Weighted AdaGrad with Unified Momentum

Integrating adaptive learning rate and momentum techniques into SGD leads to a large class of efficiently accelerated adaptive stochastic algorithms, such as Nadam, AccAdaGrad, \textit{etc}. In spite of their effectiveness in practice, there is still a large gap in their theories of convergences, especially in the difficult non-convex stochastic setting. To fill this gap, we propose \emph{weighted AdaGrad with unified momentum}, dubbed AdaUSM, which has the main characteristics that (1) it incorporates a unified momentum scheme which covers both the heavy ball momentum and the Nesterov accelerated gradient momentum; (2) it adopts a novel weighted adaptive learning rate that can unify the learning rates of AdaGrad, AccAdaGrad, Adam, and RMSProp. Moreover, when we take polynomially growing weights in AdaUSM, we obtain its $\mathcal{O}(\log(T)/\sqrt{T})$ convergence rate in the non-convex stochastic setting. We also show that the adaptive learning rates of Adam and RMSProp correspond to taking exponentially growing weights in AdaUSM, which thereby provides a new perspesctive for understanding Adam and RMSProp. Lastly, comparative experiments of AdaUSM against SGD with momentum, AdaGrad, AdaEMA, Adam, and AMSGrad on various deep learning models and datasets are also provided

Integrative transcriptomic profiling of mRNA, miRNA, circRNA, and lncRNA in alveolar macrophages isolated from PRRSV-infected porcine

IntroductionThe porcine reproductive and respiratory syndrome virus (PRRSV) continues to pose a significant threat to the global swine industry, attributed largely to its immunosuppressive properties and the chronic nature of its infection. The absence of effective vaccines and therapeutics amplifies the urgency to deepen our comprehension of PRRSV’s intricate pathogenic mechanisms. Previous transcriptomic studies, although informative, are partially constrained by their predominant reliance on in vitro models or lack of long-term infections. Moreover, the role of circular RNAs (circRNAs) during PRRSV invasion is yet to be elucidated.MethodsIn this study, we employed an in vivo approach, exposing piglets to a PRRSV challenge over varied durations of 3, 7, or 21 days. Subsequently, porcine alveolar macrophages were isolated for a comprehensive transcriptomic investigation, examining the expression patterns of mRNAs, miRNAs, circRNAs, and long non-coding RNAs (lncRNAs).ResultsDifferentially expressed RNAs from all four categories were identified, underscoring the dynamic interplay among these RNA species during PRRSV infection. Functional enrichment analyses indicate that these differentially expressed RNAs, as well as their target genes, play a pivotal role in immune related pathways. For the first time, we integrated circRNAs into the lncRNA-miRNA-mRNA relationship, constructing a competitive endogenous RNA (ceRNA) network. Our findings highlight the immune-related genes, CTLA4 and SAMHD1, as well as their associated miRNAs, lncRNAs, and circRNAs, suggesting potential therapeutic targets for PRRS. Importantly, we corroborated the expression patterns of selected RNAs through RT-qPCR, ensuring consistency with our transcriptomic sequencing data.DiscussionThis study sheds lights on the intricate RNA interplay during PRRSV infection and provides a solid foundation for future therapeutic strategizing

Mechanisms and recent advances in the diagnosis and treatment of nitrous oxide-induced peripheral neuropathy: a narrative review

Under standard conditions, nitrous oxide (N2O) manifests as a colorless, odorless gas with a mildly sweet taste. The compound finds applications in various fields, including its use as an aerosol propellants, an accelerant in motor racing, and an anesthetic in surgical procedures and dentistry. Unfortunately, the recreational misuse of N2O has become prevalent among young individuals due to its euphoric and hallucinogenic effects. Compounding this issue is the fact that nitrous oxide can be easily obtained from over-the-counter household items, facilitating its non-medical use. The global community has witnessed a surge in the recreational utilization of nitrous oxide gas in recent years. Despite the widespread non-medical abuse of N2O, there remains inadequate understanding of the potential adverse effects resulting from exposure to it. This paper provides an overview of management findings, laboratory and electrodiagnostic characteristics, as well as clinical presentations associated with neurological disorders induced by nitrous oxide usage

