Dual problems for weak and quasi approximation properties

AbstractIt is shown that for the separable dual X∗ of a Banach space X if X∗ has the weak approximation property, then X has the metric quasi approximation property. Using this it is shown that for the separable dual X∗ of a Banach space X the quasi approximation property and metric quasi approximation property are inherited from X∗ to X and for a separable and reflexive Banach space X, X having the weak approximation property, bounded weak approximation property, quasi approximation property, metric weak approximation property, and metric quasi approximation property are equivalent. Also it is shown that the weak approximation property, bounded weak approximation property, and quasi approximation property are not inherited from a Banach space X to X∗

Multifunctional heteronanomat-mediated electrodes for high-performance/flexible lithium-ion batteries

Department of Energy EngineeringWith the rapid growth of the demands for portable electronics, electric vehicles (EVs) with high-energy density and mechanical flexibility, the importance of rechargeable power sources is on the steady rise. Among a variety of rechargeable systems, lithium-ion batteries (LIBs) are the most suitable energy storage system. It is well known that the higher energy density of LIBs comes from the higher storage capacity value of electrode active materials and electrode architecture. Unfortunately, almost all the conventional electrode architecture suffers several drawbacks. First, the random stacking of electrode components such as active materials, conductive additives, and polymeric binders causes irregular electron/ion transport pathway through-thickness direction. Second, the incomplete electron/ion transport pathway increases unnecessary electrochemical polarization. Third, the non-faradaic materials such as metallic current collector, conductive additives and polymeric binders account for a great part of the total mass of electrode, resulting in lower areal capacity and energy densities of the LIBs. To overcome these unavoidable challenges, a new strategy to gain uniform ion/electron pathway is needed. In this dissertation, we propose a new class of three-dimensional (3D) heteronanomat electrodes (HM electrode) based on multifunctional polymer fibrils and carbon nanotube (CNT). Through this architectural design, we enable unprecedented improvements in the electrochemical performance and mechanical flexibility, which lie far beyond those achievable with conventional LIBs electrode technologies. To realize the aforementioned goal, our primary interest is focused on the design/synthesis of multifunctional polymer fibrils and also HM electrode architecture, along with a proper selection of target electrode active materials. In addition, much attention should be also devoted to manufacturing processes and optimization fabrication conditions for the HM electrodes. To explore the potential applicability of the HM electrodes for LIBs, structural/electrochemical characterizations are comprehensively conducted, with a particular focus on 3D-reticulated, bicontinuous ion/electron conduction pathways.clos

Vitamin or antioxidant intake (or serum level) and risk of cervical neoplasm: a meta‐analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86903/1/BJO_3032_sm_TableS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/86903/2/j.1471-0528.2011.03032.x.pd

Language Detoxification with Attribute-Discriminative Latent Space

Transformer-based Language Models (LMs) have achieved impressive results on natural language understanding tasks, but they can also generate toxic text such as insults, threats, and profanity, limiting their real-world applications. To overcome this issue, a few text generation approaches aim to detoxify toxic texts using additional LMs or perturbations. However, previous methods require excessive memory, computations, and time which are serious bottlenecks in their real-world application. To address such limitations, we propose an effective yet efficient method for language detoxification using an attribute-discriminative latent space. Specifically, we project the latent space of an original Transformer LM onto a discriminative latent space that well-separates texts by their attributes using a projection block and an attribute discriminator. This allows the LM to control the text generation to be non-toxic with minimal memory and computation overhead. We validate our model, Attribute-Discriminative Language Model (ADLM) on detoxified language and dialogue generation tasks, on which our method significantly outperforms baselines both in performance and efficiency.Comment: ACL 2023; *Equal contribution. Author ordering determined by coin fli

Context-dependent Instruction Tuning for Dialogue Response Generation

Recent language models have achieved impressive performance in natural language tasks by incorporating instructions with task input during fine-tuning. Since all samples in the same natural language task can be explained with the same task instructions, many instruction datasets only provide a few instructions for the entire task, without considering the input of each example in the task. However, this approach becomes ineffective in complex multi-turn dialogue generation tasks, where the input varies highly with each turn as the dialogue context changes, so that simple task instructions cannot improve the generation performance. To address this limitation, we introduce a context-based instruction fine-tuning framework for each multi-turn dialogue which generates both responses and instructions based on the previous context as input. During the evaluation, the model generates instructions based on the previous context to self-guide the response. The proposed framework produces comparable or even outstanding results compared to the baselines by aligning instructions to the input during fine-tuning with the instructions in quantitative evaluations on dialogue benchmark datasets with reduced computation budget.Comment: Work in Progres

Simplified Analytical Method for Optimized Initial Shape Analysis of Self-Anchored Suspension Bridges and Its Verification

A simplified analytical method providing accurate unstrained lengths of all structural elements is proposed to find the optimized initial state of self-anchored suspension bridges under dead loads. For this, equilibrium equations of the main girder and the main cable system are derived and solved by evaluating the self-weights of cable members using unstrained cable lengths and iteratively updating both the horizontal tension component and the vertical profile of the main cable. Furthermore, to demonstrate the validity of the simplified analytical method, the unstrained element length method (ULM) is applied to suspension bridge models based on the unstressed lengths of both cable and frame members calculated from the analytical method. Through numerical examples, it is demonstrated that the proposed analytical method can indeed provide an optimized initial solution by showing that both the simplified method and the nonlinear FE procedure lead to practically identical initial configurations with only localized small bending moment distributions

Comparative efficacy of targeted therapies in patients with non-small cell lung cancer: a network meta-analysis of clinical trials

This study aims to investigate the efficacy of targeted therapies in the treatment of non-small cell lung cancer (NSCLC) by using a network meta-analysis of clinical trials. PubMed, EMBASE, Cochrane Library, and Clinicaltrials.gov were searched by using keywords related to the topic on 19 September 2018. Two investigators independently selected relevant trials by pre-determined criteria. A pooled response ratio (RR) for overall response rate (ORR) and a hazard ratio (HR) for progression-free survival (PFS) were calculated based on both the Bayesian and frequentist approaches. A total of 128 clinical trials with 39,501 participants were included in the final analysis of 14 therapeutic groups. Compared with chemotherapy, both ORR and PFS were significantly improved for afatinib, alectinib, and crizotinib, while only PFS was significantly improved for cabozantinib, ceritinib, gefitinib, and osimertinib. Consistency was observed between the direct and indirect comparisons based on the Bayesian approach statistically and the frequentist approach visually. Cabozantinib and alectinib showed the highest probability for the first-line treatment ranking in ORR (62.5%) and PFS (87.5%), respectively. The current network meta-analysis showed the comprehensive evidence-based comparative efficacy of different types of targeted therapies, which would help clinicians use targeted therapies in clinical practice

Hyaluronan- and RNA-binding deubiquitinating enzymes of USP17 family members associated with cell viability

BACKGROUND: Protein degradation by the ubiquitin system plays a crucial role in numerous cellular signaling pathways. Deubiquitination, a reversal of ubiquitination, has been recognized as an important regulatory step in the ubiquitin-dependent degradation pathway. RESULTS: While identifying putative ubiquitin specific protease (USP) enzymes that contain a conserved Asp (I) domain in humans, 4 USP17 subfamily members, highly homologous to DUB-3, have been found (USP17K, USP17L, USP17M, and USP17N), from human chorionic villi. Expression analysis showed that USP17 transcripts are highly expressed in the heart, liver, and pancreas and are expressed moderately in various human cancerous cell lines. Amino acid sequence analysis revealed that they contain the highly conserved Cys, His, and Asp domains which are responsible for the deubiquitinating activity. Biochemical enzyme assays indicated that they have deubiquitinating activity. Interestingly, the sequence analysis showed that these proteins, with exception of USP17N, contain the putative hyaluronan/RNA binding motifs, and cetylpyridinium chloride (CPC)-precipitation analysis confirmed the association between these proteins and intracellular hyaluronan and RNA. CONCLUSION: Here, we report that the overexpression of these proteins, with exception of USP17N, leads to apoptosis, suggesting that the hyaluronan and RNA binding motifs in these enzymes play an important role in regulating signal transduction involved in cell death