Lift force, drag force, and tension response in vortex-induced vibration for marine risers under shear flow

An experiment was performed in a deep-water basin to investigate VIV mechanisms under shear flow. Lift force, drag force, and tension response were obtained. Results show that multiple frequencies are appeared for nonuniform vortex shedding frequency and interaction between the IL and CF vibrations. Beat phenomenon is observed in time history of lift force, and decreased with the increasing riser pretension. Dominant frequencies of riser tension are consistent with the IL and CF dominant frequency, and amplitudes of the tension are not uniform. VIV is inhibited with increasing riser pretension and the dominant frequencies also increase with increasing riser tension

Effect of drilling pipe rotation on vortex induced vibration response of drilling riser

An experiment was carried out in a basin to investigate rotation of drilling pipe on vortex induced vibration response of drilling riser. Vibration displacement time-history and frequency are obtained. Results show that dominant vibration frequency in the in-line direction is almost twice as high as that in the cross-flow direction. The vibration amplitudes in both the cross-flow and in-line direction increase with an increase in rotation speed of drilling pipe under the experimental conditions. However, the influence of rotation speed drilling pipe on drilling riser vibration amplitude is insignificant. Dominant frequencies are invariant with variation of drilling pipe rotation under experimental conditions

Multi-objective Optimization of Space-Air-Ground Integrated Network Slicing Relying on a Pair of Central and Distributed Learning Algorithms

As an attractive enabling technology for next-generation wireless communications, network slicing supports diverse customized services in the global space-air-ground integrated network (SAGIN) with diverse resource constraints. In this paper, we dynamically consider three typical classes of radio access network (RAN) slices, namely high-throughput slices, low-delay slices and wide-coverage slices, under the same underlying physical SAGIN. The throughput, the service delay and the coverage area of these three classes of RAN slices are jointly optimized in a non-scalar form by considering the distinct channel features and service advantages of the terrestrial, aerial and satellite components of SAGINs. A joint central and distributed multi-agent deep deterministic policy gradient (CDMADDPG) algorithm is proposed for solving the above problem to obtain the Pareto optimal solutions. The algorithm first determines the optimal virtual unmanned aerial vehicle (vUAV) positions and the inter-slice sub-channel and power sharing by relying on a centralized unit. Then it optimizes the intra-slice sub-channel and power allocation, and the virtual base station (vBS)/vUAV/virtual low earth orbit (vLEO) satellite deployment in support of three classes of slices by three separate distributed units. Simulation results verify that the proposed method approaches the Pareto-optimal exploitation of multiple RAN slices, and outperforms the benchmarkers.Comment: 19 pages, 14 figures, journa

Brain atlas fusion from high-thickness diagnostic magnetic resonance images by learning-based super-resolution

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images

Rate-delay analysis of radio access network slices

Based on wireless network virtualization, radio access network (RAN) slicing is developed to provide services for the different users' requirements. Moreover, the users' sum data rate and delay are two significant metrics to guarantee quality of services. In this paper, we first establish an optimization problem to maximize the downlink sum rate while guaranteeing users' delay for RAN slices, where the base stations and user equipments are randomly distributed. Then we analyze the performance tradeoff between the sum rate maximization and delay tolerance. With the aid of Lyapunov optimization, the upper bounds of the achievable rate and delay are derived, through which the existence of tradeoff in performance is obvious and verified by numerical results

Striking Isotopologue-Dependent Photodissociation Dynamics of Water Molecules:The Signature of an Accidental Resonance

Investigations of the photofragmentation patterns of both light and heavy water at the state-to-state level are a prerequisite for any thorough understanding of chemical processing and isotope heterogeneity in the interstellar medium. Here we reveal dynamical features of the dissociation of water molecules following excitation to the (C) over tilde (010) state using a tunable vacuum ultraviolet source in combination with the high-resolution H(D)-atom Rydberg tagging time-of-flight technique. The action spectra for forming H(D) atoms and the OH(OD) product state distributions resulting from excitation to the (C) over tilde (010) states of H2O and D2O both show striking differences, which are attributable to the effects of an isotopologue-specific accidental resonance. Such accidental-resonance-induced state mixing may contribute to the D/H isotope heterogeneity in the solar system. The present study provides an excellent example of competitive state-to-state nonadiabatic decay pathways involving at least five electronic states

Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features

Neuroimage measures from magnetic resonance (MR) imaging, such as cortical thickness, have been playing an increasingly important role in searching for bio-markers of Alzheimer’s disease (AD). Recent studies show that, AD, mild cognitive impairment (MCI) and normal control (NC) can be distinguished with relatively high accuracy using the baseline cortical thickness. With the increasing availability of large longitudinal datasets, it also becomes possible to study the longitudinal changes of cortical thickness and their correlation with the development of pathology in AD. In this study, the longitudinal cortical thickness changes of 152 subjects from four clinical groups (AD, NC, Progressive-MCI and Stable-MCI) selected from Alzheimer’s Disease Neuroimaging Initiative (ADNI) are measured by our recently-developed 4D (spatial+temporal) thickness measuring algorithm. It is found that the four clinical groups demonstrate very similar spatial distribution of GM loss on cortex. To fully utilizing the longitudinal information and better discriminate the subjects from four groups, especially between Stable-MCI and Progressive-MCI, three different categories of features are extracted for each subject, i.e., (1) static cortical thickness measures computed from the baseline and endline, (2) cortex thinning dynamics, such as the thinning speed (mm/year) and the thinning ratio (endline/baseline), and (3) network features computed from the brain network constructed based on the correlation between the longitudinal thickness changes of different ROIs. By combining the complementary information provided by features from all three different categories, two classifiers are trained to diagnose AD and to predict the conversion to AD in MCI subjects, respectively. In the leave-one-out cross-validation, the proposed method can distinguish AD patients from NC at an accuracy of 96.1%, and can detect 81.7% (AUC=0.875) of the MCI converters at 6-months ahead of their conversions to AD. Also, by analyzing the brain network built via longitudinal cortical thickness changes, a significant decrease (P<0.02) of the network clustering coefficient (associated with the development of AD pathology) is found in the Progressive-MCI group, which indicates the degenerated wiring efficiency of the brain network due to AD. More interestingly, the decreasing of network clustering coefficient of the olfactory cortex region was also found in the AD patients, which suggests the olfactory dysfunction. Although the smell identification test is not performed in ADNI, this finding is consistent with other AD-related olfactory studies

Case Report: Leiomyosarcoma of the right external iliac artery: a diagnostic-based study on a rare case

Leiomyosarcoma (LMS) is an uncommon and aggressive form of cancer that originates in the smooth muscles. It possesses the capacity for rapid growth and often manifests with general, nonspecific symptoms arising from the displacement of nearby structures rather than direct invasion. In this particular instance, an 81-year-old woman presented with right lower abdominal pain, leading to the discovery of a mass adjacent to the right external iliac artery. In this case, the patient was misdiagnosed initially because of her nonspecific and poorly distinguished clinical symptoms. The laboratory results were within normal ranges. A well-defined tumor was detected through laparoscopic operation and subsequently surgically excised. The histopathological analysis of the tumor revealed the presence of malignant spindle cells, nuclear pleomorphism, and tumor giant cells. Immunohistochemistry tests indicated positive results for CD34 and Desmin, while CD117 and DOG1 showed adverse effects. It is worth noting that LMS of the right external iliac artery is an infrequent occurrence, potentially resulting in delayed diagnosis and misidentification. To enhance our comprehension of this uncommon cancer, more cases with detailed information are essential

Suicide rates among patients with first and second primary cancer

Abstract Aims With advancements in cancer treatments, the survival rates of patients with their first primary cancer (FPC) have increased, resulting in a rise in the number of patients with second primary cancer (SPC). However, there has been no assessment on the incidence of suicide among patients with SPC. This study assessed the occurrence of suicide among patients with SPC and compared them with that in patients with FPC. Methods This was a retrospective, population-based cohort study that followed patients with FPC and SPC diagnosed from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) 17 registries database between 1 January 2000 and 31 December 2019. Results For patients with SPC, an age of 85+ years at diagnosis was associated with a higher incidence of suicide death (HR, 1.727; 95% CI, 1.075–2.774), while the suicide death was not considerably different in the chemotherapy group (P > 0.05). Female genital system cancers (HR, 3.042; 95% CI, 1.819–6.361) accounted for the highest suicide death among patients with SPC. The suicide death distribution of patients with SPC over time indicated that suicide events mainly occurred within 5 to 15 years of diagnosis. Compared with patients with FPC, patients with SPC in general had a lower risk of suicide, but increased year by year. Conclusion The risk of suicide was reduced in patients with SPC compared with patients with FPC, but increased year by year. Therefore, oncologists and related health professionals need to provide continuous psychological support to reduce the incidence of suicide. The highest suicide death was found among patients with female genital system cancer

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe