Automated data pre-processing via meta-learning

The final publication is available at link.springer.comA data mining algorithm may perform differently on datasets with different characteristics, e.g., it might perform better on a dataset with continuous attributes rather than with categorical attributes, or the other way around. As a matter of fact, a dataset usually needs to be pre-processed. Taking into account all the possible pre-processing operators, there exists a staggeringly large number of alternatives and nonexperienced users become overwhelmed. We show that this problem can be addressed by an automated approach, leveraging ideas from metalearning. Specifically, we consider a wide range of data pre-processing techniques and a set of data mining algorithms. For each data mining algorithm and selected dataset, we are able to predict the transformations that improve the result of the algorithm on the respective dataset. Our approach will help non-expert users to more effectively identify the transformations appropriate to their applications, and hence to achieve improved results.Peer ReviewedPostprint (published version

Assessing Interaction Networks with Applications to Catastrophe Dynamics and Disaster Management

In this paper we present a versatile method for the investigation of interaction networks and show how to use it to assess effects of indirect interactions and feedback loops. The method allows to evaluate the impact of optimization measures or failures on the system. Here, we will apply it to the investigation of catastrophes, in particular to the temporal development of disasters (catastrophe dynamics). The mathematical methods are related to the master equation, which allows the application of well-known solution methods. We will also indicate connections of disaster management with excitable media and supply networks. This facilitates to study the effects of measures taken by the emergency management or the local operation units. With a fictious, but more or less realistic example of a spreading epidemic disease or a wave of influenza, we illustrate how this method can, in principle, provide decision support to the emergency management during such a disaster. Similar considerations may help to assess measures to fight the SARS epidemics, although immunization is presently not possible

Quality and complexity measures for data linkage and deduplication

Summary. Deduplicating one data set or linking several data sets are increasingly important tasks in the data preparation steps of many data mining projects. The aim of such linkages is to match all records relating to the same entity. Research interest in this area has increased in recent years, with techniques originating from statistics, machine learning, information retrieval, and database research being combined and applied to improve the linkage quality, as well as to increase performance and efficiency when linking or deduplicating very large data sets. Different measures have been used to characterise the quality and complexity of data linkage algorithms, and several new metrics have been proposed. An overview of the issues involved in measuring data linkage and deduplication quality and complexity is presented in this chapter. It is shown that measures in the space of record pair comparisons can produce deceptive quality results. Various measures are discussed and recommendations are given on how to assess data linkage and deduplication quality and complexity. Key words: data or record linkage, data integration and matching, deduplication, data mining pre-processing, quality and complexity measures

Ultrastructural and functional fate of recycled vesicles in hippocampal synapses

Efficient recycling of synaptic vesicles is thought to be critical for sustained information transfer at central terminals. However, the specific contribution that retrieved vesicles make to future transmission events remains unclear. Here we exploit fluorescence and time-stamped electron microscopy to track the functional and positional fate of vesicles endocytosed after readily releasable pool (RRP) stimulation in rat hippocampal synapses. We show that most vesicles are recovered near the active zone but subsequently take up random positions in the cluster, without preferential bias for future use. These vesicles non-selectively queue, advancing towards the release site with further stimulation in an actin-dependent manner. Nonetheless, the small subset of vesicles retrieved recently in the stimulus train persist nearer the active zone and exhibit more privileged use in the next RRP. Our findings reveal heterogeneity in vesicle fate based on nanoscale position and timing rules, providing new insights into the origins of future pool constitution

DNA isolation protocol effects on nuclear DNA analysis by microarrays, droplet digital PCR, and whole genome sequencing, and on mitochondrial DNA copy number estimation.

Potential bias introduced during DNA isolation is inadequately explored, although it could have significant impact on downstream analysis. To investigate this in human brain, we isolated DNA from cerebellum and frontal cortex using spin columns under different conditions, and salting-out. We first analysed DNA using array CGH, which revealed a striking wave pattern suggesting primarily GC-rich cerebellar losses, even against matched frontal cortex DNA, with a similar pattern on a SNP array. The aCGH changes varied with the isolation protocol. Droplet digital PCR of two genes also showed protocol-dependent losses. Whole genome sequencing showed GC-dependent variation in coverage with spin column isolation from cerebellum. We also extracted and sequenced DNA from substantia nigra using salting-out and phenol / chloroform. The mtDNA copy number, assessed by reads mapping to the mitochondrial genome, was higher in substantia nigra when using phenol / chloroform. We thus provide evidence for significant method-dependent bias in DNA isolation from human brain, as reported in rat tissues. This may contribute to array "waves", and could affect copy number determination, particularly if mosaicism is being sought, and sequencing coverage. Variations in isolation protocol may also affect apparent mtDNA abundance

