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Abstract Ice air jet technology is one non-destructive, residue-free and environmentally friendly machining process. It is an efficient method to form ice particles by atomizing water droplets in ultra-low temperature environment. The freezing characteristics of water droplets in cryogenic gas and liquid nitrogen environment are visually analyzed, and the effects of droplet volume, ambient temperature are also studied. The results show that when water droplets freeze in a cryogenic gas environment, four distinct stages are observed, namely pre-cooling stage, recalescence stage, solidification stage, and deep cooling stage. However, when water droplets freeze in liquid nitrogen, the recalescence stage cannot be observed. For a 5 µl water droplet, it takes 68 s for water droplets to freeze into ice particles at − 20.36 °C, while it takes only 1.7 s in liquid nitrogen. During the freezing process, the water droplets form an ice shell outside and freeze inwardly. Ice particles may break up due to differences in solubility and density. With the increase of volume the time spent on pre-cooling stage and freezing stage both increases. For the large latent heat of water phase transformation, the solidification stage time is greatly affected by the volume of water droplets. When the ambient temperature drops from − 10.67 °C to − 24.68 °C, the freezing time of 5 µl water droplets decreases by 45.5%, indicating that the ambient temperature has a great influence on the freezing time. The results of the study can significantly contribute to the development of ice air jet technology.

This paper presents a new analytical solution for assessing the longitudinal deformation of shield tunnel associated with overcrossing tunnelling in consideration of circumferential joints. A simplified longitudinal beam-spring model (SLBSM) is established to model the longitudinal behaviours of shield tunnel, which can consider the opening and dislocation between segmental rings simultaneously. Then, the existing tunnel is treated as the SLBSM resting on the elastic foundation. The state equations including tunnel displacements and internal forces are constructed to solve the discontinuous deformation of circumferential joint-segmental ring. The feasibility of the proposed solution is verified through three well-documented cases. The predictions from the proposed method are also compared with other analytical methods. It is found that the proposed method can well capture the deformation of tunnel segmental rings and joints, where the rigid displacement mainly occurs in the segmental rings while the rotation and dislocation occur in the circumferential joints. Some dominant parameters are also analysed to explore the effects on existing tunnel deformation, including the rotation stiffness and shearing stiffness of joints, the skew angle and the clearance between new and old tunnels.

Major Depressive Disorder (MDD) - can be evaluated by advanced neurocomputing and traditional machine learning techniques. This study aims to develop an automatic system based on a Brain-Computer Interface (BCI) to classify and score depressive patients by specific frequency bands and electrodes. In this study, two Residual Neural Networks (ResNets) based on electroencephalogram (EEG) monitoring are presented for classifying depression (classifier) and for scoring depressive severity (regression). Significant frequency bands and specific brain regions are selected to improve the performance of the ResNets. The algorithm, which is estimated by 10-fold cross-validation, attained an average accuracy rate ranging from 0.371 to 0.571 and achieved average Root-Mean-Square Error (RMSE) from 7.25 to 8.41. After using the beta frequency band and 16 specific EEG channels, we obtained the best-classifying accuracy at 0.871 and the smallest RMSE at 2.80. It was discovered that signals extracted from the beta band are more distinctive in depression classification, and these selected channels tend to perform better on scoring depressive severity. Our study also uncovered the different brain architectural connections by relying on phase coherence analysis. Increased delta deactivation accompanied by strong beta activation is the main feature of depression when the depression symptom is becoming more severe. We can therefore conclude that the model developed here is acceptable for classifying depression and for scoring depressive severity. Our model can offer physicians a model that consists of topological dependency, quantified semantic depressive symptoms and clinical features by using EEG signals. These selected brain regions and significant beta frequency bands can improve the performance of the BCI system for detecting depression and scoring depressive severity.

Although dimming the light in tunnels brings salient benefits to energy saving, the effects of dimming-induced luminance changes on driving safety have been rarely explored. Adopting the visual performance experiment, the present study investigated the impacts of the dimming-induced luminance change rate (V) on the safety of driver’s perception, judgment, and operation in the threshold zone of the tunnel under different seasons and weather conditions. The results show that the reaction times (RTs), pupil area change rate (vp), and blink frequency (fb), increased with the increase of V. When the luminance before the beginning of dimming (L) was higher, drivers reacted faster and stood a lower level of the mental load and fatigue. Compared with decreasing the luminance through dimming, when increasing the luminance through dimming, the present study found that each of the visual performance indices was about 10% lower, and the changes with V became smaller. Based on the safety thresholds of RT, vp, and fb, the present study obtained the thresholds of V which can meet the safety requirements of driver’s perception, judgment, and operation. Finally, a theoretical model between the thresholds of V and L was developed, and this model will shed light on the control of V in the threshold zone of the tunnel under different seasons and weather conditions.

In this paper, we propose a Fuzzy Window with the Gaussian Processed Label (FW-GPL) method to mitigate the overlap problem in the neighboring ordinal category when scoring images. Many published conventional methods treat this challenge as a traditional regression problem and make a strong assumption that each ordinal category owns an adequate intrinsic rank to outline its distribution. Our FW-GPL method aims to refine the ordinal label pattern by using two novel techniques: (1) assembling fuzzy logic to the fully connected layer of convolution neural networks and (2) transforming the ordinal labels with a Gaussian process. Specifically, it incorporates a heuristic fuzzy logic from the ordinal characteristic and simultaneously plugs in ordinal distribution shapes that penalize the difference between the targeted label and its neighbors to ensure a concentrated regional distribution. Accordingly, the function of these proposed windows is leveraged to minimize the influence of majority classes that mislead the prediction of minority samples. Our model is specifically designed to carefully avoid partially missing continuous facial-age segments. It can perform competitively when using the whole continuous facial-age dataset. Extensive experimental results on three facial-aging datasets and one ambiguous medical dataset demonstrate that our FW-GPL can achieve compelling performance results compared to the State-Of-The-Art (SOTA).

BackgroundMicroneedling is a promising method for the treatment of acne scars, while the effect of microneedling combined with platelet-rich plasma (PRP) remains unknown. We performed a meta-analysis of controlled studies to compare the efficacy and safety of microneedling treatment with and without additional PRP in patients with acne scars.MethodsRandomized and non-randomized controlled studies were identified by search of Medline, Embase, and Cochrane's Library databases. Results were pooled with a random-effects model, incorporating the possible heterogeneity.ResultsFour randomized and 10 split-face non-randomized controlled studies with 472 patients were included. Compared to microneedling therapy without PRP, combined treatment with microneedling and PRP was associated with increased odds of clinical improvement of >50% in Goodman's qualitative scale [GQS: odds ratio (OR): 2.97, 95% confidence interval (CI): 1.96–4.51, p < 0.001; I2 = 0%], and a significantly improved mean GQS score (mean difference: −0.32, 95% CI: −0.44 to −0.20, p < 0.001; I2 = 0%). Combined treatment was associated with a higher patient satisfying rate (OR: 4.15, 95% CI: 2.13 to 8.09, p < 0.001; I2 = 53%), while the incidence of severe adverse events such as severe erythema (OR: 1.59, 95% CI:.73 to 3.46, P = 0.24; I2 = 0%) and severe edema (OR: 1.14, 95% CI: 0.47 to 2.76, P = 0.77; I2 = 0%) were not significantly different.ConclusionsCombined treatment with microneedling with PRP is more effective than microneedling without PRP for patients with acne scars.

Radial jet drilling (RJD) technology has been proved to be an economical and efficient stimulation technology for oil and gas, geothermal, hydrate, etc. but conventional RJD technology adopts pure water jet to break rock and form laterals, which has low rock breaking efficiency and is unable to effectively break hard rock such as shale. Swirling abrasive jet is proposed to promote the development of RJD. Here, the characteristics of the flow field of the swirling abrasive jet nozzle and the influence of the key impeller parameters are studied by numerical simulation. The distribution and development of axial velocity, tangential velocity, and radial velocity of water and abrasive are analyzed. The results show that the swirling abrasive jet has no constant velocity core, has stronger diffusivity, and can form a larger impact area than the direct jet. Abrasive particles and water can acquire large tangential and radial velocity which can break rock under the action of shear and tensile stress efficiently. With the increase of the spinning angle, the axial velocity of the fluid decreases, and the tangential velocity increases gradually. With the increase of blade thickness, the axial velocity decreases, and the tangential velocity increases. With the increase of the number of blades, the axial velocity decreases, and the tangential velocity increases. The spinning direction almost has no effect on the flow field. Therefore, the spinning angle is recommended to be no less than 270°, blade thickness is 2.5 mm, and number of blades are 3. The research results provide theoretical guidance for the structural design of swirling abrasive jet nozzles.

BackgroundDengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible.MethodsWe used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population.FindingsNaïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggest that this supplemental transmission route could result in larger outbreaks which peak sooner.InterpretationThe potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes.FundingThis study was funded by grants from the National Health Research Institutes, Taiwan (04D2-MMMOST02), the Human Frontier Science Program (RGP0033/2021), the National Institutes of Health (1R01AI143698-01A1, R01AI151004 and DP2AI152071) and the Ministry of Science and Technology, Taiwan (MOST104-2321-B-400-016).

This study is to examine changes of functional connectivity in patients with depressive disorder using synchronous brain activity. Event-related potentials were acquired during a visual oddball task in 14 patients with depressive disorder and 19 healthy controls. Electroencephalogram recordings were analyzed using event-related phase coherence to obtain the functional network. Alteration of the phase synchronization index (PSI) of the functional network was investigated. Patients with depression showed a decreased number of significant electrode pairs in delta phase synchronization, and an increased number of significant electrode pairs in theta, alpha, and beta phase synchronization, compared with controls. Patients with depression showed lower target-dependent PSI increment in the frontal-parietal/temporal/occipital electrode pairs in delta-phase synchronization than healthy participants. However, patients with depression showed higher target-dependent PSI increments in theta band in the prefrontal/frontal and frontal-temporal electrode pairs, higher PSI increments in alpha band in the prefrontal pairs, and higher increments of beta PSI in the central and right frontal-parietal pairs than controls. It implied that the decrease in delta PSI activity in major depression may indicate impairment of the connection between the frontal and parietal/temporal/occipital regions. The increase in theta, alpha, and beta PSI in the frontal/prefrontal sites may reflect the compensatory mechanism to maintain normal cognitive performance. These findings may provide a foundation for a new approach to assess the effectiveness of therapeutic strategies for depression.

In this study, a previously known high-affinity silica binding protein (SB) was genetically engineered to fuse with an integrin-binding peptide (RGD) to create a recombinant protein (SB-RGD). SB-RGD was successfully expressed in Escherichia coli and purified using silica beads through a simple and fast centrifugation method. A further functionality assay showed that SB-RGD bound to the silica surface with an extremely high affinity that required 2 M MgCl2 for elution. Through a single-step incubation, the purified SB-RGD proteins were noncovalently coated onto an electrospun silica nanofiber (SNF) substrate to fabricate the SNF-SB-RGD substrate. SNF-SB-RGD was characterized by a combination of scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and immunostaining fluorescence microscopy. As PC12 cells were seeded onto the SNF-SB-RGD surface, significantly higher cell viability and longer neurite extensions were observed when compared to those on the control surfaces. These results indicated that SB-RGD could serve as a noncovalent coating biologic to support and promote neuron growth and differentiation on silica-based substrates for neuronal tissue engineering. It also provides proof of concept for the possibility to genetically engineer protein-based signaling molecules to noncovalently modify silica-based substrates as bioinspired material.

In this study, we first synthesized a slow-degrading silica nanofiber (SNF2) through an electrospun solution with an optimized tetraethyl orthosilicate (TEOS) to polyvinyl pyrrolidone (PVP) ratio. Then, laminin-modified SNF2, namely SNF2-AP-S-L, was obtained through a series of chemical reactions to attach the extracellular matrix protein, laminin, to its surface. The SNF2-AP-S-L substrate was characterized by a combination of scanning electron microscopy (SEM), Fourier transform–infrared (FTIR) spectroscopy, nitrogen adsorption/desorption isotherms, and contact angle measurements. The results of further functional assays show that this substrate is a biocompatible, bioactive and biodegradable scaffold with good structural integrity that persisted beyond 18 days. Moreover, a synergistic effect of sustained structure support and prolonged biochemical stimulation for cell differentiation on SNF2-AP-S-L was found when neuron-like PC12 cells were seeded onto its surface. Specifically, neurite extensions on the covalently modified SNF2-AP-S-L were significantly longer than those observed on unmodified SNF and SNF subjected to physical adsorption of laminin. Together, these results indicate that the SNF2-AP-S-L substrate prepared in this study is a promising 3D biocompatible substrate capable of sustaining longer neuronal growth for tissue-engineering applications.