Assessing the Accuracy of Biogenic Content Estimation from Visible Derivative Spectroscopy of Sedimentary Cores from the Western Pacific

AbstractThe biogenic contents of marine sediments, such as carbonate (CaCO3) and organic carbon (TOC), provide important information about past climatic and environmental changes. For sediment cores, such as those found in the marginal seas of the western Pacific, intensive laboratory study takes considerable time and effort. The previous drilling and coring programs have developed nondestructive methods, which require less time and labor, such as those that utilize visible reflectance derivative spectra measured from the surface of sediment samples to estimate downcore biogenic content. Nevertheless, these methods have been shown to be useful only for on-site estimation of downcore samples and are not considered entirely feasible for testing samples collected from regional or larger spatial scales. The present study presents a novel protocol of spectral decomposition utilizing varimax-rotated principal component analysis (VPCA) for estimating biogenic contents of sediment samples at the basin scale. Using two sediment cores from the South China Sea (SCS) separated by 200 kilometers, we evaluated a new protocol by measuring the visible reflectance spectrum and the biogenic content. Based on six VPCA components of first derivative reflectance spectrum measurements and laboratory analyzed biogenic contents of core MD972148, a set of empirical equations for estimating CaCO3, TOC, and opal contents have been established. The equations were tested using data from core MD012396, and the new regression equations provided accurate estimations. Our study demonstrated that our new methods could achieve better estimates due to the improvement of the regression model with a reduced number of independent variables. Further, this study circumvents the limitation of applying empirical equations to sediment cores outside of the calibration range. Our present findings state that with more comprehensive and systematic reflectance spectral data, the new protocol can be used to estimate biogenic content with more regional or spatial precision in future research

Effects of painful stimulation and acupuncture on attention networks in healthy subjects

Pain is a subjective sensory and emotional experience, and it has been reported that many different brain regions are regulated by pain, and that pain can impact attention. Acupuncture is an important treatment component of Chinese traditional medicine, and has been used for thousands of years to treat a wide variety of conditions. Although several studies have shown that acupuncture improves consciousness, the precise impact of both acupuncture and painful stimulation on attention is unclear. Are all of the attention networks modulated, or do these stimuli act on a specific network? Is the effect of painful stimulation similar to that of acupuncture? We administered the attention network test to 30 participants (15 males) to investigate the relative efficiencies of three independent attention networks (alerting, orienting, and executive control networks) under three conditions: baseline, after painful stimulation, and after acupuncture. The degree of pain experienced was assessed on a horizontally oriented visual analogue scale. The results showed that painful stimulation and acupuncture had similar effects on the orienting and executive control networks; however, there was a significantly different effect between the three conditions on the alerting network. In conclusion, (1) painful stimulation can selectively impact attention; (2) acupuncture can also selectively impact attention; i.e., both have selective influences on the alerting and executive control networks, but not on the orienting network; (3) the effects of acupuncture and painful stimulation are not identical. The mechanisms by which painful stimulation and acupuncture influence attention warrant further research

Predicting hyperlinks via hypernetwork loop structure

While links in simple networks describe pairwise interactions between nodes, it is necessary to incorporate hypernetworks for modeling complex systems with arbitrary-sized interactions. In this study, we focus on the hyperlink prediction problem in hypernetworks, for which the current state-of-art methods are latent-feature-based. A practical algorithm via topological features, which can provide understandings of the organizational principles of hypernetworks, is still lacking. For simple networks, local clustering or loop reflects the correlations among nodes; therefore, loop-based link prediction algorithms have achieved accurate performance. Extending the idea to hyperlink prediction faces several challenges. For instance, what is an effective way of defining loops for prediction is not clear yet; besides, directly comparing topological statistics of variable-sized hyperlinks could introduce biases in hyperlink cardinality. In this study, we address the issues and propose a loop-based hyperlink prediction approach. First, we discuss and define the loops in hypernetworks; then, we transfer the loop-features into a hyperlink prediction algorithm via a simple modified logistic regression. Numerical experiments on multiple real-world datasets demonstrate superior performance compared to the state-of-the-art methods

