Split ring hole metamaterial-enhanced pyroelectric detector for efficient multi-narrowband terahertz detection.

Derived from infrared pyroelectric detection, typical terahertz (THz) pyroelectric detectors have low sensitivity at low-frequency THz bands. Based on the high-efficiency absorption of the metamaterial perfect absorber (MPA), a novel split ring hole metamaterial-enhanced pyroelectric detector is proposed to achieve efficient multi-narrowband THz detection. Using high frequency simulation software (HFSS), the dimensional parameters including ring radius, ring width, connection beam width, array period, and thickness, are optimized to enhance efficient multi-narrowband absorption. The as-optimized metamaterial-enhanced detectors are fabricated via micro-nano manufacturing technology. The voltage responsiveness and noise equivalent power of the metamaterial-enhanced detector are tested by THz focused optical path and compared with those of the typical pyroelectric detector and the simulated MPA absorptivity. The results indicate that the metamaterial-enhanced detector has a multi-narrowband detection capability at 0.245 THz, 0.295 THz, and 0.38 THz, which is close to the simulated MPA absorptivity. Compared to the typical pyroelectric detector, the split ring hole metamaterial-enhanced detector can simultaneously achieve thermal absorption, thermal conduction, and pyroelectricity in the same MPA structure, providing faster response speed above 100 Hz chopper frequency and two times higher detection sensitivity at multi-narrowband THz frequencies. This research can be used for THz sensing, absorption filtering, biological macromolecule detection, and other applications.

Compensatory growth of Microcystis aeruginosa after copper stress and the characteristics of algal extracellular organic matter (EOM).

Cyanobacterial blooms can impair drinking water quality due to the concomitant extracellular organic matter (EOM). As copper is often applied as an algicide, cyanobacteria may experience copper stress. However, it remains uncertain whether algal growth compensation occurs and how EOM characteristics change in response to copper stress. This study investigated the changes in growth conditions, photosynthetic capacity, and EOM characteristics of M. aeruginosa under copper stress. In all copper treatments, M. aeruginosa experienced a growth inhibition stage followed by a growth compensation stage. Notably, although chlorophyll-a fluorescence parameters dropped to zero immediately following high-intensity copper stress (0.2 and 0.5 mg/L), they later recovered to levels exceeding those of the control, indicating that photosystem II was not destroyed by copper stress. Copper stress influenced the dissolved organic carbon (DOC) content, polysaccharides, proteins, excitation-emission matrix spectra, hydrophobicity, and molecular weight (MW) distribution of EOM, with the effects varying based on stress intensity and growth stage. Principal component analysis revealed a correlation between the chlorophyll-a fluorescence parameters and EOM characteristics. These results imply that copper may not be an ideal algicide. Further research is needed to explore the dynamic response of EOM characteristics to environmental stress.

TokenCut: Segmenting Objects in Images and Videos With Self-Supervised Transformer and Normalized Cut.

In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With this approach, the image patches that compose an image or video are organised into a fully connected graph, in which the edge between each pair of patches is labeled with a similarity score based on the features learned by the transformer. Detection and segmentation of salient objects can then be formulated as a graph-cut problem and solved using the classical Normalized Cut algorithm. Despite the simplicity of this approach, it achieves state-of-the-art results on several common image and video detection and segmentation tasks. For unsupervised object discovery, this approach outperforms the competing approaches by a margin of 6.1%, 5.7%, and 2.6% when tested with the VOC07, VOC12, and COCO20 K datasets. For the unsupervised saliency detection task in images, this method improves the score for Intersection over Union (IoU) by 4.4%, 5.6% and 5.2%. When tested with the ECSSD, DUTS, and DUT-OMRON datasets. This method also achieves competitive results for unsupervised video object segmentation tasks with the DAVIS, SegTV2, and FBMS datasets.

Numerical Investigation of GaN HEMT Terahertz Detection Model Considering Multiple Scattering Mechanisms.

GaN high-electron-mobility transistor (HEMT) terahertz (THz) detectors have been widely studied and applied in the past few decades. However, there are few reports about the influence of GaN/AlGaN heterostructure material properties on the detection model at present. In this paper, a response voltage model for a GaN HEMT THz detector that considers the carrier scattering in a GaN/AlGaN heterostructure is proposed. The phonon scattering, dislocation scattering, and interface roughness scattering mechanisms are taken into account in the classic THz response voltage model; furthermore, the influence of various material parameters on the response voltage is studied. In a low-temperature region, acoustic scattering plays an important role, and the response voltage drops with an increase in temperature. In a high temperature range, optical phonon scattering is the main scattering mechanism, and the detector operates in a non-resonant detection mode. With an increase in carrier surface density, the response voltage decreases and then increases due to piezoelectric scattering and optical phonon scattering. For dislocation and interface roughness scattering, the response voltage is inversely proportional to the dislocation density and root mean square roughness (RMS) but is positively related to lateral correlation length. Finally, a comparison between our model and the reported models shows that our proposed model is more accurate.

