The energy penalty of post-combustion CO2 capture & storage and its implications for retrofitting the U.S. installed base

A review of the literature has found a factor of 4 spread in the estimated values of the energy penalty for post-combustion capture and storage of CO2 from pulverized-coal (PC) fired power plants. We elucidate the cause of that spread by deriving an analytic relationship for the energy penalty from thermodynamic principles and by identifying which variables are most difficult to constrain. We define the energy penalty for CCS to be the fraction of fuel that must be dedicated to CCS for a fixed quantity of work output. That penalty can manifest itself as either the additional fuel required to maintain a power plant's output or the loss of output for a constant fuel input. Of the 17 parameters that constitute the energy penalty, only the fraction of available waste heat that is recovered for use and the 2nd-law separation efficiency are poorly constrained. We provide an absolute lower bound for the energy penalty of ~11%, and we demonstrate to what degree increasing the fraction of available-waste-heat recovery can reduce the energy penalty from the higher values reported. It is further argued that an energy penalty of ~40% will be easily achieved while one of ~29% represents a decent target value. Furthermore, we analyze the distribution of PC plants in the U.S. and calculate a distribution for the additional fuel required to operate all these plants with CO2 capture and storage (CCS).Earth and Planetary SciencesEngineering and Applied Science

Laser structuring of electrodes in roll-to-roll environment using multi-beam processing: process upscaling and its perspective

The development of next-generation lithium-ion batteries with volumetric energy densities > 750 Wh/L and gravimetric energy densities > 400 Wh/kg is a key objective of the European Union’s Strategic Energy Technology Plan to be achieved by 2030. Both new materials and production strategies play an important role in the development of those batteries. Thick-film electrodes are advantageous to increase the volumetric and gravimetric energy densities alike since the amount of inactive material can be reduced. To facilitate higher C-rates during (dis-)charging in thick-film electrodes, laser generated structured are introduced, thus creating new lithium-ion diffusion pathways leading to a reduced cell polarization. Additionally, electrode wetting with liquid electrolyte is significantly improved, reducing the risk of dry spots in the electrode stack. Industry interest in implementing laser patterning of electrodes into existing or planned manufacturing lines has increased significantly in recent times. The strip speeds of electrode production are decisive for the required speeds to be realized in laser structuring. Various technical approaches can be applied to upscale the laser patterning process such as multibeam processing which can be realized by splitting a laser beam into several beamlets with a DOE. In this work, a large field scanner and a related optical lens system are combined with an ultrashort pulsed, high repetition rate, high power laser source. The ablation behavior of commercial graphite composite electrode material was investigated for upscaling using different laser patterning scenarios

A scoping study on the social determinants of health and sugar consumption in the context of policy approaches for improving population health

Objectives To conduct a scoping review of existing research on the social determinants of health, sugar consumption and public health policy responses to address or improve health outcomes. Methods A total of 13 categories were developed to reflect the authors' interest in the overall focus on the social determinants of health, sugar as an independent risk factor, upstream policy action (‘whole populations’), downstream policy action (‘targeted’) and two contemporary policy strategies (namely ‘Vulnerable populations’ and ‘Proportionate Universalism’). The search strategy was then performed on MEDLINE (via Ovid) and Web of Science, and was limited to the English language. No time limits prior to when the database search was conducted in 2022 were set to explore the full extent of the literature in this field. Results Five hundred and sixty articles were retrieved, of which 181 met the criteria for review. When all categories were applied, the findings showed that 76% of papers focusing on sugar consumption as a risk factor for non-communicable diseases (NCDs) mentioned the social determinants of health. The majority of studies (60%) recommended downstream interventions, with 40% recommending ‘upstream’ interventions. A limited proportion (12%) of research work was published in dental journals. Research had been done using predominantly quantitative methods (66% of articles), with 24% of studies adopting a mixed methods approach, and 8% being exclusively qualitative. Research on contemporary strategies for sugar reduction were focused on the ‘Global North’ and 98% of papers used individual level data focused on targeted approaches, highlighting that there is little direct evidence for contemporary strategies aimed at reducing sugar consumption. Conclusions Whilst the majority of public and dental health research argues that there is a need to address the social determinants of health, the findings from this study highlight that very few empirical studies have been designed to directly inform contemporary strategies for sugar reduction. More research is therefore needed that can directly assess the evidence for contemporary strategies in public health policy

