FedLion: Faster Adaptive Federated Optimization with Fewer Communication

In Federated Learning (FL), a framework to train machine learning models across distributed data, well-known algorithms like FedAvg tend to have slow convergence rates, resulting in high communication costs during training. To address this challenge, we introduce FedLion, an adaptive federated optimization algorithm that seamlessly incorporates key elements from the recently proposed centralized adaptive algorithm, Lion (Chen et al. 2o23), into the FL framework. Through comprehensive evaluations on two widely adopted FL benchmarks, we demonstrate that FedLion outperforms previous state-of-the-art adaptive algorithms, including FAFED (Wu et al. 2023) and FedDA. Moreover, thanks to the use of signed gradients in local training, FedLion substantially reduces data transmission requirements during uplink communication when compared to existing adaptive algorithms, further reducing communication costs. Last but not least, this work also includes a novel theoretical analysis, showcasing that FedLion attains faster convergence rate than established FL algorithms like FedAvg.Comment: ICASSP 202

Physiology and Pathophysiology of CLC-1: Mechanisms of a Chloride Channel Disease, Myotonia

The CLC-1 chloride channel, a member of the CLC-channel/transporter family, plays important roles for the physiological functions of skeletal muscles. The opening of this chloride channel is voltage dependent and is also regulated by protons and chloride ions. Mutations of the gene encoding CLC-1 result in a genetic disease, myotonia congenita, which can be inherited as an autosmal dominant (Thomsen type) or an autosomal recessive (Becker type) pattern. These mutations are scattered throughout the entire protein sequence, and no clear relationship exists between the inheritance pattern of the mutation and the location of the mutation in the channel protein. The inheritance pattern of some but not all myotonia mutants can be explained by a working hypothesis that these mutations may exert a “dominant negative” effect on the gating function of the channel. However, other mutations may be due to different pathophysiological mechanisms, such as the defect of protein trafficking to membranes. Thus, the underlying mechanisms of myotonia are likely to be quite diverse, and elucidating the pathophysiology of myotonia mutations will require the understanding of multiple molecular/cellular mechanisms of CLC-1 channels in skeletal muscles, including molecular operation, protein synthesis, and membrane trafficking mechanisms

Embryo splitting can increase the quantity but not the quality of blastocysts

AbstractObjectiveIn this study, we investigated the developmental potential of single blastomeres that were obtained from 4-cell mice embryos that were split during the blastocyst stage.Materials and MethodsImprinting Control Region (ICR) mice (age: 6–8 weeks), were superovulated and mated with a single fertile male of the same strain. We obtained 2-cell embryos that were then cultured in 4 groups (×4) with Human tubal fluid (HTF) supplemented with 12% fetal bovine serum. When these embryos reached the 4-cell stage, their zonae pellucidae were removed and every single blastomere was isolated by repeated pipetting with Ca/Mg2+-free medium. The isolated blastomeres (study group) and the intact embryos (control group) were then cultured to determine the blastocyst formation rate and quality.ResultsWe collected a total of 936 embryos from 524 morphologically intact, top-grade embryos in the 4-cell stage from 80 stimulated mice. We used 356 of these embryos to isolate the blastomeres. The remaining 168 embryos were cultured as controls. A total of 1312 single blastomeres were obtained and cultured in vitro. Among these, 620 blastocysts were harvested from the original embryos compared with 136 blastocysts that were harvested from the control group. The overall blastocyst formation rate was 174.2% (620 blastocysts from 356 embryos) for the study group compared with 81.5% (136 blastocysts from 168 embryos) for the control group. The study group was 43.3% (268 of 620) top-grade blastocysts compared with 91% (152 of 168) of the control group. Taken together, the percentage of top-grade blastocysts obtained per original embryo in the split group was 75.4% (174.2%×43.3%) compared with 74.2% (81.5%×91%) for the control group.ConclusionsEmbryo splitting can increase the number of blastocysts. However, the percentage of available top-grade blastocysts is the same compared with nonsplit embryos. Embryo splitting may not be a cost-effective technique for the generation of high-quality mouse blastocysts

Improvement on thermal performance of a disk-shaped miniature heat pipe with nanofluid

The present study aims to investigate the effect of suspended nanoparticles in base fluids, namely nanofluids, on the thermal resistance of a disk-shaped miniature heat pipe [DMHP]. In this study, two types of nanoparticles, gold and carbon, in aqueous solution are used respectively. An experimental system was set up to measure the thermal resistance of the DMHP with both nanofluids and deionized [DI] water as the working medium. The measured results show that the thermal resistance of DMHP varies with the charge volume and the type of working medium. At the same charge volume, a significant reduction in thermal resistance of DMHP can be found if nanofluid is used instead of DI water

A New Method for Calculating Viscosity and Solubility of Lubricant- Refrigerant Mixtures

A new model was developed to determine viscosity and solubility of lubricant-refrigerant mixture, using concepts from lattice model in liquid state, reaction rate theory for viscosity, and local composition theory. The computing results from our new model showed high degree of accuracy, and are comparable to the results from NRTL model and Flory-Huggins model. Various type of POE lubricants (viscosity ranges from 68~220cst) in R134a refrigerant have been fitted for the new model to describe the viscosity and pressure of binary systems. The tests were conducted in temperature ranging from 0? to 100?. Typical average absolute deviation (AAD%) of these calculation results in the model is between 1.0~3.5%

Ground Reaction Forces of Dart-Throwing at Different Target Heights

The purpose of the study was to explore whether dart players produce different lower limb control strategies when throwing darts at spatially separated targets in the vertical direction. Eight experienced darts players (height 1.75±0.04 m, mass 83.4±19.3 kg) participated in this research. Two Multi-Axis Force Plates were used to collect GRF data on both legs and synchronized with a Motion Capture System. The participants threw darts at three targets at different heights, which were the upper section of the 20 point area, bullseye and lower section of the 3 point area. The results showed that the amplitude of anterior-posterior GRF of their front legs were significantly different when darts was thrown at the 20 zone, bullseye and 3 zone respectively. Our study found that the braking forces of the front legs were greater when a dart was being thrown at the highest target (20 points) than when it was being thrown at the lowest target (3 points)

Missing Data Imputation with Graph Laplacian Pyramid Network

Data imputation is a prevalent and important task due to the ubiquitousness of missing data. Many efforts try to first draft a completed data and second refine to derive the imputation results, or "draft-then-refine" for short. In this work, we analyze this widespread practice from the perspective of Dirichlet energy. We find that a rudimentary "draft" imputation will decrease the Dirichlet energy, thus an energy-maintenance "refine" step is in need to recover the overall energy. Since existing "refine" methods such as Graph Convolutional Network (GCN) tend to cause further energy decline, in this work, we propose a novel framework called Graph Laplacian Pyramid Network (GLPN) to preserve Dirichlet energy and improve imputation performance. GLPN consists of a U-shaped autoencoder and residual networks to capture global and local detailed information respectively. By extensive experiments on several real-world datasets, GLPN shows superior performance over state-of-the-art methods under three different missing mechanisms. Our source code is available at https://github.com/liguanlue/GLPN.Comment: 12 pages, 5 figure