Knowledge-based recommender systems: overview and research directions

Recommender systems are decision support systems that help users to identify items of relevance from a potentially large set of alternatives. In contrast to the mainstream recommendation approaches of collaborative filtering and content-based filtering, knowledge-based recommenders exploit semantic user preference knowledge, item knowledge, and recommendation knowledge, to identify user-relevant items which is of specific relevance when dealing with complex and high-involvement items. Such recommenders are primarily applied in scenarios where users specify (and revise) their preferences, and related recommendations are determined on the basis of constraints or attribute-level similarity metrics. In this article, we provide an overview of the existing state-of-the-art in knowledge-based recommender systems. Different related recommendation techniques are explained on the basis of a working example from the domain of survey software services. On the basis of our analysis, we outline different directions for future research.

Polymorphism and orientation control of copper-dicarboxylate metal-organic framework thin films through vapour- and liquid-phase growth

Precise control over the crystalline phase and crystallographic orientation within thin films of metal-organic frameworks (MOFs) is highly desirable. Here, we report a comparison of the liquid- and vapour-phase film deposition of two copper-dicarboxylate MOFs starting from an oriented metal hydroxide precursor. X-ray diffraction revealed that the vapour- or liquid-phase reaction of the linker with this precursor results in different crystalline phases, morphologies, and orientations. Pole figure analysis showed that solution-based growth of the MOFs follows the axial texture of the metal hydroxide precursor, resulting in heteroepitaxy. In contrast, the vapour-phase method results in non-epitaxial growth with uniplanar texture only.

Recommender systems for sustainability: overview and research issues

Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.

Unraveling the timescale of the structural photo-response within oriented metal-organic framework films

Fundamental knowledge on the intrinsic timescale of structural transformations in photo-switchable metal-organic framework films is crucial to tune their switching performance and to facilitate their applicability as stimuli-responsive materials. In this work, for the first time, an integrated approach to study and quantify the temporal evolution of structural transformations is demonstrated on an epitaxially oriented DMOF-1-on-MOF film system comprising azobenzene in the DMOF-1 pores (DMOF-1/AB). We employed time-resolved Grazing Incidence Wide-Angle X-Ray Scattering measurements to track the structural response of the DMOF-1/AB film upon altering the length of the azobenzene molecule by photo-isomerization (trans-to-cis, 343 nm; cis-to-trans, 450 nm). Within seconds, the DMOF-1/AB response occurred fully reversible and over several switching cycles by cooperative photo-switching of the oriented DMOF-1/AB crystallites as confirmed further by infrared measurements. Our work thereby suggests a new avenue to elucidate the timescales and photo-switching characteristics in structurally responsive MOF film systems.

Neoptile feathers contribute to outline concealment of precocial chicks

Camouflage is a widespread strategy to increase survival. The cryptic plumage colouration of precocial chicks improves camouflage often through disruptive colouration. Here, we examine whether and how fringed neoptile feathers conceal the outline of chicks. We first conducted a digital experiment to test two potential mechanisms for outline concealment through appendages: (1) reduction of edge intensity and (2) luminance transition. Local Edge Intensity Analysis showed that appendages decreased edge intensity whereas a mean luminance comparison revealed that the appendages created an intermediate transition zone to conceal the object's outline. For edge intensity, the outline diffusion was strongest for a vision system with low spatial acuity, which is characteristic of many mammalian chick predators. We then analysed photographs of young snowy plover (Charadrius nivosus) chicks to examine whether feathers increase outline concealment in a natural setting. Consistent with better camouflage, the outline of digitally cropped chicks with protruding feathers showed lower edge intensities than the outline of chicks without those feathers. However, the observed mean luminance changes did not indicate better concealment. Taken together, our results suggest that thin skin appendages such as neoptile feathers improve camouflage. As skin appendages are widespread, this mechanism may apply to many organisms.

Phase dependent encapsulation and release profile of ZIF-based biocomposites

Biocomposites composed of Zeolitic Imidazolate Frameworks (ZIFs) are generating significant interest due to their facile synthesis, and capacity to protect proteins from harsh environments. Here we systematically varied the composition (i.e. relative amounts of ligand (2-methylimidazole), metal precursor (Zn(OAc)2·2H2O), and protein) and post synthetic treatments (i.e. washes with water or water/ethanol) to prepare a series of protein@ZIF biocomposites. These data were used to construct two ternary phase diagrams that showed the synthesis conditions employed gave rise to five different phases including, for the first time, biocomposites based on ZIF-CO3-1. We examined the influence of the different phases on two properties relevant to drug delivery applications: encapsulation efficiency and release profile. The encapsulation efficiencies of bovine serum albumin and insulin were phase dependent and ranged from 75% to 100%. In addition, release profiles showed that 100% protein release varied between 40 and 300 minutes depending on the phase. This study provides a detailed compositional map for the targeted preparation of ZIF-based biocomposites of specific phases and a tool for the straightforward analysis of the crystalline phases of ZIF based materials (web application named "ZIF phase analysis"). These data will facilitate the progress of ZIF bio-composites in the fields of biomedicine and biotechnology.