Content Distribution by Multiple Multicast Trees and Intersession Cooperation: Optimal Algorithms and Approximations

In traditional massive content distribution with multiple sessions, the sessions form separate overlay networks and operate independently, where some sessions may suffer from insufficient resources even though other sessions have excessive resources. To cope with this problem, we consider the universal swarming approach, which allows multiple sessions to cooperate with each other. We formulate the problem of finding the optimal resource allocation to maximize the sum of the session utilities and present a subgradient algorithm which converges to the optimal solution in the time-average sense. The solution involves an NP-hard subproblem of finding a minimum-cost Steiner tree. We cope with this difficulty by using a column generation method, which reduces the number of Steiner-tree computations. Furthermore, we allow the use of approximate solutions to the Steiner-tree subproblem. We show that the approximation ratio to the overall problem turns out to be no less than the reciprocal of the approximation ratio to the Steiner-tree subproblem. Simulation results demonstrate that universal swarming improves the performance of resource-poor sessions with negligible impact to resource-rich sessions. The proposed approach and algorithm are expected to be useful for infrastructure-based content distribution networks with long-lasting sessions and relatively stable network environment

China's uncertain demographic present and future

This paper applies methods of probabilistic population forecasting to assess the range of uncertainty of China’s future population trends. Unlike previous applications of probabilistic population projections that consider stochastic future fertility, mortality and migration, this paper will also account for the significant uncertainty of China’s current fertility level (with published figures ranging from 1.2 to 2.3) and the related uncertainties about the sex ratio at birth (with estimates from 1.06 to above 1.2) and the size of the youngest cohorts in the 2000 census. The model applied in this paper will be based on assumed uncertainty ranges for current conditions, in addition to the probabilistic treatment of future trends. Given the sheer size of China’s population, these significant uncertainties about current conditions are of high importance not only for the future population of China but also for considerations on a global scale.

Effectiveness of folic acid fortified flour for prevention of neural tube defects in a high risk region

Despite efforts to tackle folate deficiency and Neural Tube Defects (NTDs) through folic acid fortification, its implementation is still lacking where it is needed most, highlighting the need for studies that evaluate the effectiveness of folic acid fortified wheat flour in a poor, rural, high-risk, NTD region of China. One of the most affected regions, Shanxi Province, was selected as a case study. A community intervention was carried out in which 16,648 women of child-bearing age received fortified flour (eight villages) and a control group received ordinary flour (three villages). NTD birth prevalence and biological indicators were measured two years after program initiation at endline only. The effect on the NTD burden was calculated using the disability-adjusted life years (DALYs) method. In the intervention group, serum folate level was higher than in the control group. NTDs in the intervention group were 68.2% lower than in the control group (OR = 0.313, 95% CI = 0.207-0473, p < 0.001). In terms of DALYs, burden in intervention group was approximately 58.5% lower than in the control group. Flour fortification was associated with lower birth prevalence and burden of NTDs in economically developing regions with a high risk of NTDs. The positive findings confirm the potential of fortification when selecting an appropriate food vehicle and target region. As such, this study provides support for decision makers aiming for the implementation of (mandatory) folic acid fortification in China

A robust potential-based contact force solution approach for discontinuous deformation analysis of irregular convex polygonal block/particle systems

Contact interaction of two bodies can be modeled using the penalty function approach while its accuracy and robustness are directly associated with the geometry of contact bodies. Particularly, in the research fields of rock mechanics, we need to treat polygonal shapes such as mineral grains/particles at a mesoscale and rock blocks at a macroscale. The irregular shapes (e.g., polygons with small angles or small edges) pose challenges to traditional contact solution approach in terms of algorithmic robustness and complexity. This paper proposed a robust potential-based penalty function approach to solve contact of polygonal particles/block. An improved potential function is proposed considering irregular polygonal shapes. A contact detection procedure based on the entrance block concept is presented, followed by a numerical integral algorithm to compute the contact force. The proposed contact detection approach is implemented into discontinuous deformation analysis with an explicit formulation. The accuracy and robustness of the proposed contact detection approach are verified by benchmarking examples. The potential of the proposed approach in analysis of kinetic behavior of complex polygonal block systems is shown by two application examples. It can be applied in any discontinuous computation models using stepwise contact force-based solution procedures. © 2020, The Author(s)

Assessing the Therapeutic Effect of 630 nm Light-emitting Diodes Irradiation on the Recovery of Exercise-induced Hand Muscle Fatigue with Surface Electromyogram