Preoperative individual-target transcranial magnetic stimulation demonstrates an effect comparable to intraoperative direct electrical stimulation in language-eloquent glioma mapping and improves postsurgical outcome: A retrospective fiber-tracking and electromagnetic simulation study.

Background: Efforts to resection of glioma lesions located in brain-eloquent areas must balance the extent of resection (EOR) and functional preservation. Currently, intraoperative direct electrical stimulation (DES) is the gold standard for achieving the maximum EOR while preserving as much functionality as possible. However, intraoperative DES inevitably involves risks of infection and epilepsy. The aim of this study was to verify the reliability of individual-target transcranial magnetic stimulation (IT-TMS) in preoperative mapping relative to DES and evaluate its effectiveness based on postsurgical outcomes. Methods: Sixteen language-eloquent glioma patients were enrolled. Nine of them underwent preoperative nTMS mapping (n=9, nTMS group), and the other seven were assigned to the non-nTMS group and did not undergo preoperative nTMS mapping (n=7). Before surgery, online IT-TMS was performed during a language task in the nTMS group. Sites in the cortex at which this task was disturbed in three consecutive trials were recorded and regarded as positive and designated nTMS hotspots (HSnTMS). Both groups then underwent awake surgery and intraoperative DES mapping. DES hotspots (HSDES) were also determined in a manner analogous to HSnTMS. The spatial distribution of HSnTMS and HSDES in the nTMS group was recorded, registered in a single brain template, and compared. The center of gravity (CoG) of HSnTMS (HSnTMS-CoG)-based and HSDES-CoG-based diffusion tensor imaging-fiber tracking (DTI-FT) was performed. The electromagnetic simulation was conducted, and the values were then compared between the nTMS and DES groups, as were the Western Aphasia Battery (WAB) scale and fiber-tracking values. Results: HSnTMS and HSDES showed similar distributions (mean distance 6.32 ± 2.6 mm, distance range 2.2-9.3 mm, 95% CI 3.9-8.7 mm). A higher fractional anisotropy (FA) value in nTMS mapping (P=0.0373) and an analogous fiber tract length (P=0.2290) were observed. A similar distribution of the electric field within the brain tissues induced by nTMS and DES was noted. Compared with the non-nTMS group, the integration of nTMS led to a significant improvement in language performance (WAB scores averaging 78.4 in the nTMS group compared with 59.5 in the non-nTMS group, P=0.0321 < 0.05) as well as in brain-structure preservation (FA value, P=0.0156; tract length, P=0.0166). Conclusion: Preoperative IT-TMS provides data equally crucial to DES and thus facilitates precise brain mapping and the preservation of linguistic function.

Clinical Response of Major Depressive Disorder Patients With Suicidal Ideation to Individual Target-Transcranial Magnetic Stimulation.

Suicidal ideation increases precipitously in patients with depression, contributing to the risk of suicidal attempts. Despite the recent advancement in transcranial magnetic stimulation, its effectiveness in depression disorder and its wide acceptance, the network mechanisms of the clinical response to suicidal ideation in major depressive disorder remain unclear. Independent component analysis for neuroimaging data allows the identification of functional network connectivity which may help to explore the neural basis of suicidal ideation in major depressive disorder. Resting-state functional magnetic resonance imaging data and clinical scales were collected from 30 participants (15 major depressive patients with suicidal ideation and 15 healthy subjects). Individual target-transcranial magnetic stimulation (IT-TMS) was then used to decrease the subgenual anterior cingulate cortex activity through the left dorsolateral prefrontal cortex. Thirty days post IT-TMS therapy, seven of 15 patients (46.67%) met suicidal remission criteria, and 12 patients (80.00%) met depression remission criteria. We found that IT-TMS could restore the abnormal functional network connectivity between default mode network and precuneus network, left executive control network and sensory-motor network. Furthermore, the changes in functional network connectivity between the default mode network and precuneus network were associated with suicidal ideation, and depressive symptoms were related to connectivity between left executive control network and sensory-motor network. These findings illustrate that IT-TMS is an effective protocol for the accurate restoration of impaired brain networks, which is consistent with clinical symptoms.