reliability and applicability of modern numerical analyses of dams

Relevance. At present the application of numerical analyses to real problems of dam engineering has suffered at times from the gaps between the specialists of mathematical modeling and dam engineers and managers. The first group usually includes information system specialists because they are able to develop the computer models to their full potential. The professionals belonging to the second group often prefer to revert to traditional methods of calculation and empirical methods based on their proven experience. The aim of the work - based on recommendations of International workshops seminars, organized by the ICOLD Committee on Computational Aspects of Dam Analysis and Design, help dam engineers to interact with mathematical modeling specialists and to work with them without language barriers or gaps in knowledge. In this relation the assessment of reliability and applicability of numerical analyses of dams allows engineers to develop the optimal dam design. Methods. Assessment of the reliability of numerical methods of analyses of dam behavior was based on data of 10 International benchmark-workshop seminars, organized by the Committee in Italy (1991 and 1992), France (1994 and 2009), Spain (1996), USA (1999), Austria (2001), Romania (2003), China (2005), Russia (2007), in which specialists of these countries also took part

Truncated and Helix-Constrained Peptides with High Affinity and Specificity for the cFos Coiled-Coil of AP-1

Protein-based therapeutics feature large interacting surfaces. Protein folding endows structural stability to localised surface epitopes, imparting high affinity and target specificity upon interactions with binding partners. However, short synthetic peptides with sequences corresponding to such protein epitopes are unstructured in water and promiscuously bind to proteins with low affinity and specificity. Here we combine structural stability and target specificity of proteins, with low cost and rapid synthesis of small molecules, towards meeting the significant challenge of binding coiled coil proteins in transcriptional regulation. By iteratively truncating a Jun-based peptide from 37 to 22 residues, strategically incorporating i-->i+4 helix-inducing constraints, and positioning unnatural amino acids, we have produced short, water-stable, alpha-helical peptides that bind cFos. A three-dimensional NMR-derived structure for one peptide (24) confirmed a highly stable alpha-helix which was resistant to proteolytic degradation in serum. These short structured peptides are entropically pre-organized for binding with high affinity and specificity to cFos, a key component of the oncogenic transcriptional regulator Activator Protein-1 (AP-1). They competitively antagonized the cJun–cFos coiled-coil interaction. Truncating a Jun-based peptide from 37 to 22 residues decreased the binding enthalpy for cJun by ~9 kcal/mol, but this was compensated by increased conformational entropy (TDS ≤ 7.5 kcal/mol). This study demonstrates that rational design of short peptides constrained by alpha-helical cyclic pentapeptide modules is able to retain parental high helicity, as well as high affinity and specificity for cFos. These are important steps towards small antagonists of the cJun-cFos interaction that mediates gene transcription in cancer and inflammatory diseases

An ultra-deep sequencing strategy to detect sub-clonal TP53 mutations in presentation chronic lymphocytic leukemia cases using multiple polymerases

Chronic lymphocytic leukaemia (CLL) is the most common clonal B-cell disorder characterized by clonal diversity, a relapsing and remitting course, and in its aggressive forms remains largely incurable. Current front-line regimes include agents such as fludarabine, which act primarily via the DNA damage response pathway. Key to this is the transcription factor p53. Mutations in the TP53 gene, altering p53 functionality, are associated with genetic instability, and are present in aggressive CLL. Furthermore, the emergence of clonal TP53 mutations in relapsed CLL, refractory to DNA-damaging therapy, suggests that accurate detection of sub-clonal TP53 mutations prior to and during treatment may be indicative of early relapse. In this study, we describe a novel deep sequencing workflow using multiple polymerases to generate sequencing libraries (MuPol-Seq), facilitating accurate detection of TP53 mutations at a frequency as low as 0.3%, in presentation CLL cases tested. As these mutations were mostly clustered within the regions of TP53 encoding DNA-binding domains, essential for DNA contact and structural architecture, they are likely to be of prognostic relevance in disease progression. The workflow described here has the potential to be implemented routinely to identify rare mutations across a range of diseases

