Design of Deep Learning Acoustic Sonar Receiver with Temporal/ Spatial Underwater Channel Feature Extraction Capability

In this study, deep learning network technology is employed to solve the problem of rapid changes in underwater channels. The modulation techniques employed are frequency-shift keying (FSK) and the BELLHOP module of MATLAB; they are used to create water with multipath, Doppler shifts, and additive Gaussian white noise such that underwater acoustic receiving signals simulating the actual ocean environment can be obtained. The southwest coastal area of Taiwan is simulated in the manuscript. The results reveal that optimizing the environment by using the virtual time reversal mirror (VTRM) technique can generally mitigate the bit error rates (BERs) of the deep learning network’s model receiver and traditional demodulation receiver. Lastly, seven deep learning networks are deployed to demodulate the FSK signals, and these approaches are compared with traditional demodulation techniques to determine the deep learning network techniques that are most suitable for marine environments

The role of Toll signaling in dorsoventral axis formation in the milkweed bug Oncopeltus fasciatus

The establishment of dorsoventral (DV) axis in the Drosophila embryo relies on the Toll/Dorsal signaling pathway. The transcription factor Dorsal acts downstream of Toll forming a nuclear gradient that determines different cell fates along the DV axis. The formation of the DV axis has been studied in two other holometabolous insects, the bee- tle Tribolium and the wasp Nasonia. However, the role of Toll signaling has not been addressed in the more basally branching hemimetabolous insects. Here, the functions of Toll signaling components have been studied in a representative of the hemimetabola, the milkweed bug Oncopeltus fasciatus. All components of the Toll signaling pathway were identified from the Oncopeltus transcriptome, including the Spätzle ligands, Toll receptors, Myd88 adaptors, Pelle and Tube-like protein kinases, and the Dorsal transcrip- tion factors. Knockdown of these components by parental RNAi (pRNAi) leads to a loss of expression of the ventral marker genes twist, short gastrulation (sog) and the lateral marker gene sim, indicating a dorsalization of the embryos. Anterior-shifted expression of several marker genes in Toll-1 and dorsal-1 RNAi embryos indicates that Toll signal- ing also modulates the AP patterning system. Surprisingly, even some genes required upstream of Toll to activate the Toll ligand Spätzle are conserved between Drosopihla and Oncopeltus. Thus, in Oncopeltus transcripts of the serine protease Nudel and the sulfotransferase Pipe are expressed in the follicle cells surrounding the oocyte like in flies and knockdown of their function results in dorsalized embryos. This indicates that the mechanisms responsible for transmitting the DV polarity of the egg chamber to the em- bryo are evolutionarily conserved within insects predating the split between bugs and the holometabola 350 million years ago. Previous work has shown that in addition to Toll signaling BMP signaling also plays a crucial role for patterning the entire DV axis in Oncopeltus. To investigate the relationship between Toll and BMP signaling, double knockdown experiments were performed. Simultaneous loss-of-function of dpp and Toll-1, which encode the BMP ligand and Toll receptor, leads to an expansion of twist and sog expression around entire embryonic circumference like in the dpp single knockdown, indi- cating that BMP is epistatic to Toll. Thus, BMP signaling seems to be more important than Toll signaling for establishing the cell fates along the DV axis in Oncopeltus. As a DV function of Toll signaling has not been observed outside of insects, the diminished function of Toll signaling in Oncopeltus (compared to holometabolous insects) is likely to represent an ancestral aspect of DV axis formation in insects

A Holographic Theory for the Phase Transitions Between Fermionic Symmetry-protected Topological States

In an earlier work we developed a holographic theory for the phase transition between bosonic symmetry-protected topological (SPT) states. This paper is a continuation of it. Here we present the holographic theory for fermionic SPT phase transitions. We show that in any dimension $d$, the critical states of fermionic SPT phase transitions has an emergent $Z_2^T$ symmetry and can be realized on the boundary of a $d+1$-dimensional bulk SPT with an extra $Z_2^T$ symmetry.Comment: 35 pages, 10 figure

IGF-1/IGFBP-1 increases blastocyst formation and total blastocyst cell number in mouse embryo culture and facilitates the establishment of a stem-cell line

BACKGROUND: Apoptosis occurs frequently for blastocysts cultured in vitro, where conditions are suboptimal to those found in the natural environment. Insulin-like growth factor-1 (IGF-1) plays an important role in preventing apoptosis in the early development of the embryo, as well as in the progressive regulation of organ development. We hypothesize that IGF-1 and its dephosphorylated binding protein (IGFBP-1) may be able to improve embryo culture with an associated reduced cell death, and that the resultant increase in the total cell number of the embryo could increase the chances of establishing an embryonic stem-cell line. RESULTS: In vivo fertilized zygotes were cultured in medium containing supplementary IGF-1, or IGFBP-1/IGF-1. The stages of the resultant embryos were evaluated at noon on day five post-hCG injection. The extent of apoptosis and necrosis was evaluated using Annexin V and propidium iodine staining under fluorescent microscopy. The establishment of embryonic stem-cell lines was performed using the hatching blastocysts that were cultured in the presence of IGF-1 or IGFBP-1/IGF-1. The results show that the rate of blastocyst formation in a tissue-culture system in the presence of IGF-1 was 88.7% and IGFBP-1/IGF-1 it was 94.6%, respectively, and that it was significantly greater than the figure for the control group (81.9%). IGFBP-1/IGF-1 also resulted in a higher hatching rate than was the case for the control group (68.8% vs. 48.6% respectively). IGF-1 also increased the number of Annexin V-free and propidium iodine-free blastocysts in culture (86.8% vs. 75.9% respectively). Total cell number of blastocyst in culture was increased by 18.9% for those examples cultured with dephosphorylated IGFBP-1/IGF-1. For subsequent stem-cell culture, the chances of the successful establishment of a stem-cell line was increased for the IGF-1 and IGFBP-1/IGF-1 groups (IGF-1 vs. IGFBP-1/IGF-1 vs. control: 45.8% vs. 59.6% vs. 27.3% respectively). CONCLUSION: IGF-1 or dephosphorylated IGFBP-1/IGF-1 supplement does result in an anti-apoptotic effect for early embryo development in culture, with a subsequent increased total cell number resulting from cell culture. The effect is beneficial for the later establishment of a stem-cell line

Comparison of the Prevalence of Metabolic Syndrome Between the Criteria for Taiwanese and Japanese and the Projected Probability of Stroke in Elderly Hypertensive Taiwanese

SummaryBackgroundThe cutoff of abdominal circumference for metabolic syndrome (MS) defined by the Bureau of Health Promotion (BHP) of Taiwan for Taiwanese (men, 90cm; women, 80cm) and by the International Diabetes Federation (IDF) for Japanese (men, 85cm; women, 90cm) differs. This study aimed to examine the impact of this difference on the prevalence of MS and the impact of an MS diagnosis on the projected risk of stroke in hypertensive Taiwanese.MethodsMS was examined in a sample of 3,472 hypertensive patients (aged 55–80 years; 1,709 women) across Taiwan. The 10-year probability of stroke estimated from the Framingham equation was compared between MS and non-MS patients.ResultsThe prevalence of MS using the BHP criteria was 59.2% using the BHP criteria (95% confidence interval, CI, 57.6–60.8%; men, 52.5%; women, 66.1%) and 48.9% by the IDF criteria (95% CI, 47.2–50.5%; men, 61.3%; women, 36.1%). Both criteria showed that, compared with non-MS, MS has higher predicted 10-year probability of stroke (BHP, 0.153 ± 0.115 vs. 0.133 ± 0.105; IDF, 0.159 ± 0.109 vs. 0.132 ± 0.112; both p < 0.001) because of the difference in women (BHP, 0.143 ± 0.124 vs. 0.102 ± 0.091; IDF, 0.147 ± 0.121 vs. 0.118 ± 0.110; both p < 0.001) rather than men (BHP, p = 0.21; IDF, p = 0.29).ConclusionBoth criteria demonstrate that MS is highly prevalent in elderly hypertensive patients in Taiwan. Additionally in women, but not men, the predicted probability of stroke is higher in MS than in non-MS patients. The diagnosis of MS is potentially useful for identifying elderly hypertensive females with an elevated risk of stroke in Taiwan

A Cloud Information Platform for 3D Printing Rehabilitation Devices

Due to the problems of current population aging, occupational injuries and traffic accidents have led to an increasing number of elder people who are physically disabled in Taiwan. These persons, mostly seek medical treatment from medical institutions to help restore them to their premorbid level. Therefore the number of patients who go to medical institutions is gradually increasing and the splinting is largely applied in the medical cares. 3D printing technology has been widely used in the medical industry in recent years, especially in the development of rehabilitation devices. Up until now, to produce the customized splint requires either face to face communication or messaging software by relevant parties. Due to the complexity of the medical process, it is often time-consuming for occupational therapists to discuss the medical records with the splint design engineers via the above mentioned means. The other difficulty is that data management becomes a real problem. Medical communication and information management are thus the most urgent issues that need to be investigated. In this study, we applied the information technology and cloud-based technology to design a simple and user-friendly web-based interface for making 3D printing splint. This web-based interface utilizes cloud-based technology to provide an information platform for communication and co-management between the relevant stakeholders. The aim of this study is to make system management, retrieving patients’ information and browsing 3D graphics be more convenient for users, and thus to improve the efficiency and effectiveness of producing splints based on the proposed system

Identification of patients with chronic migraine by using sensory-evoked oscillations from the electroencephalogram classifier

Background: To examine whether the modulating evoked cortical oscillations could be brain signatures among patients with chronic migraine, we investigated cortical modulation using an electroencephalogram with machine learning techniques. Methods: We directly record evoked electroencephalogram activity during nonpainful, painful, and repetitive painful electrical stimulation tasks. Cortical modulation for experimental pain and habituation processing was analyzed and used to differentiate patients with chronic migraine from healthy controls using a validated machine-learning model. Results: This study included 80 participants: 40 healthy controls and 40 patients with chronic migraine. Evoked somatosensory oscillations were dominant in the alpha band. Longer latency (nonpainful and repetitive painful) and augmented power (nonpainful and repetitive painful) were present among patients with chronic migraine. However, for painful tasks, alpha increases were observed among healthy controls. The oscillatory activity ratios between repetitive painful and painful tasks represented the frequency modulation and power habituation among healthy controls, respectively, but not among patients with chronic migraine. The classification models with oscillatory features exhibited high performance in differentiating patients with chronic migraine from healthy controls. Conclusion: Altered oscillatory characteristics of sensory processing and cortical modulation reflected the neuropathology of patients with chronic migraine. These characteristics can be reliably used to identify patients with chronic migraine using a machine-learning approach