Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...     

Statistical hierarchical clustering algorithm for outlier detection in evolving data streams

Machine Learning - Anomaly detection is a hard data analysis process that requires constant creation and improvement of data analysis algorithms. Using traditional clustering algorithms to analyse...     

A Comprehensive Review of Genetically Engineered Mouse Models for Prader-Willi Syndrome Research

Prader-Willi syndrome (PWS) is a neurogenetic multifactorial disorder caused by the deletion or inactivation of paternally imprinted genes on human chromosome 15q11-q13. The affected homologous locus is on mouse chromosome 7C. The positional conservation and organization of genes including the imprinting pattern between mice and men implies similar physiological functions of this locus. Therefore, considerable efforts to recreate the pathogenesis of PWS have been accomplished in mouse models. We provide a summary of different mouse models that were generated for the analysis of PWS and discuss their impact on our current understanding of corresponding genes, their putative functions and the pathogenesis of PWS. Murine models of PWS unveiled the contribution of each affected gene to this multi-facetted disease, and also enabled the establishment of the minimal critical genomic region (PWScr) responsible for core symptoms, highlighting the importance of non-protein coding genes in the PWS locus. Although the underlying disease-causing mechanisms of PWS remain widely unresolved and existing mouse models do not fully capture the entire spectrum of the human PWS disorder, continuous improvements of genetically engineered mouse models have proven to be very powerful and valuable tools in PWS research.     

Microstructure and mechanical properties of Mg-5Li-1Al sheets prepared by accumulative roll bonding

Ultrafine-grain and high-strength Mg-5Li-1Al sheets were prepared by accumulative roll bonding (ARB) process. Evolution of microstructure and mechanical properties of ARB-processed Mg-5Li-1Al sheets was investigated.Results show that, during ARB process, the evolution of deformation mechanism of t Mg-5Li-1Al alloy is as follows: twinning deformation, shear deformation, forming macro shear zone, and finally dynamic recrystallization (DRX). The grain refining mechanism changes from twin DRX to rotation DRX. With the increase in ARB cycles, strength of the Mg-5Li-1Al sheets is enhanced, whilst elongation varies slightly. With the increase in rolling cycles, anisotropy of mechanical properties decreases. It is conclusive that strain hardening and grain refinement dominate the strengthening mechanism of Mg-5Li-1Al alloy.     

Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.     

Biosorbents based on pine sawdust and malt sprouts for preconcentration and ICP-OES determination of nonferrous,heavy, and precious metals in the environmental samples

Pine sawdust and malt sprouts modified with orthophosphoric acid and carbamide have been proposed for solid-phase extraction (SPE) of nonferrous, heavy, and precious metals and their subsequent determination in the environmental samples by inductively coupled plasma optical emission spectrometry (ICP-OES). Modified adsorbents were characterized by SEM, TGA, and FT-IR and compared with native matrixes. SPE of some nonferrous and precious metal ions by biosorbents was studied. Depending on the SPE conditions, it was possible to separate nonferrous and heavy metals from alkali and alkaline earth metals. The proposed adsorbents are effective for preconcentration of nonferrous and heavy metals from natural waters and precious metals from solutions after digestion of geological samples.     

Methods and Applications of In Silico Aptamer Design and Modeling

Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.     

Pulsed laser reshaping and fragmentation of upconversion nanoparticles — from hexagonal prisms to 1D nanorods through “Medusa”-like structures

One dimensional (1D) nanostructures attract considerable attention, enabling a broad application owing to their unique properties. However, the precise mechanism of 1D morphology attainment remains a matter of debate. In this study, ultrafast picosecond (ps) laser-induced treatment on upconversion nanoparticles (UCNPs) is offered as a tool for 1D-nanostructures formation. Fragmentation, reshaping through recrystallization process and bioadaptation of initially hydrophobic (β-Na_1.5Y_1.5F₆: Yb³⁺, Tm³⁺/β-Na_1.5Y_1.5F₆) core/shell nanoparticles by means of one-step laser treatment in water are demonstrated. “True” 1D nanostructures through “Medusa”-like structures can be obtained, maintaining anti-Stokes luminescence functionalities. A matter of the one-dimensional UCNPs based on direction of energy migration processes is debated. The proposed laser treatment approach is suitable for fast UCNP surface modification and nano-to-nano transformation, that open unique opportunities to expand UCNP applications in industry and biomedicine.

     

Dissolved organic matter, aluminium and iron interactions: precipitation induced by metal/carbon ratio, pH and competition

To better understand the precipitation behaviour of dissolved organic matter induced by interactions with metals, a systematic titration experiment was conducted mimicking the soil solution conditions in an acidic, sandy soil. The variables of interest included the type of metal species (Al, Fe), the redox state [Fe(II), Fe(III)], the pH (3.5, 4.0, 4.5), the metal to organic carbon (M/C) ratio and the competition between Al and Fe. Precipitation of DOM–Al appeared to be strongly correlated with M/C ratio and the pH. For Fe(II) only little precipitation occurred, while the strongest flocculation degree was found after addition of Fe(III). In contrast to Al, hardly any correlation between DOM–Fe precipitation and pH was observed. Both reduction and oxidation of Fe was found and exhibited a strong effect on the precipitated amounts of DOM and Fe. In competition, Al determined the precipitation behaviour at lower M/C ratios (<0.10), while at higher M/C ratios Fe determined the flocculation. Below a M/C ratio of 0.06 Al was the dominant metal in the precipitates, especially at lower pH levels, while the opposite trend was found at M/C ratios above 0.06. Overall, Fe(III) gave the strongest flocculation, although Al influenced the impact of Fe(III) interactions with DOM in relation to pH and M/C ratio.     

Assessing landscape preferences: a visual choice experiment in the agricultural region of Märkische Schweiz,Germany

Natural amenities and the aesthetic value of agricultural landscapes are important territorial assets for improving rural tourism and the quality of the living environment. To identify which characteristics shape the visual quality of a landscape, a stated-preference survey was conducted (N = 200) using photorealistic landscape visualisations of four different landscape attributes (point green elements, linear green elements, crop diversity and presence of livestock). We estimated respondents’ preferences for landscape attributes, examined the extent of agreement among respondents and identified socio-economic factors influencing their responses. Results revealed that point elements had the highest general preference. About 70% of respondents preferred diverse and highly structured landscapes, while about 30% of respondents had opposing preferences. Preferences were also found to be dependent on the individual’s sociocultural background, such as their level of education, gender or age. These results can help to improve the multi-objective targeting of policies by including an aesthetic value perspective.