This paper aims to investigate the effect of light emitting diode therapy (LEDT) on exercise-induced hand muscle fatigue by measuring the surface electromyography (sEMG) of flexor digitorum superficialis. Ten healthy volunteers were randomly placed in the equal sized LEDT group and control group. All subjects performed a sustained fatiguing isometric contraction with the combination of four fingertips except thumb at 30% of maximal voluntary contraction (MVC) until exhaustion. The active LEDT or an identical passive rest therapy was then applied to flexor digitorum superficialis. Each subject was required to perform a re-fatigue task immediately after therapy which was the same as the pre-fatigue task. Average rectified value (ARV) and fractal dimension (FD) of sEMG were calculated. ARV and FD were significantly different between active LEDT and passive rest groups at 20%–50%, 70%–80%, and 100% of normalized contraction time (P \u3c 0.05 ). Compared to passive rest, active LEDT induced significantly smaller increase in ARV values and decrease in FD values, which shows that LEDT is effective on the recovery of muscle fatigue. Our preliminary results also suggest that ARV and FD are potential replacements of biochemical markers to assess the effects of LEDT on muscle fatigue

Rhodioloside inhibits apoptosis of hippocampal neurons exposed to sevoflurane via cAMP/PKA signaling pathway

Purpose: Neural injury affects patients after using inhalational anesthetics such as sevoflurane. Rhodioloside, a compound which is obtained from the Rhodiola rosea plant has been implicated to be the most commonly used psychostimulant that can improve a range of conditions. The study was aimed at finding the molecular mechanism underlying the Rhodioloside treatment of sevoflurane-injured hippocampal neurons.Methods: Main hippocampal neurons, secluded from Sprague Dawley embryonic rats were employed to create an injury model using 3 % sevoflurane. The sevoflurane-injured hippocampal neurons were treated with varying concentrations (10, 20, 40 and 80 μM/ml) of Rhodioloside to create different experimental groups: RHSD10+SEV, RHSD20+SEV, RHSD40+SEV, RHSD80+SEV, while untreated cells were considered as the Control group. Cell viability was identified using the CCK-8 assay. The CFSE assay was used to verify the promotion function of Rhodioloside on cell differentiation of neurons. FCM assay was employed to determine cell proliferation and apoptosis. Expression levels of apoptosisrelated factors, like Caspase-3, Bcl-2 and Bax were examined by RT-qPCR, while Western blot was used to measure phosphorylation of PKA.Results: Rhodioloside stimulated cell viability and prevented cell apoptosis in sevoflurane-injured hippocampal neurons in doses between 10-80 μM. The apoptosis-inhibitory effect of Rhodioloside was observed to be through cAMP/PKA pathway activation. Also, expression levels of Bcl-2, and PKA were enhanced and the level of Caspase-3 and Bax was reduced in a dose-dependent pattern. The PKA inhibitor reversed the above observation in the 40 μM Rhodioloside-treatment.Conclusion: Rhodioloside promoted cell viability and prevented apoptosis of primary hippocampal neurons injured by sevoflurane, through cAMP/PKA pathway activation. Inhibition of PKA network deteriorated the function of Rhodioloside by stimulating cell apoptosis. Our findings present a novel evidence that Rhodioloside could attenuate neurotoxicity of inhalational anesthetics. Keywords: Cell apoptosis, cAMP/PKA pathway, Hippocampal neurons, Rhodioloside, Sevofluran

Bitformer: An efficient Transformer with bitwise operation-based attention for Big Data Analytics at low-cost low-precision devices

In the current landscape of large models, the Transformer stands as a cornerstone, playing a pivotal role in shaping the trajectory of modern models. However, its application encounters challenges attributed to the substantial computational intricacies intrinsic to its attention mechanism. Moreover, its reliance on high-precision floating-point operations presents specific hurdles, particularly evident in computation-intensive scenarios such as edge computing environments. These environments, characterized by resource-constrained devices and a preference for lower precision, necessitate innovative solutions. To tackle the exacting data processing demands posed by edge devices, we introduce the Bitformer model, an inventive extension of the Transformer paradigm. Central to this innovation is a novel attention mechanism that adeptly replaces conventional floating-point matrix multiplication with bitwise operations. This strategic substitution yields dual advantages. Not only does it maintain the attention mechanism's prowess in capturing intricate long-range information dependencies, but it also orchestrates a profound reduction in the computational complexity inherent in the attention operation. The transition from an $O(n^2d)$ complexity, typical of floating-point operations, to an $O(n^2T)$ complexity characterizing bitwise operations, substantiates this advantage. Notably, in this context, the parameter $T$ remains markedly smaller than the conventional dimensionality parameter $d$. The Bitformer model in essence endeavors to reconcile the indomitable requirements of modern computing landscapes with the constraints posed by edge computing scenarios. By forging this innovative path, we bridge the gap between high-performing models and resource-scarce environments, thus unveiling a promising trajectory for further advancements in the field