Manufacturing 3-D Lithium-Ion Batteries with Interpenetrating Lattice Electrodes

3-D lithium-ion batteries have been proven to exhibit a higher energy density while minimizing power loss compared to the standard, layer-by-layer constructed 2-D lithium-ion batteries. This thesis explores the implementation of additive manufacturing in the process of constructing the proposed 3-D battery due to its capability of architecting materials with high accuracy and tunability. A 3-D lithium-ion battery backbone was created using a 2-step process, in which the first step 3-D printed the overall structure as a polymer, and the second step sputtered gold onto the polymer for conductive properties. The 3-D printed battery backbone consisted of two interpenetrating lattices made of post-cured PR48 resin that would serve as the anode and cathode, while the electrolyte would fill the space between the two electrodes. During the sputtering process, the polymer structure was rotated 6 times to guarantee that the sputtering will be conformal throughout the lattice. Electrodeposition was used to generate a LiCoO2 anode and a Li cathode. The electrodeposition of the lithium cobalt oxide cathode onto the lattice structure was proven to be unsuccessful due to the low thermal stability and high reactivity of the 3-D printed polymer when submerged into the electrolyte, consisting of KOH at 260 °C. Results indicate that the uniform electrodeposition of the lithium anode onto the lattice structure was successful using a 1s on, 1s off pulse current for a 60-minute duration. Using a titanium and gold layer proved to increase the uniformity of the coating. However, due to the failure of the lithium cobalt oxide electrodeposition, a different backbone structure may need to be considered. Having two separate structures serving as the anode and cathode (and later combining them into one structure) as opposed to both electrodes being on one structure may be beneficial. This allows for the cathode to be altered without altering both electrodes, allowing more flexibility to coat the structure with lithium cobalt oxide

PSANet: Pyramid Splitting and Aggregation Network for 3D Object Detection in Point Cloud

3D object detection in LiDAR point clouds has been extensively used in autonomous driving, intelligent robotics, and augmented reality. Although the one-stage 3D detector has satisfactory training and inference speed, there are still some performance problems due to insufficient utilization of bird’s eye view (BEV) information. In this paper, a new backbone network is proposed to complete the cross-layer fusion of multi-scale BEV feature maps, which makes full use of various information for detection. Specifically, our proposed backbone network can be divided into a coarse branch and a fine branch. In the coarse branch, we use the pyramidal feature hierarchy (PFH) to generate multi-scale BEV feature maps, which retain the advantages of different levels and serves as the input of the fine branch. In the fine branch, our proposed pyramid splitting and aggregation (PSA) module deeply integrates different levels of multi-scale feature maps, thereby improving the expressive ability of the final features. Extensive experiments on the challenging KITTI-3D benchmark show that our method has better performance in both 3D and BEV object detection compared with some previous state-of-the-art methods. Experimental results with average precision (AP) prove the effectiveness of our network

Diagenetic characteristics and microscopic pore evolution of deep shale gas reservoirs in Longmaxi Formation, Southeastern Sichuan basin, China

The Lower Silurian Longmaxi Formation is the favorable target area for deep shale gas exploration and development in southeastern Sichuan Basin. Based on whole-rock X-ray diffraction analysis, scanning electron microscope, reservoir evolution thermal simulation experiment and nitrogen adsorption experiment, the diagenetic characteristics of deep shale reservoir in Longmaxi Formation were analyzed, and the reservoir pore evolution law was clarified. The results show that: ①The diagenetic minerals of the deep shale in the Longmaxi Formation are mainly quartz and clay minerals, with a small amount of carbonate minerals and feldspar. The primary inorganic pores are mainly controlled by mechanical compaction and cementation (quartz, carbonate, clay, pyrite). The organic pores are mainly controlled by the thermal maturity of organic matter, dissolution and later compaction. ②In the process of thermal simulation experiment, the organic pores of shale show a process of change from scratch, from small to large and then from large to small. Later, the organic matter is affected by compaction and graphitization, and the volume of micropores and mesopores begins to decrease. ③The shale pores of Longmaxi Formation have undergone several evolutionary stages. In the early stage of diagenesis, compaction caused a large number of inorganic pores to disappear. In the middle stage of diagenesis, kerogen hydrocarbon generation occupied pores, dissolution and cementation transformed pores. In the late diagenetic period, liquid hydrocarbon cracking gas and pressurization promote the development of organic pores

Smart MXene‐based bioelectronic devices as wearable health monitor for sensing human physiological signals

Abstract Biosafe wearable healthcare monitor has attracted significant attention owing to their applicability to wearable electronics. However, the narrow sensing range and poor response limit the application of flexible devices for comprehensive monitoring of human health‐related physiological signals (i.e., pulse diagnosis). Critical challenges remain in the development of biocompatible materials and the design of flexible bio‐integrated platforms for these purposes, targeting performance approaching those of conventional wafer‐based technologies and long‐term operational stability. In this context, this work presents a robust and flexible MXene/polydopamine (PDA)‐composite‐film‐based pressure sensor in a portable/wearable fashion, which establishes a unique intercalated spherical‐like PDA molecules structure, thereby resulting in excellent sensing performance. The MXene/PDA‐based pressure sensor has sensitivity of up to 138.8 kPa−1 in the pressure range of 0.18–6.20 kPa with fast response and recovery speed (t1 < 100 ms; t2< 50 ms). Associated embodiment involves real‐time precise measurements of a variety of health‐related physiological signals, ranging from wrist pulse, to finger motions, to vocalization and to facial expressions, with high sensitivity and accuracy. Studies on human subjects establish the clinical significance of these devices for future opportunities of health monitoring and intelligent control to predict and diagnose diseases