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A collection of applications of polymer matrix syntactic foams is presented in this article. Syntactic foams are lightweight porous composites that found their early applications in marine structures due to their naturally buoyant behavior and low moisture absorption. Their light weight has been beneficial in weight sensitive aerospace structures. Syntactic foams have pushed the performance boundaries for composites and have enabled the development of vehicles for traveling to the deepest parts of the ocean and to other planets. The high volume fraction of porosity in syntactic foams also enabled their applications in thermal insulation of pipelines in oil and gas industry. The possibility of tailoring the mechanical and thermal properties of syntactic foams through a combination of material selection, hollow particle volume fraction, and hollow particle wall thickness has helped in rapidly growing these applications. The low coefficient of thermal expansion and dimensional stability at high temperatures are now leading their use in electronic packaging, composite tooling, and thermoforming plug assists. Methods have been developed to tailor the mechanical and thermal properties of syntactic foams independent of each other over a wide range, which is a significant advantage over other traditional particulate and fibrous composites.

Application of pneumatic separators in coal beneficiation is increasing rapidly over the last decade primarily due to their low capital and operating costs, and waste handling problems associated with traditional wet processing methods. Large amount of shale/rock that is extracted in coal production can be removed prior to transportation at the mine face by using this methodology. Due to the limited washing facilities in India, most of the thermal power plants burn raw coal from run-of-mine （ROM） to generate electricity. This practice causes poor utilization efficiency, high operating and maintenance costs, and high emission rates for the power plants. One potential method that can be utilized is the air-fluidized inclined vibrating deck technology. The technology was demonstrated on a pilot-scale at different coal washeries in India at a feed rate of 5-ton per hour. The pilot-scale evaluation showed that 20 %-25 % high-ash incombustible material can be eliminated from ROM feed with only minor losses in energy content （〈10 %） from respective ROM coal. Furthermore, a feasibility analysis showed significant economic gains in terms of transportation cost, improving power-plant efficiency, and reducing emissions rates by using the technology.

Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.

Emergence of extensively drug-resistant tuberculosis (XDR-TB) has significantly threatened to jeopardize global efforts to control TB, especially in HIV endemic regions. XDR-TB is mainly an iatrogenically created issue, and understanding the epidemiological and risk factors associated with it is of paramount importance in curbing this menace. Emergence of this deadly phenomenon can be prevented by prompt diagnosis and effective treatment with second-line drugs in rifampicin-resistant TB (RR-TB) as well as multidrug-resistant TB (MDR-TB) patients. Optimal treatment of RR-TB, MDR-TB and XDR-TB cases alone will not suffice to reduce the global burden. The TB control programmes need to prioritize on policies focusing on the effective as well as rational use of first-line drugs in every newly diagnosed drug susceptible TB patients so as to prevent the emergence of drug resistance.

Multidrug-resistant tuberculosis (MDR-TB)/rifampicin-resistant TB (RR-TB) is human-made problem and emerging due to poor management of TB and is a threat to control of TB. Early suspicion and diagnosis are important. Culture and drug susceptibility testing are gold standards, but newer molecular methods help in rapid diagnosis. Once diagnosed, prompt treatment should be started, preferably under direct observation. Treatment can be standardized or individualized. Conventional regimen takes up to 24 months but recently shorter regimen of up to 12 months was introduced in specific subset of MDR-TB/RR-TB patients. Management of MDR-TB/RR-TB is complicated, costlier, and challenging and is a concern for human health worldwide. It must be emphasized that optimal treatment of MDR-TB/RR-TB alone is not sufficient. Efforts must be made to ensure effective use of first- and second-line anti-TB drugs.

Task-oriented dialog (TOD) systems often need to formulate knowledge base (KB) queries corresponding to the user intent and use the query results to generate system responses. Existing approaches require dialog datasets to explicitly annotate these KB queries—these annotations can be time consuming, and expensive. In response, we define the novel problems of predicting the KB query and training the dialog agent, without explicit KB query annotation. For query prediction, we propose a reinforcement learning (RL) baseline, which rewards the generation of those queries whose KB results cover the entities mentioned in subsequent dialog. Further analysis reveals that correlation among query attributes in KB can significantly confuse memory augmented policy optimization (MAPO), an existing state of the art RL agent. To address this, we improve the MAPO baseline with simple but important modifications suited to our task. To train the full TOD system for our setting, we propose a pipelined approach: it independently predicts when to make a KB query (query position predictor), then predicts a KB query at the predicted position (query predictor), and uses the results of predicted query in subsequent dialog (next response predictor). Overall, our work proposes first solutions to our novel problem, and our analysis highlights the research challenges in training TOD systems without query annotation.

The protein phosphatase 2A (PP2A) heterotrimer PP2A-B56α is a human tumour suppressor. However, the molecular mechanisms inhibiting PP2A-B56α in cancer are poorly understood. Here, we report molecular level details and structural mechanisms of PP2A-B56α inhibition by an oncoprotein CIP2A. Upon direct binding to PP2A-B56α trimer, CIP2A displaces the PP2A-A subunit and thereby hijacks both the B56α, and the catalytic PP2Ac subunit to form a CIP2A-B56α-PP2Ac pseudotrimer. Further, CIP2A competes with B56α substrate binding by blocking the LxxIxE-motif substrate binding pocket on B56α. Relevant to oncogenic activity of CIP2A across human cancers, the N-terminal head domain-mediated interaction with B56α stabilizes CIP2A protein. Functionally, CRISPR/Cas9-mediated single amino acid mutagenesis of the head domain blunted MYC expression and MEK phosphorylation, and abrogated triple-negative breast cancer in vivo tumour growth. Collectively, we discover a unique multi-step hijack and mute protein complex regulation mechanism resulting in tumour suppressor PP2A-B56α inhibition. Further, the results unfold a structural determinant for the oncogenic activity of CIP2A, potentially facilitating therapeutic modulation of CIP2A in cancer and other diseases.

The improvement in corrosion resistance of WE43 was well realized by heat treatment. To study the influence of microstructure on the corrosion behavior of WE43 in as-cast and heat-treated conditions, an immersion test was employed with as-cast and heat-treated samples in the 3.5% NaCl solution. The corrosion rate and change of morphology were recorded and the corrosion behavior was further investigated by scanning electron microscopy (SEM). The results indicated that the corrosion rate of the WE43 alloy decreased after heat treatment. It was observed that the eutectic gradually damages the protective film on the surface of the as-cast WE43 in the process of corrosion, which further increases the corrosion rate. The Zr-rich phase formed a domed structure resulting in the adjacent area being further corroded. The Y-rich phase has little effect on the corrosion reaction.

DNA methylation is an essential epigenetic mark in mammals. The proper distribution of this mark depends on accurate deposition and maintenance mechanisms, and underpins its functional role. This, in turn, depends on the precise recruitment and activation of de novo and maintenance DNA methyltransferases (DNMTs). In this review, we discuss mechanisms of recruitment of DNMTs by transcription factors and chromatin modifiers-and by RNA-and place these mechanisms in the context of biologically meaningful epigenetic events. We present hypotheses and speculations for future research, and underline the fundamental and practical benefits of better understanding the mechanisms that govern the recruitment of DNMTs.