Research on domain ontology construction based on the content features of online rumors.

Online rumors are widespread and difficult to identify, which bring serious harm to society and individuals. To effectively detect and govern online rumors, it is necessary to conduct in-depth semantic analysis and understand the content features of rumors. This paper proposes a TFI domain ontology construction method, which aims to achieve semantic parsing and reasoning of the rumor text content. This paper starts from the term layer, the frame layer, and the instance layer, and based on the reuse of the top-level ontology, the extraction of core literature content features, and the discovery of new concepts in the real corpus, obtains the core classes (five parent classes and 88 subclasses) of the rumor domain ontology and defines their concept hierarchy. Object properties and data properties are designed to describe relationships between entities or their features, and the instance layer is created according to the real rumor datasets. OWL language is used to encode the ontology, Protégé is used to visualize it, and SWRL rules and pellet reasoner are used to mine and verify implicit knowledge of the ontology, and judge the category of rumor text. This paper constructs a rumor domain ontology with high consistency and reliability.

Old woman with Sheehan's syndrome suffered severe hyponatremia following percutaneous coronary intervention: a case report and review of literature.

Glucocorticoid deficiency can lead to hypoglycemia, hypotension, and electrolyte disorders. Acute glucocorticoid deficiency under stress is very dangerous. Here, we present a case study of an elderly patient diagnosed with Sheehan's syndrome, manifesting secondary adrenal insufficiency and secondary hypothyroidism, managed with daily prednisone and levothyroxine therapy. She was admitted to our hospital due to acute non-ST segment elevation myocardial infarction. The patient developed nausea and limb twitching post-percutaneous coronary intervention, with subsequent diagnosis of hyponatremia. Despite initial intravenous sodium supplementation failed to rectify the condition, and consciousness disturbances ensued. However, administration of 50 mg hydrocortisone alongside 6.25 mg sodium chloride rapidly ameliorated symptoms and elevated blood sodium levels. Glucocorticoid deficiency emerged as the primary etiology of hyponatremia in this context, exacerbated by procedural stress during percutaneous coronary intervention. Contrast agent contributed to blood sodium dilution. Consequently, glucocorticoid supplementation emerges as imperative, emphasizing the necessity of stress-dose administration of glucocorticoid before the procedure. Consideration of shorter intervention durations and reduced contrast agent dosages may mitigate severe hyponatremia risks. Moreover, it is crucial for this patient to receive interdisciplinary endocrinologist management. In addition, Sheehan's syndrome may pose a risk for coronary atherosclerotic disease.

Sub-gigahertz bandwidth all-optical tunable differentiator with high-energy efficiency based on a micro-ring resonator.

We propose and demonstrate a tunable fractional-order photonic differentiator (DIFF) that can process input pulses with a sub-gigahertz bandwidth. Our scheme utilizes the self-induced optical modulation effect observed in a silicon-on-insulator micro-ring resonator. Gaussian-like pulses with varying pulse widths between 7.5 and 20 ns are employed for differentiation, achieving an energy efficiency over 45%, to the best of our knowledge, which surpasses all previously reported schemes for input pulses with a sub-gigahertz bandwidth. We simulate the temporal dynamics of pulses to gain insight into the physical mechanisms underlying the differentiated outputs and provide a method for differentiation order adjustment, which is experimentally realized using an all-optical pump-probe technique.

Unmanned Aerial Vehicle Cooperative Data Dissemination Based on Graph Neural Networks.

Unmanned Aerial Vehicles (UAVs) have critical applications in various real-world scenarios, including mapping unknown environments, military reconnaissance, and post-disaster search and rescue. In these scenarios where communication infrastructure is missing, UAVs will form an ad hoc network and perform tasks in a distributed manner. To efficiently carry out tasks, each UAV must acquire and share global status information and data from neighbors. Meanwhile, UAVs frequently operate in extreme conditions, including storms, lightning, and mountainous areas, which significantly degrade the quality of wireless communication. Additionally, the mobility of UAVs leads to dynamic changes in network topology. Therefore, we propose a method that utilizes graph neural networks (GNN) to learn cooperative data dissemination. This method leverages the network topology relationship and enables UAVs to learn a decision policy based on local data structure, ensuring that all UAVs can recover global information. We train the policy using reinforcement learning that enhances the effectiveness of each transmission. After repeated simulations, the results validate the effectiveness and generalization of the proposed method.

