Larger Building Blocks Research Articles

The Pristine Inner Galaxy Survey – VIII. Characterizing the orbital properties of the ancient, very metal-poor inner Milky Way

ABSTRACT The oldest stars in the Milky Way (born in the first few billion years) are expected to have a high density in the inner few kpc, spatially overlapping with the Galactic bulge. We use spectroscopic data from the Pristine Inner Galaxy Survey (PIGS) to study the dynamical properties of ancient, metal-poor inner Galaxy stars. We compute distances using starhorse, and orbital properties in a barred Galactic potential. With this paper, we release the spectroscopic AAT/PIGS catalogue (13 235 stars). We find that most PIGS stars have orbits typical for a pressure-supported population. The fraction of stars confined to the inner Galaxy decreases with decreasing metallicity, but many very metal-poor stars (VMP; [Fe/H] <−2.0) stay confined ($\sim 60~{{\ \rm per \, cent}}$ stay within 5 kpc). The azimuthal velocity vϕ also decreases between [Fe/H] = −1.0 and −2.0, but is constant for VMP stars (at ∼+40 km s−1). The carbon-enhanced metal-poor (CEMP) stars in PIGS appear to have similar orbital properties compared to normal VMP stars. Our results suggest a possible transition between two spheroidal components – a more metal-rich, more concentrated, faster rotating component, and a more metal-poor, more extended and slower/non-rotating component. We propose that the former may be connected to pre-disc in-situ stars (or those born in large building blocks), whereas the latter may be dominated by contributions from smaller galaxies. This is an exciting era where large metal-poor samples, such as in this work (as well as upcoming surveys, e.g. 4MOST), shed light on the earliest evolution of our Galaxy.

Highly efficient photosynthesis of hydrogen peroxide by a stable Zr(IV)-based MOF with a diamino-functionalized ligand.

Metal-organic frameworks (MOFs) have emerged as a promising class of materials for solar-driven hydrogen peroxide (H2O2) generation due to their porosity, large surface area and designable molecular building blocks; however, producing H2O2 from oxygen and water without sacrificial agents remains a major challenge. Herein, we have constructed two UiO-67-type MOFs, UiO-67-NH2 and UiO-67-(NH2)2, by a solvothermal method using 2-amino-4,4'-biphenyldicarboxylic acid and 2,2'-diamino-4,4'-biphenyldicarboxylic acid as ligands, respectively. A variety of photochemical measurements have shown that the introduction of diamino groups into UiO-67-(NH2)2 not only enhances its absorption ability for visible light, but also facilitates the separation of photogenerated electron/hole pairs. Consequently, compared to monoamino-functionalized UiO-67-NH2, UiO-67-(NH2)2 exhibits a 5.5 times higher H2O2 production rate in pure water for 1 h. A two-step one-electron oxygen reduction reaction pathway for photocatalytic H2O2 production was suggested based on a series of control experiments and active species trapping tests by electron paramagnetic resonance spectra. This work provides new insights into the regulation of functionalized MOF ligands at the molecular level and a catalytic mechanism towards MOF-based photocatalysts for H2O2 production with high activity.

Geminal-Based Strategies for Modeling Large Building Blocks of Organic Electronic Materials.

We elaborate on unconventional electronic structure methods based on geminals and their potential to advance the rapidly developing field of organic photovoltaics (OPVs). Specifically, we focus on the computational advantages of geminal-based methods over standard approaches and identify the critical aspects of OPV development. Examples are reliable and efficient computations of orbital energies, electronic spectra, and van der Waals interactions. Geminal-based models can also be combined with quantum embedding techniques and a quantum information analysis of orbital interactions to gain a fundamental understanding of the electronic structures and properties of realistic OPV building blocks. Furthermore, other organic components present in, for instance, dye-sensitized solar cells (DSSCs) represent another promising scope of application. Finally, we provide numerical examples predicting the properties of a small building block of OPV components and two carbazole-based dyes proposed as possible DSSC sensitizers.