A Terahertz Detector Based on Double-Channel GaN/AlGaN High Electronic Mobility Transistor.

A double-channel (DC) GaN/AlGaN high-electron-mobility transistor (HEMT) as a terahertz (THz) detector at 315 GHz frequency is proposed and fabricated in this paper. The structure of the epitaxial layer material in the detector is optimized, and the performance of the GaN HEMT THz detector is improved. The maximum responsivity of 10 kV/W and minimum noise equivalent power (NEP) of 15.5 pW/Hz0.5 are obtained at the radiation frequency of 315 GHz. The results are comparable to and even more promising than the reported single-channel (SC) GaN HEMT detectors. The enhancement of THz response and the reduction of NEP of the DC GaN HEMT detector mainly results from the interaction of 2DEG in the upper and lower channels, which improves the self-mixing effect of the detector. The promising experimental results mean that the proposed DC GaN/AlGaN HEMT THz detector is capable of the practical applications of THz detection.

Enhancement of Electromagnetic Interference Shielding Performance and Wear Resistance of the UHMWPE/PP Blend by Constructing a Segregated Hybrid Conductive Carbon Black-Polymer Network.

The low-percolation-threshold conductive networking structure is indispensable for the high performance and functionalization of conductive polymer composites (CPCs). In this work, conductive carbon black (CCB)-reinforced ultrahigh-molecular-weight polyethylene (UHMWPE)/polypropylene (PP) blend with tunable electrical conductivity and good mechanical properties was prepared using a high-speed mechanical mixing method and a compression-molded process. An interconnecting segregated hybrid CCB-polymer network is formed in electrically conductive UHMWPE/PP/CCB (UPC) composites. The UPC composites possess a dense conductive pathway at a low percolation threshold of 0.48 phr. The composite with 3 phr CCB gives an electrical conductivity value of 1.67 × 10-3 S/cm, 12 orders of magnitude higher than that of the polymeric matrix, suggesting that CCB improves both the electrical conductivity and electromagnetic interference shielding effectiveness (EMI SE) of the composite at the loading fraction over its percolation threshold. The composite with 15 phr CCB presents an absorption-dominated electromagnetic interference shielding effectiveness (EMI SE) as high as 27.29 dB at the X-band. The composite also presents higher tribological properties, mechanical properties, and thermal stability compared to the UP blend. This effort provides a simple and effective way for the mass fabrication of CPC materials with excellent performance.

Bacterial degradation of anthraquinone dyes.

Anthraquinone dyes, which contain anthraquinone chromophore groups, are the second largest class of dyes after azo dyes and are used extensively in textile industries. The majority of these dyes are resistant to degradation because of their complex and stable structures; consequently, a large number of anthraquinone dyes find their way into the environment causing serious pollution. At present, the microbiological approach to treating printing and dyeing wastewater is considered to be an economical and feasible method, and reports regarding the bacterial degradation of anthraquinone dyes are increasing. This paper reviews the classification and structures of anthraquinone dyes, summarizes the types of degradative bacteria, and explores the possible mechanisms and influencing factors of bacterial anthraquinone dye degradation. Present research progress and existing problems are further discussed. Finally, future research directions and key points are presented.

K-MEAP: Multiple Exemplars Affinity Propagation With Specified $K$ Clusters.

Recently, an attractive clustering approach named multiexemplar affinity propagation (MEAP) has been proposed as an extension to the single exemplar-based AP. MEAP is able to automatically identify multiple exemplars for each cluster associated with a superexemplar. However, if the cluster number is a prior knowledge and can be specified by the user, MEAP is unable to make use of such knowledge directly in its learning process. Instead, it has to rely on rerunning the process as many times as it takes by tuning parameters until it generates the desired number of clusters. The process of MEAP rerunning may be very time-consuming. In this paper, we propose a new clustering algorithm called Multiple Exemplars Affinity Propagation with Specified K Clusters which is able to generate specified K clusters directly while retaining the advantages of MEAP. Two kinds of new additional messages are introduced in K-MEAP in order to control the number of clusters in the process of message passing. Detailed problem formulation, derived messages, and in-depth analysis of the proposed K-MEAP are provided. Experimental studies on 11 real-world data sets with different kinds of applications demonstrate that K-MEAP not only generates K clusters directly and efficiently without tuning parameters but also outperforms related approaches in terms of clustering accuracy.