Case report: Right coronary artery to left ventricular fistula complicated with coronary artery dilation presenting as persistent cardiogenic ischemic chest pain.

We reported a patient with a fistula of the right coronary artery to the left ventricle, accompanied by dilation of the right coronary artery and persistent chest pain. This patient underwent surgical fistula closure surgery, but the fistula recurred. Persistent chest pain reappeared after encountering COVID-19 infection. We analyzed the mechanism of persistent myocardial ischemic chest pain caused by coronary artery fistula in this patient, the impact of surgery on the patient's disease, the possible mechanism of COVID-19 causing persistent ischemic chest pain in this patient, and the possible mechanism of metoprolol in alleviating myocardial ischemic chest pain in this patient.

Sparse 2-D optical phased array with large grating-lobe-free steering range based on an aperiodic grid.

Two-dimensional (2-D) optical phased arrays (OPAs) usually suffer from limited scan ranges and small aperture sizes. To overcome these bottlenecks, we utilize an aperiodic 32 × 32 grid to increase the beam scanning range and furthermore distribute 128 grating antennas sparsely among 1024 grid points so as to reduce the array element number. The genetic algorithm is used to optimize the uneven grid spacings and the sparse distribution of grating antennas. With these measures, a 128-channel 2-D OPA operating at 1550 nm realizes a grating-lobe-free steering range of 53° × 16°, a field of view of 24° × 16°, a beam divergence of 0.31° × 0.49°, and a sidelobe suppression ratio of 9 dB.

COVID-19 epidemic phases and morbidity in different areas of Chinese mainland, 2020.

Background: In the early stage of COVID-19 epidemic, the Chinese mainland once effectively controlled the epidemic, but COVID-19 eventually spread faster and faster in the world. The purpose of this study is to clarify the differences in the epidemic data of COVID-19 in different areas and phases in Chinese mainland in 2020, and to analyze the possible factors affecting the occurrence and development of the epidemic. Methods: We divided the Chinese mainland into areas I, I and III, and divided the epidemic process into phases I to IV: limited cases, accelerated increase, decelerated increase and containment phases. We also combined phases II and III as outbreak phase. The epidemic data included the duration of different phases, the numbers of confirmed cases, asymptomatic infections, and the proportion of imported cases from abroad. Results: In area I, II and III, only area I has a Phase I, and the Phase II and III of area I are longer. In Phase IV, there is a 17-day case clearing period in area I, while that in area II and III are 2 and 0 days, respectively. In phase III or the whole outbreak phase, the average daily increase of confirmed cases in area I was higher than that in areas II and III (P = 0.009 and P = 0.001 in phase III; P = 0.034 and P = 0.002 in the whole outbreak phase), and the average daily in-hospital cases were most in area I and least in area III (P = 0.000, P = 0.000, and P = 0.000 in phase III; P = 0.000, P = 0.000, and P = 0.009 in the whole outbreak phase). The average number of daily in-hospital COVID-19 cases in phase III was more than that in phase II in each area (P = 0.000, P = 0.000, and P = 0.001). In phase IV, from March 18, 2020 to January 1, 2021, the increase of confirmed cases in area III was higher than areas I and II (both P = 0.000), and the imported cases from abroad in Chinese mainland accounted for more than 55-61%. From June 16 to July 2, 2020, the number of new asymptomatic infections in area III was higher than that in area II (P = 0.000), while there was zero in area I. From July 3, 2020 to January 1, 2021, the increased COVID-19 cases in area III were 3534, while only 14 and 0, respectively, in areas I and II. Conclusions: The worst epidemic areas in Chinese mainland before March 18, 2020 and after June 15, 2020 were area I and area III, respectively, and area III had become the main battlefield for Chinese mainland to fight against imported epidemic since March 18, 2020. In Wuhan, human COVID-19 infection might occur before December 8, 2019, while the outbreak might occur before January 16 or even 10, 2020. Insufficient understanding of COVID-19 hindered the implementation of early effective isolation measures, leading to COVID-19 outbreak in Wuhan, and strict isolation measures were effective in controlling the epidemic. The import of foreign COVID-19 cases has made it difficult to control the epidemic of area III. When humans are once again faced with potentially infectious new diseases, it is appropriate to first and foremost take strict quarantine measures as soon as possible, and mutual cooperation between regions should be explored to combat the epidemic.

Chest pain with ST-elevation in leads AVR, III, AVF, V1, V3R, V4R and V5R.

We mistakenly diagnosed a patient with pulmonary embolism as ST-elevation acute myocardial infarction. The case complained of chest pain with ST-elevation in leads AVR, III, AVF, V1, V3R, V4R and V5R. In addition, we also found ST- elevation AVR, III>ST- elevation AVF, QIII>QAVF and QV1. Multi-site pulmonary embolism can lead to type 2 myocardial infarction or special type of myocardial infarction with non-obstructive coronary arteries through multiple pathological mechanisms.

Polarization-insensitive antisymmetric multimode waveguide Bragg grating filter based on an SiN-Si dual-layer stack.

A polarization-insensitive multimode antisymmetric waveguide Bragg grating (MASWBG) filter based on an SiN-Si dual-layer stack is demonstrated. Carefully optimized grating corrugations patterned on the sidewall of a silicon waveguide and SiN overlay are used to perturbate TE and TM modes, respectively. Furthermore, the lateral-shift apodization technique is utilized to improve the sidelobe suppression ratio (SLSR). A good overlap between the passbands measured in TE and TM polarization states is obtained. Insertion losses, SLSRs, and 3-dB bandwidths of measured passbands in TE/TM polarizations are 1/1.72 dB, 18.5/19.1 dB, and 5.1/3.5 nm, respectively.

Silicon-based high-power traveling wave photodetector with inductive gain peaking.

We demonstrate Ge/Si high-power and high-speed distributed traveling wave photodetectors (TWPD) by using the inductive gain peaking technique. Input terminals of TW electrodes are open to enhance RF output efficiencies to output loads. Furthermore, optimized on-chip spiral inductors are incorporated at output terminals of TW electrodes to alleviate bandwidth degradations caused by the absences of matching impedances. A comprehensive equivalent circuit model is developed to calculate the frequency response of this scheme. It is used to optimize the design, and then is validated by measurement results. After inducing on-chip inductors, the bandwidths of 4-stage and 8-stage TWPDs are improved from 32 to 44 GHz and 16 to 24 GHz, respectively. Maximum RF output powers of 4-stage and 8-stage TWPDs with on-chip inductors are measured to be 5.7 dBm and 9.4 dBm at 20 GHz, respectively.

Rebound sign: a case report and review of literature.

We reviewed previously reported imaging features of coronary air embolism. We also reported an unusual image 'rebound sign' of proximal coronary artery air embolism for the first time, that is, with the regular contraction and relaxation of the heart, the contrast medium near the embolus rebounds regularly, and the smooth gas-liquid boundary is alternately clear and blurred. We conclude that myocardial bridge plays a role in the formation of 'rebound sign.'Abbreviations: CAE: Coronary Air Embolism; CAG: Coronary Angiography; RCA: Right Coronary Artery; LCA: Left Coronary Artery; LAD: Left Anterior Descending Coronary Artery; LCX: Left Circumflex Artery; MB: Myocardial Bridge; STEMI: ST Segment Elevation Myocardial Infarction; TOE: Transesophageal Echocardiography.

Wavelet convolutional neural network for robust and fast temperature measurements in Brillouin optical time domain reflectometry.

In this paper, a wavelet convolutional neural network (WNN) consisting of a one-dimensional (1D) convolutional neural network and a self-adaptive wavelet neural network has been proposed and demonstrated experimentally for temperature measurement in a Brillouin optical time domain reflectometry (BOTDR) system. Based on the analysis of the system noise, it follows the Gaussian white noise distribution along the time-related sensing distance. The impact of the noise in time-domain on the measured Brillouin gain spectra (BGSs) could be neglected, so that the BGSs in the fiber can be regarded as a series of 1D input data of the proposed WNN. Different self-adaptive wavelet activation functions connected to each output of the full-connection network are adopted to realize the multi-scaled analysis and the scale translation, which can obtain more local characteristics in frequency-domain. The output extracted by the WNN is Brillouin frequency shift (BFS), which presents linearity correlation to the actual temperature. Considering the multi-parameters including different frequency ranges, signal-to-noise-ratios (SNRs), BFSs and spectral widths (SWs), a general model of the proposed WNN is trained to handle more extreme cases, in which it doesn't require retraining for different single-mode (SM) optical fibers in BOTDR sensing system. The performances of the WNN are compared with other two techniques, the Lorentzian curve fitting based on Levenberg-Marquardt (LM) algorithm and the basic neural network (NN) containing input and output layers together with two hidden layers. Both the simulated and measured results show that the WNN has better robustness and flexibility than the LM and the NN. Besides, the computational accuracy of the WNN is improved and the fluctuation of that is slighter, especially when the SNR is less than 11 dB. Moreover, the WNN takes approximately 0.54 s to measure the temperature from the 18,000 collected BGSs transmitted through the 18 km SM optical fiber. The calculating time of the WNN is greatly reduced by three orders of magnitude in comparison with that of the LM, and is comparable to that of the NN. It proves that the proposed WNN may provide a feasible or even better scheme for the robust and fast temperature measurement in BOTDR system.

Ultra-compact silicon mode (de)multiplexer based on directional couplers with subwavelength sidewall corrugations.

Asymmetrical directional couplers aided with subwavelength sidewall corrugations are used to realize ultra-compact silicon mode (de)multiplexers at C-band. Three mode (de)multiplexers with ultra-short coupling lengths of 5.6/6.5/7.7 µm are designed to enable low-loss mode conversions between TE0 and TE1/2/3 modes. They are then cascaded to build a four-channel mode-division-multiplexing (MDM) link. The four mode channels present minimal on-chip insertion losses of 0.2/0.7/0.7/0.9 dB at their peak wavelengths. Measured cross talk levels of the four mode channels are better than -18.0/-19.1/-16.0/-18.2 dB within the wavelength range from 1530 nm to 1580 nm.

Efficient extraction of chitin from crustacean waste via a novel ternary natural deep eutectic solvents.

Extraction of chitin from crustacean waste with acidic natural deep eutectic solvents (NADESs) is usually accompanied by degradation of chitin, which lowers the yield and molecular weight of product. Herein, this study proposed a eco-friendly and feasible route for effectively improving the yield and molecular weight of chitin by introducing N-acetyl-D-glucosamine into ternary NADESs. A high molecular weight chitin with molecular weight of 3.92 × 105 Da, purity of 90.2% and yield of 85.6% was obtained from crab shell. Compared with conventional acid/alkali and binary NADESs method, the maximum yield of chitin extracted by ChCl-G-FA2 was increased by 1.57 times and 1.39 times respectively. Molecular weight of chitin was 3.16 times that of acid/alkali method. Recycling performance evaluation revealed that the purity of chitin could still reach 80.4% after five cycles of NADESs. This study provided a eco-friendly utilization strategy for crustacean waste based on multifunctional NADESs.

Accent Recognition with Hybrid Phonetic Features.

The performance of voice-controlled systems is usually influenced by accented speech. To make these systems more robust, frontend accent recognition (AR) technologies have received increased attention in recent years. As accent is a high-level abstract feature that has a profound relationship with language knowledge, AR is more challenging than other language-agnostic audio classification tasks. In this paper, we use an auxiliary automatic speech recognition (ASR) task to extract language-related phonetic features. Furthermore, we propose a hybrid structure that incorporates the embeddings of both a fixed acoustic model and a trainable acoustic model, making the language-related acoustic feature more robust. We conduct several experiments on the AESRC dataset. The results demonstrate that our approach can obtain an 8.02% relative improvement compared with the Transformer baseline, showing the merits of the proposed method.

Metabolic Processes are Potential Biological Processes Distinguishing Nonischemic Dilated Cardiomyopathy from Ischemic Cardiomyopathy: A Clue from Serum Proteomics.

BACKGROUND: Ischemic cardiomyopathy (ICM) and nonischemic dilated cardiomyopathy (DCM) are the two most common causes of heart failure. However, our understanding of the specific proteins and biological processes distinguishing DCM from ICM remains insufficient. MATERIALS AND METHODS: The proteomics analyses were performed on serum samples from ICM (n=5), DCM (n=5), and control (n=5) groups. Proteomics and bioinformatics analyses, including weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA), were performed to identify the hub circulating proteins and the hub biological processes in ICM and DCM. RESULTS: The analysis of differentially expressed proteins and WGCNA identified the hub circulating proteins in ICM (GAPDH, CLSTN1, VH3, CP, and ST13) and DCM (one downregulated protein, FGG; 18 upregulated proteins, including HEL-S-276, IGK, ALDOB, HIST1H2BJ, HEL-S-125m, RPLP2, EL52, NCAM1, P4HB, HEL-S-99n, HIST1H4L, HIST2H3PS2, F8, ERP70, SORD, PSMA3, PSMB6, and PSMA6). The mRNA expression of the heart specimens from GDS651 validated that ALDOB, GAPDH, RPLP2, and IGK had good abilities to distinguish DCM from ICM. In addition, GSEA results showed that cell proliferation and differentiation were the hub biological processes related to ICM, while metabolic processes and cell signaling transduction were the hub biological processes associated with DCM. CONCLUSION: The present study identified five dysregulated hub circulating proteins among ICM patients and 19 dysregulated hub circulating proteins among DCM patients. Cell proliferation and differentiation were significantly enriched in ICM. Metabolic processes were strongly enhanced in DCM and may be used to distinguish DCM from ICM.

