A Homogenization Approach for Gradient-Dominated Stochastic Optimization

Gradient dominance property is a condition weaker than strong convexity, yet it sufficiently ensures global convergence for first-order methods even in non-convex optimization. This property finds application in various machine learning domains, including matrix decomposition, linear neural networks, and policy-based reinforcement learning (RL). In this paper, we study the stochastic homogeneous second-order descent method (SHSODM) for gradient-dominated optimization with $\alpha \in [1, 2]$ based on a recently proposed homogenization approach. Theoretically, we show that SHSODM achieves a sample complexity of $O(\epsilon^{-7/(2 \alpha) +1})$ for $\alpha \in [1, 3/2)$ and $\tilde{O}(\epsilon^{-2/\alpha})$ for $\alpha \in [3/2, 2]$. We further provide a SHSODM with a variance reduction technique enjoying an improved sample complexity of $O( \epsilon ^{-( 7-3\alpha ) /( 2\alpha )})$ for $\alpha \in [1,3/2)$. Our results match the state-of-the-art sample complexity bounds for stochastic gradient-dominated optimization without \emph{cubic regularization}. Since the homogenization approach only relies on solving extremal eigenvector problems instead of Newton-type systems, our methods gain the advantage of cheaper iterations and robustness in ill-conditioned problems. Numerical experiments on several RL tasks demonstrate the efficiency of SHSODM compared to other off-the-shelf methods

Industry 4.0-Oriented Turnkey Project: Rapid Configuration and Intelligent Operation of Manufacturing Systems

More extensive personalized product requirements and shorter product life cycles have put forward higher requirements for the rapid establishment, commissioning, and operation of corresponding manufacturing systems. However, the traditional manufacturing system development process is complicated, resulting in a longer delivery time. Many manufacturing enterprises, especially small and micro enterprises, may not have the necessary manufacturing knowledge or capabilities to meet these requirements. Therefore, it is essential to promote the construction of turnkey projects under the paradigm of Industry 4.0, parallelizing and integrating the existing manufacturing system development process based on mass manufacturing equipment to quickly provide turnkey solutions for manufacturing systems’ configuration and implementation for these enterprises. This paper aims to extract and refine the configuration and operation key views of the Industry 4.0-oriented Turnkey Project (I4TP) from Reference Architecture Model Industrie 4.0 (RAMI4.0) and use it to guide the development of key functional processes of turnkey projects to achieve rapid configuration and efficient operation management of manufacturing systems. The turnkey project platform in the Advanced Manufacturing Technology Center (AMTC) is taken as a demonstration case to provide a reference idea for the rapid configuration and intelligent operation of the turnkey manufacturing system

Promoted Photocharge Separation in 2D Lateral Epitaxial Heterostructure for Visible‐Light‐Driven CO2 Photoreduction

Photocarrier recombination remains a big barrier for the improvement of solar energy conversion efficiency. For 2D materials, construction of heterostructures represents an efficient strategy to promote photoexcited carrier separation via an internal electric field at the heterointerface. However, due to the difficulty in seeking two components with suitable crystal lattice mismatch, most of the current 2D heterostructures are vertical heterostructures and the exploration of 2D lateral heterostructures is scarce and limited. Here, lateral epitaxial heterostructures of BiOCl @ Bi2O3 at the atomic level are fabricated via sonicating‐assisted etching of Cl in BiOCl. This unique lateral heterostructure expedites photoexcited charge separation and transportation through the internal electric field induced by chemical bonding at the lateral interface. As a result, the lateral BiOCl @ Bi2O3 heterostructure demonstrates superior CO2 photoreduction properties with a CO yield rate of about 30 µmol g−1 h−1 under visible light illumination. The strategy to fabricate lateral epitaxial heterostructures in this work is expected to provide inspiration for preparing other 2D lateral heterostructures used in optoelectronic devices, energy conversion, and storage fields

Assessing public perception and willingness to pay for renewable energy in Pakistan through the theory of planned behavior

With growing urbanization and increasing world population, energy demand also increases. A significant portion of the world’s energy comes from fossil fuels, and these sources of energy are declining rapidly at the current consumption rate. There are also growing environmental concerns on the use of fossil fuels increasing greenhouse gas emissions. In this regard, renewable energy (RE) shows promising solutions which are both sustainable and environmentally friendly. Developed countries and leading organizations are investing heavily in the RE sector. However, the developing world has anxieties over social acceptability and people’s willingness to pay for renewable energy. This study is conducted in Pakistan to understand the public perception and willingness to pay. The Theory of Planned Behavior (TPB) was utilized with background factors such as awareness, perceived advantages, perceived challenges, and moral obligations to examine its influence on people’s willingness to pay. In addition to this, the study also assessed the indirect effects of background factors (awareness, perceived advantages, and perceived challenges) on willingness to pay through public attitude. Furthermore, the indirect relationship between background factors (awareness and moral obligation) and willingness to pay through subjective norms was also examined. A total of 512 samples were gathered from participants and were analyzed through partial least square–structural equation modeling (PLS-SEM) and SPSS. The study findings are very interesting and back up our hypotheses that the background factors (awareness, perceived advantages, and perceived challenges) are positively associated with public attitude and have an indirect effect on willingness to pay through public attitude. Similarly, variables such as awareness and moral obligation are negatively and positively associated with subjective norms, respectively. However, the variables, awareness and moral obligation, have no indirect relationship with willingness to pay through subjective norms. Additionally, the study reveals that the components (attitude and perceived behavior control) of TPB have a significantly positive effect on willingness to pay. The study also concludes that the participants having formal education and knowledge about climate change and renewable energy are inclined toward green energy and are willing to pay, and they are hardly influenced by others' opinions. Furthermore, the study also provides insights for policymakers, suggestions, and recommendations for the future

Slippery for scaling resistance in membrane distillation: a novel porous micropillared superhydrophobic surface

Scaling in membrane distillation (MD) is a key issue in desalination of concentrated saline water, where the interface property between the membrane and the feed become critical. In this paper, a slippery mechanism was explored as an innovative concept to understand the scaling behavior in membrane distillation for a soluble salt, NaCl. The investigation was based on a novel design of a superhydrophobic polyvinylidene fluoride (PVDF) membrane with micro-pillar arrays (MP-PVDF) using a micromolding phase separation (μPS) method. The membrane showed a contact angle of 166.0 ± 2.3° and the sliding angle of 15.8 ± 3.3°. After CF4 plasma treatment, the resultant membrane (CF4-MP-PVDF) showed a reduced sliding angle of 3.0o. In direct contact membrane distillation (DCMD), the CF4-MP-PVDF membrane illustrated excellent anti-scaling in concentrating saturated NaCl feed. Characterization of the used membranes showed that aggregation of NaCl crystals occurred on the control PVDF and MP-PVDF membranes, but not on the CF4-MP-PVDF membrane. To understand this phenomenon, a “slippery” theory was introduced and correlated the sliding angle to the slippery surface of CF4-MP-PVDF and its anti-scaling property. This work proposed a well-defined physical and theoretical platform for investigating scaling problems in membrane distillation and beyond

Tau Pathology in Parkinson's Disease

Tau protein—a member of the microtubule-associated protein family—is a key protein involved in many neurodegenerative diseases. Tau pathology in neurodegenerative diseases is characterized by pathological tau aggregation in neurofibrillary tangles (NFTs). Diseases with this typical pathological feature are called tauopathies. Parkinson's disease (PD) was not initially considered to be a typical tauopathy. However, recent studies have demonstrated increasing evidence of tau pathology in PD. A genome-wide association (GWA) study indicated a potential association between tauopathy and sporadic PD. The aggregation and deposition of tau were also observed in ~50% of PD brains, and it seems to be transported from neuron to neuron. The aggregation of NFTs, the abnormal hyperphosphorylation of tau protein, and the interaction between tau and alpha-synuclein may all contribute to the cell death and poor axonal transport observed in PD and Parkinsonism