Theory of excited state absorptions in phenylene-based π\pi-conjugated polymers

Within a rigid-band correlated electron model for oligomers of poly-(paraphenylene) (PPP) and poly-(paraphenylenevinylene) (PPV), we show that there exist two fundamentally different classes of two-photon A$_g$ states in these systems to which photoinduced absorption (PA) can occur. At relatively lower energies there occur A$_g$ states which are superpositions of one electron - one hole (1e--1h) and two electron -- two hole (2e--2h) excitations, that are both comprised of the highest delocalized valence band and the lowest delocalized conduction band states only. The dominant PA is to one specific member of this class of states (the mA$_g$). In addition to the above class of A$_g$ states, PA can also occur to a higher energy kA$_g$ state whose 2e--2h component is {\em different} and has significant contributions from excitations involving both delocalized and localized bands. Our calculated scaled energies of the mA$_g$ and the kA$_g$ agree reasonably well to the experimentally observed low and high energy PAs in PPV. The calculated relative intensities of the two PAs are also in qualitative agreement with experiment. In the case of ladder-type PPP and its oligomers, we predict from our theoretical work a new intense PA at an energy considerably lower than the region where PA have been observed currently. Based on earlier work that showed that efficient charge--carrier generation occurs upon excitation to odd--parity states that involve both delocalized and localized bands, we speculate that it is the characteristic electronic nature of the kA$_g$ that leads to charge generation subsequent to excitation to this state, as found experimentally.Comment: Revtex4 style, 2 figures inserted in the text, three tables, 10 page

Elucidation of tonic and activated B-cell receptor signaling in Burkitt's lymphoma provides insights into regulation of cell survival.

Burkitt's lymphoma (BL) is a highly proliferative B-cell neoplasm and is treated with intensive chemotherapy that, because of its toxicity, is often not suitable for the elderly or for patients with endemic BL in developing countries. BL cell survival relies on signals transduced by B-cell antigen receptors (BCRs). However, tonic as well as activated BCR signaling networks and their relevance for targeted therapies in BL remain elusive. We have systematically characterized and compared tonic and activated BCR signaling in BL by quantitative phosphoproteomics to identify novel BCR effectors and potential drug targets. We identified and quantified ∼16,000 phospho-sites in BL cells. Among these sites, 909 were related to tonic BCR signaling, whereas 984 phospho-sites were regulated upon BCR engagement. The majority of the identified BCR signaling effectors have not been described in the context of B cells or lymphomas yet. Most of these newly identified BCR effectors are predicted to be involved in the regulation of kinases, transcription, and cytoskeleton dynamics. Although tonic and activated BCR signaling shared a considerable number of effector proteins, we identified distinct phosphorylation events in tonic BCR signaling. We investigated the functional relevance of some newly identified BCR effectors and show that ACTN4 and ARFGEF2, which have been described as regulators of membrane-trafficking and cytoskeleton-related processes, respectively, are crucial for BL cell survival. Thus, this study provides a comprehensive dataset for tonic and activated BCR signaling and identifies effector proteins that may be relevant for BL cell survival and thus may help to develop new BL treatments

Abschätzung der wirtschaftlichen Folgen des Kriegs in der Ukraine und der Sanktionen gegen Russland

Der Krieg gegen die Ukraine hat über mehrere Kanäle Auswirkungen auf die österreichische Wirtschaft. Neben den unmittelbaren Produktionseinbrüchen und dem Einbruch des Außenhandels sind die Rohstoffexporte auf die heimische Produktion und die Auswirkungen auf die Finanzmärkte zentral. Dieser Policy Brief diskutiert die Wirkungskanäle, behandelt den Stellenwert Russlands, Belarus und der Ukraine für den österreichischen Waren- und Dienstleistungsexport und -import und analysiert anschließend mit einem multiregionalen Input-Output-Modell Auswirkungen eines Exportstopps auf die österreichische Wertschöpfung und Arbeitsleistung. Ein einjähriger Exportstopp würde kurzfristig zu einem Wertschöpfungsverlust von ca. 4 Mrd. Euro führen. Das entspricht der Jahresarbeitsleistung von ca. 44.000 Beschäftigten. 1,14% der Wertschöpfung, bzw. 1,01% des BIP sowie 1,08% der Arbeitsleistung stehen im direkten oder indirekten Zusammenhang mit österreichischen und europäischen Exporten nach Russland, Belarus und in die Ukraine. Ca. 70% der österreichweiten Effekte sind dabei direkt auf den Exportstopp österreichischer Güter und Dienstleistungen zurückzuführen, während 30% indirekt aufgrund von Exportbeschränkungen anderer europäischer Länder wirksam werden. Ca. 61% der Gesamteffekte sind auf Warenexporte zurückzuführen. Die relativen Wertschöpfungsrückgänge sind in Vorarlberg und Burgenland am höchsten. Die vorliegende Analyse kann nur eine erste Abschätzung möglicher Effekte darstellen

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization