Frontiers of Energy Storage Technologies

Energy storage technologies (ESTs) play a crucial role in ensuring energy security and addressing the challenges posed by climate change. They enable us to overcome the mismatch between energy supply and demand caused by the intermittent and unpredictable nature of renewable energy sources. The identification of research frontiers in ESTs has primarily relied on expert experience and has been limited to specific areas of study. However, there is a relative lack of data-driven approaches to identify these frontiers. In this study, we employed an integrated technique combining bibliographic coupling and sliding window analysis to identify the research frontiers in ESTs and understand their evolution over time. Our study reveals 19 research frontiers in ESTs distributed across four knowledge domains: electrochemical energy storage, electrical energy storage, chemical energy storage, and energy storage systems. Among these frontiers, two noteworthy areas are aqueous zinc batteries (AZBs) and two-dimensional transition metal carbon-nitride composites (MXenes). By identifying these research frontiers, our study provides insights into the potential future directions for research and development (R&D) deployment in energy storage technologies

A Reversible Steganography Scheme of Secret Image Sharing Based on Cellular Automata and Least Significant Bits Construction

Secret image sharing schemes have been extensively studied by far. However, there are just a few schemes that can restore both the secret image and the cover image losslessly. These schemes have one or more defects in the following aspects: (1) high computation cost; (2) overflow issue existing when modulus operation is used to restore the cover image and the secret image; (3) part of the cover image being severely modified and the stego images having worse visual quality. In this paper, we combine the methods of least significant bits construction (LSBC) and dynamic embedding with one-dimensional cellular automata to propose a new lossless scheme which solves the above issues and can resist differential attack and support parallel computing. Experimental results also show that this scheme has the merit of big embedding capacity

Cell-type, Dose, and Mutation-type Specificity Dictate Mutant p53 Functions In Vivo

SummaryThe specific roles of mutant p53's dominant-negative (DN) or gain-of-function (GOF) properties in regulating acute response and long-term tumorigenesis is unclear. Using “knockin” mouse strains expressing varying R246S mutant levels, we show that the DN effect on transactivation is universally observed after acute p53 activation, whereas the effect on cellular outcome is cell-type specific. Reducing mutant p53 levels abrogated the DN effect. Mutant p53's DN effect protected against radiation-induced death but did not accentuate tumorigenesis. Furthermore, the R246S mutant did not promote tumorigenesis compared to p53−/− mice in various models, even when MDM2 is absent, unlike the R172H mutant. Together, these data demonstrate that mutant p53's DN property only affects acute responses, whereas GOF is not universal, being mutation-type specific

Guided propagation of extremely intense lasers in plasma via ion motion

The upcoming 10–100 PW laser facilities may deliver laser pulses with unprecedented intensity of 1022–1025Wcm−2. Such laser pulses interacting with ultrarelativistic electrons accelerated in plasma can trigger various nonlinear quantum electrodynamic processes. Usually, ion motion is expected to be ignorable since the laser intensities below 1025Wcm−2 are underrelativistic for ions. Here, we find that ion motion becomes significant even with the intensity around 1022Wcm−2 when electron cavitation is formed by the strong laser ponderomotive force. Due to the electron cavitation, guided laser propagation becomes impossible via usual plasma electron response to laser fields. However, we find that ion response to the laser fields may effectively guide laser propagation at such high intensity levels. The corresponding conditions of the required ion density distribution and laser power are presented and verified by three-dimensional particle-in-cell simulations

Quantumness and quantum to classical transition in the generalized Rabi model

The quantum to classical transition (QCT) is one of the central mysteries in quantum physics. This process is generally interpreted as state collapse from measurement or decoherence from interacting with the environment. Here we define the quantumness of a Hamiltonian by the free energy difference between its quantum and classical descriptions, which vanishes during QCT. We apply this criterion to the many-body Rabi model and study its scaling law across the phase transition, finding that not only the temperature and Planck constant, but also all the model parameters are important for this transition. We show that the Jaynes-Cummings and anti Jaynes-Cummings models exhibit greater quantumness than the Rabi model. Moreover, we show that the rotating wave and anti-rotating wave terms in this model have opposite quantumness in QCT. We demonstrate that the quantumness may be enhanced or suppressed at the critical point. Finally, we estimate the quantumness of the Rabi model in current trapped ion experiments. The quantumness provides an important tool to characterize the QCT in a vast number of many-body models.Comment: 6 pages, 5 figure

T3SEdb: data warehousing of virulence effectors secreted by the bacterial Type III Secretion System

<p>Abstract</p> <p>Background</p> <p>Effectors of Type III Secretion System (T3SS) play a pivotal role in establishing and maintaining pathogenicity in the host and therefore the identification of these effectors is important in understanding virulence. However, the effectors display high level of sequence diversity, therefore making the identification a difficult process. There is a need to collate and annotate existing effector sequences in public databases to enable systematic analyses of these sequences for development of models for screening and selection of putative novel effectors from bacterial genomes that can be validated by a smaller number of key experiments.</p> <p>Results</p> <p>Herein, we present T3SEdb <url>http://effectors.bic.nus.edu.sg/T3SEdb</url>, a specialized database of annotated T3SS effector (T3SE) sequences containing 1089 records from 46 bacterial species compiled from the literature and public protein databases. Procedures have been defined for i) comprehensive annotation of experimental status of effectors, ii) submission and curation review of records by users of the database, and iii) the regular update of T3SEdb existing and new records. Keyword fielded and sequence searches (BLAST, regular expression) are supported for both experimentally verified and hypothetical T3SEs. More than 171 clusters of T3SEs were detected based on sequence identity comparisons (intra-cluster difference up to ~60%). Owing to this high level of sequence diversity of T3SEs, the T3SEdb provides a large number of experimentally known effector sequences with wide species representation for creation of effector predictors. We created a reliable effector prediction tool, integrated into the database, to demonstrate the application of the database for such endeavours.</p> <p>Conclusions</p> <p>T3SEdb is the first specialised database reported for T3SS effectors, enriched with manual annotations that facilitated systematic construction of a reliable prediction model for identification of novel effectors. The T3SEdb represents a platform for inclusion of additional annotations of metadata for future developments of sophisticated effector prediction models for screening and selection of putative novel effectors from bacterial genomes/proteomes that can be validated by a small number of key experiments.</p

