Generalized Activation via Multivariate Projection

Activation functions are essential to introduce nonlinearity into neural networks, with the Rectified Linear Unit (ReLU) often favored for its simplicity and effectiveness. Motivated by the structural similarity between a shallow Feedforward Neural Network (FNN) and a single iteration of the Projected Gradient Descent (PGD) algorithm, a standard approach for solving constrained optimization problems, we consider ReLU as a projection from R onto the nonnegative half-line R+. Building on this interpretation, we extend ReLU by substituting it with a generalized projection operator onto a convex cone, such as the Second-Order Cone (SOC) projection, thereby naturally extending it to a Multivariate Projection Unit (MPU), an activation function with multiple inputs and multiple outputs. We further provide mathematical proof establishing that FNNs activated by SOC projections outperform those utilizing ReLU in terms of expressive power. Experimental evaluations on widely-adopted architectures further corroborate MPU's effectiveness against a broader range of existing activation functions

A multi-user selective undo/redo approach for collaborative CAD systems

AbstractThe engineering design process is a creative process, and the designers must repeatedly apply Undo/Redo operations to modify CAD models to explore new solutions. Undo/Redo has become one of most important functions in interactive graphics and CAD systems. Undo/Redo in a collaborative CAD system is also very helpful for collaborative awareness among a group of cooperative designers to eliminate misunderstanding and to recover from design error. However, Undo/Redo in a collaborative CAD system is much more complicated. This is because a single erroneous operation is propagated to other remote sites, and operations are interleaved at different sites. This paper presents a multi-user selective Undo/Redo approach in full distributed collaborative CAD systems. We use site ID and State Vectors to locate the Undo/Redo target at each site. By analyzing the composition of the complex CAD model, a tree-like structure called Feature Combination Hierarchy is presented to describe the decomposition of a CAD model. Based on this structure, the dependency relationship among features is clarified. B-Rep re-evaluation is simplified with the assistance of the Feature Combination Hierarchy. It can be proven that the proposed Undo/Redo approach satisfies the intention preservation and consistency maintenance correctness criteria for collaborative systems

Cost-Effectiveness Analysis of Early Reading Programs: A Demonstration With Recommendations for Future Research

We review the value of cost-effectiveness analysis for evaluation and decision making with respect to educational programs and discuss its application to early reading interventions. We describe the conditions for a rigorous cost-effectiveness analysis and illustrate the challenges of applying the method in practice, providing examples of programs for which we have estimated costs, but find effectiveness data lacking in comparability. We provide a demonstration of how cost-effectiveness analysis can be applied to two early reading programs: the Wilson Reading System and Corrective Reading. We use existing effectiveness data from an experimental evaluation in which the programs were implemented under similar conditions and the use of common outcomes measures for both programs yielded data that are comparable. We combine these data with cost data we collected using the ingredients method to calculate cost-effectiveness ratios for the alphabetics domain. A complete picture of the relative cost-effectiveness of each program could be provided if effectiveness metrics were available for fluency, vocabulary, and comprehension. We highlight the obstacles to applying cost-effectiveness analysis more frequently and recommend strategies for improving the availability of the requisite data

Evaluating the efficacy of mesenchymal stem cells for diabetic neuropathy: A systematic review and meta-analysis of preclinical studies

Diabetic neuropathy affects nearly half of all diabetics and poses a significant threat to public health. Recent preclinical studies suggest that mesenchymal stem cells (MSCs) may represent a promising solution for the treatment of diabetic neuropathy. However, an objective assessment of the preclinical effectiveness of MSCs is still pending. We conducted a comprehensive search of PubMed, Web of Science, Embase, and Cochrane library to identify preclinical studies that investigate the effects of MSCs on diabetic neuropathy up until 15 September 2023. Outcome indicators consisted of motor and sensory nerve conduction velocities, intra-epidermal nerve fiber density, sciatic nerve blood flow, capillary-to-muscle fiber ratio, neurotrophic factors, angiogenic factors and inflammatory cytokines. The literature review and meta-analysis were conducted independently by two researchers. 23 studies that met the inclusion criteria were included in this system review for qualitative and quantitative analysis. Pooled analyses indicated that MSCs exhibited an evident benefit in diabetic neuropathy in terms of motor (SMD = 2.16, 95% CI: 1.71–2.61) and sensory nerve conduction velocities (SMD = 2.93, 95% CI: 1.78–4.07), intra-epidermal nerve fiber density (SMD = 3.17, 95% CI: 2.28–4.07), sciatic nerve blood flow (SMD = 2.02, 95% CI: 1.37–2.66), and capillary-to-muscle fiber ratio (SMD = 2.28, 95% CI: 1.55 to 3.01, p < 0.00001). Furthermore, after MSC therapy, the expressions of neurotrophic and angiogenic factors increased significantly in most studies, while the levels of inflammatory cytokines were significantly reduced. The relevance of this review relies on the fact that summarizes an extensive body of work entailing substantial preclinical evidence that supports the efficacy of MSCs in mitigating diabetic neuropathy. While MSCs emerge as a promising potential treatment for diabetic neuropathy, further research is essential to elucidate the underlying mechanisms and the best administration strategy for MSCs

Hidden Real Topology and Unusual Magnetoelectric Responses in Monolayer Antiferromagnetic Cr2_2Se2_2O

Recently, the real topology has been attracting widespread interest in two dimensions (2D). Here, based on first-principles calculations and theoretical analysis, we reveal the monolayer Cr$_2$Se$_2$O (ML-CrSeO) as the first material example of a 2D antiferromagnetic (AFM) real Chern insulator (RCI) with topologically protected corner states. Unlike previous RCIs, we find that the real topology of the ML-CrSeO is rooted in one certain mirror subsystem of the two spin channels, and can not be directly obtained from all the valence bands in each spin channel as commonly believed. In particular, due to antiferromagnetism, the corner modes in ML-CrSeO exhibit strong corner-contrasted spin polarization, leading to spin-corner coupling (SCC). This SCC enables a direct connection between spin space and real space. Consequently, large and switchable net magnetization can be induced in the ML-CrSeO nanodisk by electrostatic means, such as potential step and in-plane electric field, and the corresponding magnetoelectric responses behave like a sign function, distinguished from that of the conventional multiferroic materials. Our work considerably broadens the candidate range of RCI materials, and opens up a new direction for topo-spintronics and 2D AFM materials research

Copper binding in IscA inhibits iron-sulphur cluster assembly in Escherichia coli

© 2014 John Wiley & Sons Ltd. Among the iron-sulphur cluster assembly proteins encoded by gene cluster iscSUA-hscBA-fdx in Escherichia coli, IscA has a unique and strong iron binding activity and can provide iron for iron-sulphur cluster assembly in proteins in vitro. Deletion of IscA and its paralogue SufA results in an E. coli mutant that fails to assemble [4Fe-4S] clusters in proteins under aerobic conditions, suggesting that IscA has a crucial role for iron-sulphur cluster biogenesis. Here we report that among the iron-sulphur cluster assembly proteins, IscA also has a strong and specific binding activity for Cu(I) in vivo and in vitro. The Cu(I) centre in IscA is stable and resistant to oxidation under aerobic conditions. Mutation of the conserved cysteine residues that are essential for the iron binding in IscA abolishes the copper binding activity, indicating that copper and iron may share the same binding site in the protein. Additional studies reveal that copper can compete with iron for the metal binding site in IscA and effectively inhibits the IscA-mediated [4Fe-4S] cluster assembly in E. coli cells. The results suggest that copper may not only attack the [4Fe-4S] clusters in dehydratases, but also block the [4Fe-4S] cluster assembly in proteins by targeting IscA in cells. Copyrigh

Phage family classification under Caudoviricetes: A review of current tools using the latest ICTV classification framework

Bacteriophages, which are viruses infecting bacteria, are the most ubiquitous and diverse entities in the biosphere. There is accumulating evidence revealing their important roles in shaping the structure of various microbiomes. Thanks to (viral) metagenomic sequencing, a large number of new bacteriophages have been discovered. However, lacking a standard and automatic virus classification pipeline, the taxonomic characterization of new viruses seriously lag behind the sequencing efforts. In particular, according to the latest version of ICTV, several large phage families in the previous classification system are removed. Therefore, a comprehensive review and comparison of taxonomic classification tools under the new standard are needed to establish the state-of-the-art. In this work, we retrained and tested four recently published tools on newly labeled databases. We demonstrated their utilities and tested them on multiple datasets, including the RefSeq, short contigs, simulated metagenomic datasets, and low-similarity datasets. This study provides a comprehensive review of phage family classification in different scenarios and a practical guidance for choosing appropriate taxonomic classification pipelines. To our best knowledge, this is the first review conducted under the new ICTV classification framework. The results show that the new family classification framework overall leads to better conserved groups and thus makes family-level classification more feasible