The anti-biofilm effect of silver-nanoparticle-decorated quercetin nanoparticles on a multi-drug resistant Escherichia coli strain isolated from a dairy cow with mastitis

Background Escherichia coli is an important opportunistic pathogen that could cause inflammation of the udder in dairy cows resulting in reduced milk production and changes in milk composition and quality, and even death of dairy cows. Therefore, mastitis is the main health issue which leads to major economic losses on dairy farms. Antibiotics are routinely used for the treatment of bovine mastitis. The ability to form biofilm increases the antibiotic resistance of E. coli. Nanoparticles (NPs), a nanosized, safe, and highly cost-effective antibacterial agent, are potential biomedical tools. Given their antibacterial activities, silver nanoparticles (Ag NPs) have a broad range of applications. Methods In this study, we performed antibacterial activity assays, biofilm formation assays, scanning electron microscopy (SEM) experiments, and real-time reverse transcription PCR (RT-PCR) experiments to investigate the antibacterial and anti-biofilm effect of quercetin, Ag NPs, and Silver-nanoparticle-decorated quercetin nanoparticles (QA NPs) in E. coli strain ECDCM1. Results In this study, QA NPs, a composite material combining Ag NPs and the plant-derived drug component quercetin, exhibited stronger antibacterial and anti-biofilm properties in a multi-drug resistant E. coli strain isolated from a dairy cow with mastitis, compared to Ag NPs and Qe. Discussion This study provides evidence that QA NPs possess high antibacterial and anti-biofilm activities. They proved to be more effective than Ag NPs and Qe against the biofilm formation of a multi-drug resistant E. coli isolated from cows with mastitis. This suggests that QA NPs might be used as a potential antimicrobial agent in the treatment of bovine mastitis caused by E. coli

SENP1 regulates IFN-γ−STAT1 signaling through STAT3−SOCS3 negative feedback loop

Interferon-γ (IFN-γ) triggers macrophage for inflammation response by activating the intracellular JAK−STAT1 signaling. Suppressor of cytokine signaling 1 (SOCS1) and protein tyrosine phosphatases can negatively modulate IFN-γ signaling. Here, we identify a novel negative feedback loop mediated by STAT3−SOCS3, which is tightly controlled by SENP1 via de-SUMOylation of protein tyrosine phosphatase 1B (PTP1B), in IFN-γ signaling. SENP1-deficient macrophages show defects in IFN-γ signaling and M1 macrophage activation. PTP1B in SENP1-deficient macrophages is highly SUMOylated, which reduces PTP1B-induced de-phosphorylation of STAT3. Activated STAT3 then suppresses STAT1 activation via SOCS3 induction in SENP1-deficient macrophages. Accordingly, SENP1-deficient macrophages show reduced ability to resist Listeria monocytogenes infection. These results reveal a crucial role of SENP1-controlled STAT1 and STAT3 balance in macrophage polarization

A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems

The differentiation of pluripotent stem cells (PSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variabilities, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, PSC-to-cardiomyocyte (CM) differentiation is vulnerable to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), PSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial PSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor that can further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize PSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications

Experimental study on LBL beams

Six specimens were made and tested to study the mechanical properties of LBL beams. The mean ultimate loading value is 68.39 MPa with a standard deviation of 6.37 MPa, giving a characteristic strength (expected to be exceeded by 95% of specimens) of 57.91 MPa, and the mean ultimate deflection is 53.3 mm with a standard deviation of 5.5 mm, giving the characteristic elastic modulus of 44.3 mm. The mean ultimate bending moment is 20.18 kN.m with a standard deviation of 1.88 kN.m, giving the characteristic elastic modulus of 17.08 kN.m. The mean elastic modulus is 9688 MPa with a standard deviation of 1765 MPa, giving the characteristic elastic modulus of 6785 MPa, and the mean modulus of rupture is 93.3 MPa with a standard deviation of 8.6 MPa, giving the characteristic elastic modulus of 79.2 MPa. The strain across the cross-section for all LBL beams is basically linear throughout the loading process, following standard beam theory