Superparamagnetic iron oxide nanoparticles mediated 131I-hVEGF siRNA inhibits hepatocellular carcinoma tumor growth in nude mice

BACKGROUND: Hepatocellular carcinoma (HCC) is a primary liver tumor and is the most difficult human malignancy to treat. In this study, we sought to develop an integrative approach in which real-time tumor monitoring, gene therapy, and internal radiotherapy can be performed simultaneously. This was achieved through targeting HCC with superparamagnetic iron oxide nanoparticles (SPIOs) carrying small interfering RNA with radiolabled iodine 131 ((131)I) against the human vascular endothelial growth factor (hVEGF). METHODS: hVEGF siRNA was labeled with (131)I by the Bolton-Hunter method and conjugated to SilenceMag, a type of SPIOs. (131)I-hVEGF siRNA/SilenceMag was then subcutaneously injected into nude mice with HCC tumors exposed to an external magnetic field (EMF). The biodistribution and cytotoxicity of (131)I-hVEGF siRNA/SilenceMag was assessed by SPECT (Single-Photon Emission Computed Tomography) and MRI (Magnetic Resonance Imaging) studies and blood kinetics analysis. The body weight and tumor size of nude mice bearing HCC were measured daily for the 4-week duration of the experiment. RESULTS: (131)I-hVEGF siRNA/SilenceMag was successfully labeled; with a satisfactory radiochemical purity (>80%) and biological activity in vitro. External application of an EMF successfully attracted and retained more (131)I-hVEGF siRNA/SilenceMag in HCC tumors as shown by SPECT, MRI and biodistribution studies. The tumors treated with (131)I-hVEGF siRNA/SilenceMag grew nearly 50% slower in the presence of EMF than those without EMF and the control. Immunohistochemical assay confirmed that the tumor targeted by (131)I-hVEGF siRNA/SilenceMag guided by an EMF had a lower VEGF protein level compared to that without EMF exposure and the control. CONCLUSIONS: EMF-guided (131)I-hVEGF siRNA/SilenceMag exhibited an antitumor effect. The synergic therapy of (131)I-hVEGF siRNA/SilenceMag might be a promising future treatment option against HCC with the dual functional properties of tumor therapy and imaging

Loyalty Card Membership Challenge: A Study on Membership Churn and their Spending Behaviour

Understand member spending behaviour and their loyalty is important in all industries. By gaining loyalty from customers and understand how they spend, companies are able to retain their customers, increase their revenue and plan their marketing strategy to continue grow their business in a competitive business ecosystem. This research investigates member spending behaviour and membership churn for a loyalty card company in Malaysia. This research conducts exploratory analysis on three key partners registered with the company to understand their outlets’ spending activities and patterns. Meanwhile, this research also model membership churn based on the last 24 months membership data to identify factors that influence membership churn so that effective strategy can be formulated to retain active members in the company

Comparative Proteomic Approach Identifies Pkm2 and Cofilin-1 as Potential Diagnostic, Prognostic and Therapeutic Targets for Pulmonary Adenocarcinoma

Lung cancer is the leading cause of cancer-related death in the world. Non-small cell lung carcinomas (Non-SCLC) account for almost 80% of lung cancers, of which 40% were adenocarcinomas. For a better understanding of the molecular mechanisms behind the development and progression of lung cancer, particularly lung adenocarcinoma, we have used proteomics technology to search for candidate prognostic and therapeutic targets in pulmonary adenocarcinoma. The protein profile changes between human pulmonary adenocarcinoma tissue and paired surrounding normal tissue were analyzed using two-dimensional polyacrylamide gel electrophoresis (2-DE) based approach. Differentially expressed protein-spots were identified with ESI-Q-TOF MS/MS instruments. As a result, thirty two differentially expressed proteins (over 2-fold, p<0.05) were identified in pulmonary adenocarcinoma compared to normal tissues. Among them, two proteins (PKM2 and cofilin-1), significantly up-regulated in adenocarcinoma, were selected for detailed analysis. Immunohistochemical examination indicated that enhanced expression of PKM2 and cofilin-1 were correlated with the severity of epithelial dysplasia, as well as a relatively poor prognosis. Knockdown of PKM2 expression by RNA interference led to a significant suppression of cell growth and induction of apoptosis in pulmonary adenocarcinoma SPC-A1 cells in vitro, and tumor growth inhibition in vivo xenograft model (P<0.05). In addition, the shRNA expressing plasmid targeting cofilin-1 significantly inhibited tumor metastases and prolonged survival in LL/2 metastatic model. While additional works are needed to elucidate the biological significance and molecular mechanisms of these altered proteins identified in this study, PKM2 and cofilin-1 may serve as potential diagnostic and prognostic biomarkers, as well as therapeutic targets for pulmonary adenocarcinoma