CMBF: Cross-Modal-Based Fusion Recommendation Algorithm.

A recommendation system is often used to recommend items that may be of interest to users. One of the main challenges is that the scarcity of actual interaction data between users and items restricts the performance of recommendation systems. To solve this problem, multi-modal technologies have been used for expanding available information. However, the existing multi-modal recommendation algorithms all extract the feature of single modality and simply splice the features of different modalities to predict the recommendation results. This fusion method can not completely mine the relevance of multi-modal features and lose the relationship between different modalities, which affects the prediction results. In this paper, we propose a Cross-Modal-Based Fusion Recommendation Algorithm (CMBF) that can capture both the single-modal features and the cross-modal features. Our algorithm uses a novel cross-modal fusion method to fuse the multi-modal features completely and learn the cross information between different modalities. We evaluate our algorithm on two datasets, MovieLens and Amazon. Experiments show that our method has achieved the best performance compared to other recommendation algorithms. We also design ablation study to prove that our cross-modal fusion method improves the prediction results.

Selective removal of lignin with sodium chlorite to improve the quality and antioxidant activity of xylo-oligosaccharides from lignocellulosic biomass.

As a key anti-degradation barrier that restricts the biotransformation of lignocellulose, the presence of lignin usually severely affects the quality of the extracted xylo-oligosaccharides (XOS). Herein, this study proposed a practical route to improve the quality and antioxidant activity of XOS extracted from lignocellulosic biomass via selective removal of lignin. The highest delignification of 92.6% was successfully achieved with 8% sodium chlorite at 75°C for 2 h. An ideal hemicellulose sample with a purity of 86.1% was obtained by selective removal of lignin. A high-quality XOS sample with a purity of 96.3%, a yield of 77.4%, and a color value of 814 was obtained by separating and purifying the enzymatic hydrolysate. Antioxidant activity assay showed that the highest radical scavenging activity of XOS was 87.3%. Importantly, this study provide a feasible and effective route for the lignocellulosic biomass utilization strategy based on the selective removal of lignin.

A study of the differential expression profiles of Keshan disease lncRNA/mRNA genes based on RNA-seq.

BACKGROUND: This study aims to analyze the differential expression profiles of lncRNA in Keshan disease (KSD) and to explore the molecular mechanism of the disease occurrence and development. METHODS: RNA-seq technology was used to construct the lncRNA/mRNA expression library of a KSD group (n=10) and a control group (n=10), and then Cuffdiff software was used to obtain the gene lncRNA/mRNA FPKM value as the expression profile of lncRNA/mRNA. The fold changes between the two sets of samples were calculated to obtain differential lncRNA/mRNA expression profiles, and a bioinformatics analysis of differentially expressed genes was performed. RESULTS: A total of 89,905 lncRNAs and 20,315 mRNAs were detected. Statistical analysis revealed that 921 lncRNAs had obvious differential expression, among which 36 were up-regulated and 885 were down-regulated; 2,771 mRNAs presented with obvious differential expression, among which 253 were up-regulated and 2,518 were down-regulated, and cluster analysis indicated that the gene expression trends among the sample groups were consistent. The differentially expressed lncRNAs were tested for target genes, and 117 genes were found to be regulated by differential lncRNAs, which were concentrated in six signaling pathways, among which the apoptosis FoxO signaling pathway ranked first, so the target genes IGF1R and TGFB2 were screened out. CONCLUSIONS: In this study, RNA-seq technology was used to obtain the differential gene expression profiles of KSD, and bioinformatics analysis was performed to screen out target genes, pointing out the direction for further research into the etiology, pathogenesis and drug treatment targets of KSD.