Internal structure and thermal properties of potato starches varying widely in amylose content

The correlation between starch internal structure and thermal properties (gelatinisation and retrogradation) was studied in starches of wild-type potatoes and potatoes from the lines with altered starch synthase or branching enzyme activities (GBSS, SS, SBE), representing a range of amylose:amylopectin ratio from 2 to >99.5% amylopectin. The different potato lines were divided into Group 1–8 depending on the mutation targets. The internal chain distribution and building block composition of beta-limit dextrins (β-LDs) in the whole starches were analysed by high-performance anion-exchange chromatography (HPAEC) and high-performance size-exclusion chromatography (HPSEC) based on a recently developed simplified method. The building blocks were categorised into five size groups (G2-G6). Thermal properties of the starches were investigated using differential scanning calorimetry (DSC). The proportion of fingerprint B-chains with the degree of polymerisation 4–7, and the composition of intermediate (G4) and large (G5 and G6) building blocks of starches generally decreased in the order of potato lines from Group 2 (full Sbe1 and partial Sbe2 mutated)>Group 1 (full Sbe1 mutated)>wild-type > Group 7 (full Gbss and Ss2 , and partial Ss3 mutated)>Group 8 (full Gbss , Ss2 , and Ss3 mutated). The starch of amylopectin-rich potato lines from Group 8 with multiple genes targeted and the highest degree of mutations showed the lowest enthalpy of gelatinisation (15.0 J/g of amylopectin) and retrogradation (3.1 J/g of amylopectin), compared to starches of potato lines from other groups. More intermediate and large building blocks led to higher gelatinisation temperatures. Retrogradation was favoured by dense structure of the amylopectins with many short internal chains. • A new simplified method was applied for characterisation of starch internal structure. • CRISPR potato starches with genetic variations showed different internal structure. • More intermediate and large building blocks led to higher gelatinisation temperatures. • Retrogradation was favoured by dense amylopectins with many short internal chains.

Non-Fullerene Acceptors Containing Alkylated Large π-Conjugated Building Blocks for Efficient Organic Photovoltaic Cells

Non-Fullerene Acceptors Containing Alkylated Large π-Conjugated Building Blocks for Efficient Organic Photovoltaic Cells

Knowledge Distillation for Lightweight 2D Single-Person Pose Estimation

The current state-of-the-art single-person pose estimation methods require heavily parameterized models for accurate predictions. A promising technique to achieve accurate yet lightweight pose estimation is knowledge distillation. However, existing pose knowledge distillation methods rely on the most common large basic building blocks and a complex multi-branch architecture. In this study, we propose a Single-branch Lightweight Knowledge Distillation method to increase pose distillation efficiency for 2D Single-person pose estimation, termed SLKD2S. First, we design a novel single-branch pose knowledge distillation framework, which is composed of connected lightweight pose estimation stages. Second, we utilize a special pose distillation loss based on the joint confidence map. Finally, we only keep the initial stage and the first refinement stage to achieve a good performance. Extensive experiments on two standard benchmark datasets show the superiority of the proposed SLKD2S in terms of cost and accuracy, and the average detection accuracies are increased by 1.43% and 2.74% compared with the top-performing pose distillation method, respectively.

Heuristic algorithms in evolutionary computation and modular organization of biological macromolecules: Applications to in vitro evolution.

Evolutionary computing (EC) is an area of computer sciences and applied mathematics covering heuristic optimization algorithms inspired by evolution in Nature. EC extensively study all the variety of methods which were originally based on the principles of selectionism. As a result, many new algorithms and approaches, significantly more efficient than classical selectionist schemes, were found. This is especially true for some families of special problems. There are strong arguments to believe that EC approaches are quite suitable for modeling and numerical analysis of those methods of synthetic biology and biotechnology that are known as in vitro evolution. Therefore, it is natural to expect that the new algorithms and approaches developed in EC can be effectively applied in experiments on the directed evolution of biological macromolecules. According to the John Holland's Schema theorem, the effective evolutionary search in genetic algorithms (GA) is provided by identifying short schemata of high fitness which in the further search recombine into the larger building blocks (BBs) with higher and higher fitness. The multimodularity of functional biological macromolecules and the preservation of already found modules in the evolutionary search have a clear analogy with the BBs in EC. It seems reasonable to try to transfer and introduce the methods of EC, preserving BBs and essentially accelerating the search, into experiments on in vitro evolution. We extend the key instrument of the Holland's theory, the Royal Roads fitness function, to problems of the in vitro evolution (Biological Royal Staircase, BioRS, functions). The specific version of BioRS developed in this publication arises from the realities of experimental evolutionary search for (DNA-) RNA-devices (aptazymes). Our numerical tests showed that for problems with the BioRS functions, simple heuristic algorithms, which turned out to be very effective for preserving BBs in GA, can be very effective in in vitro evolution approaches. We are convinced that such algorithms can be implemented in modern methods of in vitro evolution to achieve significant savings in time and resources and a significant increase in the efficiency of evolutionary search.

Prediction of Solution Behavior via Calorimetric Measurements Allows for Detailed Elucidation of Polyoxometalate Transformation.

The solution behavior of a polyoxometalate cluster, LiNa-U24Pp12 (Li24Na24[(UO2O2)24(P2O7)12]) that consists of 24 uranyl ions, peroxide groups, and 12 pyrophosphate linkers, was successfully predicted based on new thermodynamic results using a calorimetric method recently described for uranyl peroxide nanoclusters (UPCs), molybdenum blues, and molybdenum browns. The breakdown of LiNa-U24Pp12 and formation of U24 (Li24[UO2O2OH]24) was monitored in situ via Raman spectroscopy using a custom heating apparatus. A combination of analytical techniques confirmed the simultaneous existence of U24Pp12 and U24 midway through the conversion process and U24 as the single end product. The application of a molecular weight filter resulted in a complete and successful separation of UPCs from solution and, in conjunction with DOSY results, confirmed the presence of large intermediate cluster building blocks.

Two-dimensional d-π conjugated metal-organic framework based on hexahydroxytrinaphthylene

The development of new two-dimensional (2D) d-π conjugated metal-organic frameworks (MOFs) holds great promise for the construction of a new generation of porous and semiconductive materials. This paper describes the synthesis, structural characterization, and electronic properties of a new d-π conjugated 2D MOF based on the use of a new ligand 2,3,8,9,14,15-hexahydroxytrinaphthylene. The reticular self-assembly of this large π-conjugated organic building block with Cu(II) ions in a mixed solvent system of 1,3-dimethyl-2-imidazolidinone (DMI) and H2O with the addition of ammonia water or ethylenediamine leads to a highly crystalline MOF Cu3(HHTN)2, which possesses pore aperture of 2.5 nm. Cu3(HHTN)2 MOF shows moderate electrical conductivity of 9.01 × 10−8 S·cm−1 at 385 K and temperature-dependent band gap ranging from 0.75 to 1.65 eV. After chemical oxidation by I2, the conductivity of Cu3(HHTN)2 can be increased by 360 times. This access to HHTN based MOF adds an important member to previously reported MOF systems with hexagonal lattice, paving the way towards systematic studies of structure-property relationships of semiconductive MOFs.

Fabrication and Mechanics of Bioinspired Materials with Dense Architectures: Current Status and Future Perspectives

Materials with dense architectures are composed of stiff and strong building blocks that are arranged to interact through energy-dissipative interfaces. Examples of these materials include engineered constructions such as the Abeille vault and highly mineralized natural materials such as tooth enamel. Compared with synthetic materials, natural materials with dense architectures exhibit outstanding mechanical performance, serving as a continued source of inspiration and study. This review details the status of advances in the fabrication and mechanics of bioinspired materials with dense architectures. The fabrication methods include freeze-casting, mineralization, 3D printing, coating–assembling, and laser engraving. Micromechanics of the resulting materials are discussed in tension, flexion, fracture, puncture, and impact. The discussion shows that strength of these materials can be improved by decreasing the size of their building blocks to the nm–µm range. However, interface hardening mechanisms that are crucial to the spread of deformation and toughness have not yet been implemented at nm–μm scales although they have been successfully realized for materials with larger building blocks. Future directions to address this and other unmet challenges are discussed throughout the text.

Structural integrity versus lateral size: Enhancing graphene-based film materials by reducing planar defects rather than flake boundary

Chemically modified graphene (CMG) bulk films have displayed a large potential in a plethora of applications. Incorporation of large CMG sheets was applied as the major strategy to improve both the electrical and mechanical properties of resulted film materials, whereas the low fabrication yield of high quality large building blocks severely obstruct its scalability. Herein, we evaluated the individual impact of sheet size and structural integrity of CMG building blocks on the performance of film materials, and results show that low structural defects density rather than large size dominates the enhancement of performance. Compared with large building blocks (average area 37.2 μm2), small ones (average area 1.3 μm2) with optimized structural integrity and also higher preparation yield formed films with even higher strength and conductivity (increased by 55% and 120%, respectively). Furthermore, the influence of structural integrity on the material performance was studied via detailed characterization. These results unequivocally impart the importance of structural integrity, and may give instruction on the rational design of materials with excellent performance.

Rapid Macroscopic-Scale Assembly of Ag Nanowires at the Water/Air Interface.

Rapid macroscopic-scale assembly of Ag nanowires was demonstrated through facile self-assembly at the water/air interface. This self-assembly was induced by heating due to the surface tension effect and convection. Interestingly, a rippled hairstyle superstructure was observed when the aqueous dispersions of thinner Ag nanowires were heated. Applying the Euler buckling theory for a set of aligned Ag nanowires, it was found that the water surface tension was sufficient to bend or buckle these free Ag nanowires trapped between two nanowire stripes, which resulted in the formation of the rippled hairstyle superstructure. However, the formation of the nanowire stripes was driven by steric repulsion of nanowires along with their short-range van der Waals interactions and later lateral capillary attraction between large building blocks. Such control over self-assembly is key for designing hierarchically ordered structures, which opens a new opportunity in the exploration of novel properties and the development of new applications.

Detection of Complexes in Biological Networks Through Diversified Dense Subgraph Mining.

Protein-protein interaction (PPI) networks, providing a comprehensive landscape of protein interaction patterns, enable us to explore biological processes and cellular components at multiple resolutions. For a biological process, a number of proteins need to work together to perform a job. Proteins densely interact with each other, forming large molecular machines or cellular building blocks. Identification of such densely interconnected clusters or protein complexes from PPI networks enables us to obtain a better understanding of the hierarchy and organization of biological processes and cellular components. However, most existing graph clustering algorithms on PPI networks often cannot effectively detect densely connected subgraphs and overlapped subgraphs. In this article, we formulate the problem of complex detection as diversified dense subgraph mining and introduce a novel approximation algorithm to efficiently enumerate putative protein complexes from biological networks. The key insight of our algorithm is that instead of enumerating all dense subgraphs, we only need to find a small diverse subset of subgraphs that cover as many proteins as possible. The problem is modeled as finding a diverse set of maximal dense subgraphs where we develop highly effective pruning techniques to guarantee efficiency. To scale up to large networks, we devise a divide-and-conquer approach to speed up the algorithm in a distributed manner. By comparing with existing clustering and dense subgraph-based algorithms on several yeast and human PPI networks, we demonstrate that our method can detect more putative protein complexes and achieves better prediction accuracy.

De Novo Assembly of Highly Substituted Morpholines and Piperazines.

The morpholine and piperazine with their remarkable physical and biochemical properties are popular heterocycles in organic and medicinal chemistry used in rational property design. However, in the majority of cases these rings are added to an existing molecule in a building block approach thus limiting their substitution pattern and diversity. Here we introduce a versatile de novo synthesis of the morpholine and piperazine rings using multicomponent reaction chemistry. The large scale amenable building blocks can be further substituted at up to four positions, making this a very versatile scaffold synthesis strategy. Our methods thus fulfill the increasing demand for novel building block design and nontraditional scaffolds which previously were not accessible

OBLIQUE AERIAL IMAGERY FOR NMA – SOME BEST PRACTICES

Abstract. Oblique airborne photogrammetry is rapidly maturing and being offered by service providers as a good alternative or replacement of the more traditional vertical imagery and for very different applications (Fig.1). EuroSDR, representing European National Mapping Agencies (NMAs) and research organizations of most EU states, is following the development of oblique aerial cameras since 2013, when an ongoing activity was created to continuously update its members on the developments in this technology. Nowadays most European NMAs still rely on the traditional workflow based on vertical photography but changes are slowly taking place also at production level. Some NMAs have already run some tests internally to understand the potential for their needs whereas other agencies are discussing on the future role of this technology and how to possibly adapt their production pipelines. At the same time, some research institutions and academia demonstrated the potentialities of oblique aerial datasets to generate textured 3D city models or large building block models. The paper provides an overview of tests, best practices and considerations coming from the R&D community and from three European NMAs concerning the use of oblique aerial imagery.

Facile Route To Control the Ambipolar Transport in Semiconducting Polymers

Control of electron and hole transport in conjugated molecules is a challenging but essential task for deeply understanding the intrinsic charge transport behaviors as well as technological benefits for optimizing the performance of various optoelectronic devices. Here we suggest a facile route to controlling ambipolar charge transport in conjugated polymers by precise regulation of the copolymerization ratio between a relatively large electron donor and acceptor building block as a repeating unit. By varying the ratio between poly[2,5-bis(2-octyldodecyl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione-(E)-[2,2-bithiophen]-5-yl)-3-(thiophen-2-yl)acrylonitrile] (DPP-CNTVT) as an electron transport unit and DPP-selenophene-vinylene-selenophene (DPP-SVS) as a hole transport unit, mobility (μFET) and onset voltage (Von) in organic field-effect transistors are effectively modulated from p-channel [μFET,h = 6.23 ± 0.4 cm2 V–1 s–1] to n-channel [μFET,e = 6.88 ± 1.01 cm2 V–1 s–1] dominant transport. The same two DPP-based ...

Parameter Tuning for Scalable Multi-Resource Server Consolidation in Cloud Systems

Infrastructure as a Service cloud providers are increasingly relying on scalable and efficient Virtual Machines (VMs) placement as the main solution for reducing unnecessarycosts and wastes of physical resources. However, thecontinuous growth of the size of cloud data centers posesscalability challenges to find optimal placement solutions. The use of heuristics and simplified server consolidation models that partially discard information about the VMs behavior represents the typical approach to guarantee scalability, but at the expense of suboptimal placement solutions. A recently proposed alternative approach, namely Class-Based Placement (CBP), divides VMs in classes with similar behavior in terms of resource usage, and addresses scalability by considering a small-scale server consolidation problem that is replicated as a building block for the whole data center. However, the server consolidation model exploited by the CBP technique suffers from two main limitations. First, it considers only one VM resource (CPU) for the consolidation problem. Second, it does not analyze the impact of the number (and size) of building blocks to consider. Many small building blocks may reduce the overall VMs placement solution quality due to fragmentation of the physical server resources over blocks. On the other hand, few large building blocks may become computationally expensive to handle and may be unsolvable due to the problem complexity. This paper extends the CBP server consolidation model to take into account multiple resources. Furthermore, we analyze the impact of block size on the performance of the proposed consolidation model, and we present and compare multiple strategies to estimate the best number of blocks. Our proposal is validated through experimental results based on a real cloud computing data center.

A semi-analytical model for exploring Galilean satellites formation from a massive disk

A better knowledge of jovian satellites’ origins will bring light on the environment that surrounded Jupiter during its formation and can help us to understand the characteristics of this unique satellite system. We developed a semi-analytical model to investigate Jupiter’s regular satellite formation and present the results of our population synthesis calculations. We performed simulations adopting a massive, static, low-viscosity circumplanetary disk model, in agreement with a current study of magnetorotational instability in a circum-planetary disk. We find that the high gas density leads to very rapid migration of satellitesimals due to gas drag and type II migration of satellites in a faster disk-dominated mode. A large concentration of solids, large building blocks and longer type II migration time-scales favor formation and survival of large satellites. However, bodies as massive as Ganymede and those located far away from Jupiter, such as Callisto, are difficult to form with this scenario.

Thermal properties of barley starch and its relation to starch characteristics

Amylopectin fine structure and starch gelatinization and retrogradation were studied in 10 different barley cultivars/breeding lines. Clusters and building blocks were isolated from the amylopectin by α-amylase from Bacillus amyloliquefaciens and their structure was characterized. Gelatinization was studied at a starch:water ratio of 1:3, and retrogradation was studied on gelatinized starch at starch:water ratio of 1:2, by differential scanning calorimetry. Three barley cultivars/breeding lines possessed the amo1 mutation, and they all had a lower molar proportion of chains of DP ≥38 and more of large building blocks. The amo1 mutation also resulted in a higher gelatinization temperature and a broader temperature interval during gelatinization. Overall, small clusters with a dense structure resulted in a higher gelatinization temperature while retrogradation was promoted by short chains in the amylopectin and many large building blocks.

In the beginning was the U1A protein: a personal reflection.

In the beginning was the U1A protein: a personal reflection.