of the practice of mindfulness, as well as other simple recommendations based on neuroscientific findings such as restful sleep, physical activity, and nutrition, which can act on memory and cognition. Finally, we propose some practical recommendations on how to achieve more effective student learning in the context of the pandemic. The aim of this review is to provide some assistance in this changing and uncertain situation in which we all find ourselves, and we hope that some of the information could serve as a starting point for hypotheses to be tested in educational research and their association with neuroscience.
Neusa R. Adão Martins, Neusa R. Adão Martins, Simon Annaheim
et al.
The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms “fatigue,” “drowsiness,” “vigilance,” or “alertness” in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (Tsk), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.
Marina M. Mennucci, Rodrigo Montes, Alexandre C. Bastos
et al.
This work compares different electrodeposition procedures to produce nickel black coatings as greener and less toxic alternatives to Cr(VI)-based coatings used in different applications. Nickel and nickel-plated brass served as substrates in studies with a Hull cell and polarization curves. After a set of comparative experiments, the best electrodeposition procedure was further studied and optimized. Optimal conditions were found with a bath consisting of 75 g/L NiCl<sub>2</sub>·6H<sub>2</sub>O + 30 g/L NaCl and a current density of 0.143 A dm<sup>−2</sup> applied for 5 min at room temperature. Furthermore, a pre-treatment with 18.5 vol.% of hydrochloric acid in water was found to be necessary to warrant good coating adhesion to the substrate. The black color is attributed to the development of a nanostructured surface that absorbs the incident light. Corrosion testing was performed in 0.5 M NaCl aqueous solution using electrochemical impedance spectroscopy (EIS) and polarization tests.