Bayesian Inference Federated Learning for Heart Rate Prediction

The advances of sensing and computing technologies pave the way to develop novel applications and services for wearable devices. For example, wearable devices measure heart rate, which accurately reflects the intensity of physical exercise. Therefore, heart rate prediction from wearable devices benefits users with optimization of the training process. Conventionally, Cloud collects user data from wearable devices and conducts inference. However, this paradigm introduces significant privacy concerns. Federated learning is an emerging paradigm that enhances user privacy by remaining the majority of personal data on users’ devices. In this paper, we propose a statistically sound, Bayesian inference federated learning for heart rate prediction with autoregression with exogenous variable (ARX) model. The proposed privacy-preserving method achieves accurate and robust heart rate prediction. To validate our method, we conduct extensive experiments with real-world outdoor running exercise data collected from wearable devices.Peer reviewe

Giant panda BAC library construction and assembly of a 650-kb contig spanning major histocompatibility complex class II region

<p>Abstract</p> <p>Background</p> <p>Giant panda is rare and endangered species endemic to China. The low rates of reproductive success and infectious disease resistance have severely hampered the development of captive and wild populations of the giant panda. The major histocompatibility complex (MHC) plays important roles in immune response and reproductive system such as mate choice and mother-fetus bio-compatibility. It is thus essential to understand genetic details of the giant panda MHC. Construction of a bacterial artificial chromosome (BAC) library will provide a new tool for panda genome physical mapping and thus facilitate understanding of panda MHC genes.</p> <p>Results</p> <p>A giant panda BAC library consisting of 205,800 clones has been constructed. The average insert size was calculated to be 97 kb based on the examination of 174 randomly selected clones, indicating that the giant panda library contained 6.8-fold genome equivalents. Screening of the library with 16 giant panda PCR primer pairs revealed 6.4 positive clones per locus, in good agreement with an expected 6.8-fold genomic coverage of the library. Based on this BAC library, we constructed a contig map of the giant panda MHC class II region from <it>BTNL2 </it>to <it>DAXX </it>spanning about 650 kb by a three-step method: (1) PCR-based screening of the BAC library with primers from homologous MHC class II gene loci, end sequences and BAC clone shotgun sequences, (2) DNA sequencing validation of positive clones, and (3) restriction digest fingerprinting verification of inter-clone overlapping.</p> <p>Conclusion</p> <p>The identifications of genes and genomic regions of interest are greatly favored by the availability of this giant panda BAC library. The giant panda BAC library thus provides a useful platform for physical mapping, genome sequencing or complex analysis of targeted genomic regions. The 650 kb sequence-ready BAC contig map of the giant panda MHC class II region from <it>BTNL2 </it>to <it>DAXX</it>, verified by the three-step method, offers a powerful tool for further studies on the giant panda MHC class II genes.</p

Experimental Free-Space Distribution of Entangled Photon Pairs over a Noisy Ground Atmosphere of 13km

We report free-space distribution of entangled photon pairs over a noisy ground atmosphere of 13km. It is shown that the desired entanglement can still survive after the two entangled photons have passed through the noisy ground atmosphere. This is confirmed by observing a space-like separated violation of Bell inequality of $2.45 \pm 0.09$. On this basis, we exploit the distributed entangled photon source to demonstrate the BB84 quantum cryptography scheme. The distribution distance of entangled photon pairs achieved in the experiment is for the first time well beyond the effective thickness of the aerosphere, hence presenting a significant step towards satellite-based global quantum communication.Comment: 4 pages, 3 figure

DDX5 facilitates HIV-1 replication as a cellular co-factor of Rev.

HIV-1 Rev plays an important role in the late phase of HIV-1 replication, which facilitates export of unspliced viral mRNAs from the nucleus to cytoplasm in infected cells. Recent studies have shown that DDX1 and DDX3 are co-factors of Rev for the export of HIV-1 transcripts. In this report, we have demonstrated that DDX5 (p68), which is a multifunctional DEAD-box RNA helicase, functions as a new cellular co-factor of HIV-1 Rev. We found that DDX5 affects Rev function through the Rev-RRE axis and subsequently enhances HIV-1 replication. Confocal microscopy and co-immunoprecipitation analysis indicated that DDX5 binds to Rev and this interaction is largely dependent on RNA. If the DEAD-box motif of DDX5 is mutated, DDX5 loses almost all of its ability to bind to Rev, indicating that the DEAD-box motif of DDX5 is required for the interaction between DDX5 and Rev. Our data indicate that interference of DDX5-Rev interaction could reduce HIV-1 replication and potentially provide a new molecular target for anti-HIV-1 therapeutics