Wave Energy Converter for Marine Vessels and Isolated Communities

California Polytechnic State University’s 2023 Marine Energy Collegiate Competition team, Surf Supply, has developed a floating dock that transduces wave energy into electricity. The following report aligns with MECC requirements, and our design changes since CDR are present in the User Manual in Appendix F. Our primary market research of the Blue Economy identified electric marine vessel charging and isolated communities as early adopters that could benefit most from the first generation of our wave energy converter (WEC). Surf Supply’s design concept provides a reliable, affordable, and renewable energy source that reduces dependency on conventional fossil fuels, allowing blue economy industries to have increased energy independence. Our design uses a winch mechanism to generate rotational mechanical power from swells, that, when coupled with a generator, produces electricity. The electrical energy is stored in an on-board battery, so power can be supplied to end users on demand. A key advantage of Surf Supply’s WEC is its small, modular design, which allows for operation in low-energy sea states and ease of scalability. Further, the design maximizes use of commercial, off-the-shelf parts, minimizing the costs associated with custom manufacturing. Through our participation in the Build and Test challenge, we were able to test the mechanical and electrical system designs and identify areas for improvement. With continued development, a commercial-ready product promises to increase Surf Supply’s early adopter market share, eventually expanding into adjacent markets such as desalination. We feel confident that Surf Supply’s wave energy concept could prove to be competitive in the market and experience sustained growth as the demand for clean, independent energy rises

Reprogramming the assembly of unmodified DNA with a small molecule

The ability of DNA to store and encode information arises from base pairing of the four-letter nucleobase code to form a double helix. Expanding this DNA ‘alphabet’ by synthetic incorporation of new bases can introduce new functionalities and enable the formation of novel nucleic acid structures. However, reprogramming the self-assembly of existing nucleobases presents an alternative route to expand the structural space and functionality of nucleic acids. Here we report the discovery that a small molecule, cyanuric acid, with three thymine-like faces reprogrammes the assembly of unmodified poly(adenine) (poly(A)) into stable, long and abundant fibres with a unique internal structure. Poly(A) DNA, RNA and peptide nucleic acid all form these assemblies. Our studies are consistent with the association of adenine and cyanuric acid units into a hexameric rosette, which brings together poly(A) triplexes with a subsequent cooperative polymerization. Fundamentally, this study shows that small hydrogen-bonding molecules can be used to induce the assembly of nucleic acids in water, which leads to new structures from inexpensive and readily available materials

Carbon sequestration potential and physicochemical properties differ between wildfire charcoals and slow-pyrolysis biochars

Pyrogenic carbon (PyC), produced naturally (wildfire charcoal) and anthropogenically (biochar), is extensively studied due to its importance in several disciplines, including global climate dynamics, agronomy and paleosciences. Charcoal and biochar are commonly used as analogues for each other to infer respective carbon sequestration potentials, production conditions, and environmental roles and fates. The direct comparability of corresponding natural and anthropogenic PyC, however, has never been tested. Here we compared key physicochemical properties (elemental composition, δ13C and PAHs signatures, chemical recalcitrance, density and porosity) and carbon sequestration potentials of PyC materials formed from two identical feedstocks (pine forest floor and wood) under wildfire charring- and slow-pyrolysis conditions. Wildfire charcoals were formed under higher maximum temperatures and oxygen availabilities, but much shorter heating durations than slow-pyrolysis biochars, resulting in differing physicochemical properties. These differences are particularly relevant regarding their respective roles as carbon sinks, as even the wildfire charcoals formed at the highest temperatures had lower carbon sequestration potentials than most slow-pyrolysis biochars. Our results challenge the common notion that natural charcoal and biochar are well suited as proxies for each other, and suggest that biochar’s environmental residence time may be underestimated when based on natural charcoal as a proxy, and vice versa

Effect of Metformin on the High-Density Lipoprotein Proteome in Youth with Type 1 Diabetes

Background: Youth with type 1 diabetes (T1D) have normal or elevated High-Density Lipoprotein Cholesterol (HDL-C), however, the function of HDL, partly mediated by the HDL proteome, may be impaired. Metformin can be used as an adjunct therapy in youth with T1D, but its effects on the HDL proteome are unknown. Objective: To determine the effect of metformin on the HDL proteome. Subjects: Youth (12-20 years old) with T1D who had a BMI \u3e 90th percentile, HbA1c \u3e 8.0% and Tanner stage 5. Methods: Double-blinded, placebo-controlled randomized sub-study. We examined the effects of metformin (n = 25) or placebo (n = 10) after 6 months on HDL proteome. Changes in HDL proteins were measured by data-independent acquisition (DIA) mass spectrometry and compared between treatment groups. As a secondary outcome, associations between proteins of interest and the most studied function of HDL, the cholesterol efflux capacity (CEC), was examined. Results: The relative abundance of 84 HDL-associated proteins were measured. Two proteins were significantly affected by metformin treatment, peptidoglycan recognition protein 2 (PGRP2; +23.4%, p = .0058) and alpha-2-macroglobulin (A2MG; +29.8%, p = .049). Metformin did not significantly affect CEC. Changes in affected HDL proteins did not correlate with CEC. Conclusions: Despite having little effect on HDL-C, metformin increased PGRP2 and A2MG protein on HDL in youth with T1D, but had no significant effect on CEC. Further studies are needed to understand the impact of PGRP2 and A2MG on other HDL functions

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes