Swiss Army Research Articles

R2SCAN-3c: A "Swiss army knife" composite electronic-structure method.

The recently proposed r2SCAN meta-generalized-gradient approximation (mGGA) of Furness and co-workers is used to construct an efficient composite electronic-structure method termed r2SCAN-3c. To this end, the unaltered r2SCAN functional is combined with a tailor-made triple-ζ Gaussian atomic orbital basis set as well as with refitted D4 and geometrical counter-poise corrections for London-dispersion and basis set superposition error. The performance of the new method is evaluated for the GMTKN55 database covering large parts of chemical space with about 1500 data points, as well as additional benchmarks for non-covalent interactions, organometallic reactions, and lattice energies of organic molecules and ices, as well as for the adsorption on polar salt and non-polar coinage-metal surfaces. These comprehensive tests reveal a spectacular performance and robustness of r2SCAN-3c: It by far surpasses its predecessor B97-3c at only twice the cost and provides one of the best results of all semi-local density-functional theory (DFT)/QZ methods ever tested for the GMTKN55 database at one-tenth of the cost. Specifically, for reaction and conformational energies as well as non-covalent interactions, it outperforms prominent hybrid-DFT/QZ approaches at two to three orders of magnitude lower cost. Perhaps, the most relevant remaining issue of r2SCAN-3c is self-interaction error (SIE), owing to its mGGA nature. However, SIE is slightly reduced compared to other (m)GGAs, as is demonstrated in two examples. After all, this remarkably efficient and robust method is chosen as our new group default, replacing previous composite DFT and partially even expensive high-level methods in most standard applications for systems with up to several hundreds of atoms.

C-H Electrophilic (phenylsulfonyl)difluoromethylation of (hetero)arenes with a newly designed reagent.

The synthesis of an original electrophilic difluoromethylating reagent was successfully achieved upon a straightforward protocol (3 steps). Like a Swiss army knife, this bench-stable reagent allowed the functionalization of various classes of compounds under mild and transition metal-free conditions. Hence, an efficient and operationally simple tool for the construction of C(sp2)-, C(sp3)- and S-CF2SO2Ph bonds was provided, expanding the chemical space of PhSO2CF2-containing molecules. Late-stage functionalization of bioactive molecules and the synthesis of PhSO2CF2- and HCF2-analogs of Lidocaine were also successfully achieved.

The Percentile Bootstrap: A Primer With Step-by-Step Instructions in R

The percentile bootstrap is the Swiss Army knife of statistics: It is a nonparametric method based on data-driven simulations. It can be applied to many statistical problems, as a substitute to standard parametric approaches, or in situations for which parametric methods do not exist. In this Tutorial, we cover R code to implement the percentile bootstrap to make inferences about central tendency (e.g., means and trimmed means) and spread in a one-sample example and in an example comparing two independent groups. For each example, we explain how to derive a bootstrap distribution and how to get a confidence interval and a p value from that distribution. We also demonstrate how to run a simulation to assess the behavior of the bootstrap. For some purposes, such as making inferences about the mean, the bootstrap performs poorly. But for other purposes, it is the only known method that works well over a broad range of situations. More broadly, combining the percentile bootstrap with robust estimators (i.e., estimators that are not overly sensitive to outliers) can help users gain a deeper understanding of their data than they would using conventional methods.

CXC chemokine ligand 16: a Swiss army knife chemokine in cancer.

Today, cancer is one of the leading causes of death worldwide. Lately, cytokine and chemokine imbalances have gained attention amongst different involved pathways in cancer development and attracted much consideration in cancer research. CXCL16, as a member of the CXC subgroup of chemokines, has been attributed to be responsible for immune cell infiltration into the tumour microenvironment. The aberrant expression of CXCL16 has been observed in various cancers. This chemokine has been shown to play a conflicting role in tumour development through inducing pro-inflammatory conditions. The infiltration of various immune and non-immune cells such as lymphocytes, cancer-associated fibroblasts and myeloid-derived suppressor cells by CXCL16 into the tumour microenvironment has complicated the tumour fate. Given this diverse role of CXCL16 in cancer, a better understanding of its function might build-up our knowledge about tumour biology. Hence, this study aimed to review the impact of CXCL16 in cancer and explored its therapeutic application. Consideration of these findings might provide opportunities to achieve novel approaches in cancer treatment and its prognosis.

Nested Species Distribution Models of Chlamydiales in Ixodes ricinus (Tick) Hosts in Switzerland.

The tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, which potentially cause respiratory infections. In this study, we modeled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2,293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application, and a prospective campaign. For each tick location, we retrieved from Swiss federal data sets the environmental factors reflecting the topography, climate, and land cover. We then used the Maxent modeling technique to estimate the suitability of particular areas for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus habitat suitability is determined by higher temperature and normalized difference vegetation index (NDVI) values, lower temperature during the driest months, and a higher percentage of artificial and forest areas. The performance of the model was improved when extracting the environmental variables for a 100-m radius buffer around the sampling points and when considering the climatic conditions of the 2 years previous to the sampling date. Chlamydiales bacteria were favored by a lower percentage of artificial surfaces, drier conditions, high precipitation during the coldest months, and short distances to wetlands. From 2009 to 2018, we observed an extension of areas suitable to ticks and Chlamydiales, associated with a shift toward higher altitude. The importance of considering spatiotemporal variations in the environmental conditions for obtaining better prediction was also demonstrated.IMPORTANCEIxodes ricinus is the vector of pathogens including the agent of Lyme disease, the tick-borne encephalitis virus, and the less well-known Chlamydiales bacteria, which are responsible for certain respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results also provided the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable information for decision makers in controlling tick-borne diseases in Switzerland and establishing prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen pairs to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

Protective Swiss army knives: Intrinsically disordered protein function can be augmented and fine tuned by environmental factors

Protective Swiss army knives: Intrinsically disordered protein function can be augmented and fine tuned by environmental factors

Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows

Over the last two decades, the field of computational science has seen a dramatic shift towards incorporating high-throughput computation and big-data analysis as fundamental pillars of the scientific discovery process. This has necessitated the development of tools and techniques to deal with the generation, storage and processing of large amounts of data. In this work we present an in-depth look at the workflow engine powering AiiDA, a widely adopted, highly flexible and database-backed informatics infrastructure with an emphasis on data reproducibility. We detail many of the design choices that were made which were informed by several important goals: the ability to scale from running on individual laptops up to high-performance supercomputers, managing jobs with runtimes spanning from fractions of a second to weeks and scaling up to thousands of jobs concurrently, and all this while maximising robustness. In short, AiiDA aims to be a Swiss army knife for high-throughput computational science. As well as the architecture, we outline important API design choices made to give workflow writers a great deal of liberty whilst guiding them towards writing robust and modular workflows, ultimately enabling them to encode their scientific knowledge to the benefit of the wider scientific community.

Svpluscnv: analysis and visualization of complex structural variation data.

Despite widespread prevalence of somatic structural variations (SVs) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer's somatic landscape. svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant segmentation profiles and sequencing-based structural variant calls. The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets. https://github.com/ccbiolab/svpluscnv. Supplementary data are available at Bioinformatics online.

Towards a Swiss Army Knife State? The changing face of economic interventionism in advanced democracies, 1980–2015

This article systematically reviews trends in numerous economic policy indicators in eighteen OECD countries since the early 1980s, synthesizing findings about the fate of states’ economic interventionism from several customarily separate literatures. Rather than observing any paradigmatic policy shift, the review finds that policies with markedly different ideational foundations currently cohabitate. In line with non-interventionist prescriptions, policymakers have largely abandoned the intrusive heterodox ‘power tools’ of previous eras, while establishing new norms for monetary policy based on monetarist theory. However, this has not led to a full retreat of economic interventionism. Instead, policymakers are gradually developing a new, albeit more constrained, approach to promoting economic activity in line with selected distributional goals – here labelled the micro-interventionist state, or the ‘Swiss Army Knife State’, as it were. The cross-partisan appeal of the ‘multi-tools’ associated with this approach – such as horizontal industrial policy, active social policy, and strategic tax expenditures and procurement – partly stems from their versatility, as policymakers can use them to very different distributional ends. To better understand the politics and distributional consequences of contemporary economic policies, scholars need to take their versatility more seriously, shifting focus theoretically and empirically from how much to how policymakers intervene in the economy.

Graphene, the Swiss Army Knife of Nanomaterials Science

Graphene, the Swiss Army Knife of Nanomaterials Science

A Computational Swiss Army Knife Approach to Unraveling the Secrets of Proton Movement through SERCA

A Computational Swiss Army Knife Approach to Unraveling the Secrets of Proton Movement through SERCA

A Swiss army knife? How science challenges our understanding of mindfulness in the workplace

Abstract While mindfulness has demonstrated many advantages in the workplace, this paper addresses important issues around the future of mindfulness at work. We begin by clarifying our understanding of mindfulness in the workplace. This is followed by a discussion on the problematic nature of mindfulness-based interventions in workplaces and potential guidance is provided for those who intend to undertake interventions. Finally, we examine how workplaces are naturalistic settings that differ in how they can nurture mindfulness in employees. Ultimately this paper provides organizations and practitioners insight into potential issues in navigating mindfulness at work, while also providing cautionary optimism around the future of mindfulness in the workplace.

Smartphone: The winegrowers’ Swiss army knife

Mobile applications have found their rightful place in the working world. It is of course equally the case in the winegrowing sector! Whether it be to help the winegrower identify weeds, to estimate the porosity of foliage or share their observations, these applications represent a real tool in their daily life.

Nigeria's Income Tax (Transfer Pricing) Regulations 2018: Conceptualizing the Elephant and “Plucking the Goose”

AbstractIn 2015, the OECD gave the world a template to address base erosion and profit shifting and ensure that profit is taxed in the jurisdiction of value addition and / or where economic activities take place. The world's jurisdictions then embarked on implementing the template. Examining the legal framework subsequently put in place for the taxation of intangibles in Nigeria, this article argues that the distinct regimes for connected and unconnected persons’ transactions create flaws. It further asserts that these flaws are consequences of the conflict between the policy that underpins the legal framework and other policies in the country. It concludes that the legal framework may not be a “Swiss army knife” (providing Nigeria with all that is needed to combat transfer pricing issues associated with the transfer of intangibles by connected persons), as it creates issues that have undesired consequences for the taxation as well as the economic system.

Defensins: A Double-Edged Sword in Host Immunity.

Defensins are a major family of host defense peptides expressed predominantly in neutrophils and epithelial cells. Their broad antimicrobial activities and multifaceted immunomodulatory functions have been extensively studied, cementing their role in innate immunity as a core host-protective component against bacterial, viral and fungal infections. More recent studies, however, paint defensins in a bad light such that they are “alleged” to promote viral and bacterial infections in certain biological settings. This mini review summarizes the latest findings on the potential pathogenic properties of defensins against the backdrop of their protective roles in antiviral and antibacterial immunity. Further, a succinct description of both tumor-proliferative and -suppressive activities of defensins is also given to highlight their functional and mechanistic complexity in antitumor immunity. We posit that given an enabling environment defensins, widely heralded as the “Swiss army knife,” can function as a “double−edged sword” in host immunity.

Switchable Membrane Remodeling and Antifungal Defense by Metamorphic Chemokine XCL1.

Antimicrobial peptides (AMPs) are a class of molecules which generally kill pathogens via preferential cell membrane disruption. Chemokines are a family of signaling proteins that direct immune cell migration and share a conserved α–β tertiary structure. Recently, it was found that a subset of chemokines can also function as AMPs, including CCL20, CXCL4, and XCL1. It is therefore surprising that machine learning based analysis predicts that CCL20 and CXCL4’s α-helices are membrane disruptive, while XCL1’s helix is not. XCL1, however, is the only chemokine known to be a metamorphic protein which can interconvert reversibly between two distinct native structures (a β-sheet dimer and the α–β chemokine structure). Here, we investigate XCL1’s antimicrobial mechanism of action with a focus on the role of metamorphic folding. We demonstrate that XCL1 is a molecular “Swiss army knife” that can refold into different structures for distinct context-dependent functions: whereas the α–β chemokine structure controls cell migration by binding to G-Protein Coupled Receptors (GPCRs), we find using small angle X-ray scattering (SAXS) that only the β-sheet and unfolded XCL1 structures can induce negative Gaussian curvature (NGC) in membranes, the type of curvature topologically required for membrane permeation. Moreover, the membrane remodeling activity of XCL1’s β-sheet structure is strongly dependent on membrane composition: XCL1 selectively remodels bacterial model membranes but not mammalian model membranes. Interestingly, XCL1 also permeates fungal model membranes and exhibits anti-Candida activity in vitro, in contrast to the usual mode of antifungal defense which requires Th17 mediated cell-based responses. These observations suggest that metamorphic XCL1 is capable of a versatile multimodal form of antimicrobial defense.

The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code

The recently introduced data structure, the Matrix Profile, annotates a time series by recording the location of and distance to the nearest neighbor of every subsequence. This information trivially provides answers to queries for both time series motifs and time series discords, perhaps two of the most frequently used primitives in time series data mining. One attractive feature of the Matrix Profile is that it completely divorces the high-level details of the analytics performed, from the computational “heavy lifting.” The Matrix Profile can be computed using the appropriate computational paradigm for the task at hand: CPU, GPU, FPGA, distributed computing, anytime computation, incremental computation, and so forth. However, all the details of such computation can be hidden from the analyst who only needs to think about her analytical need. In this work, we expand on this philosophy and ask the following question: If we assume that we get the Matrix Profile for free, what interesting analytics can we do, writing at most ten lines of code? As we will show, the answer is surprisingly large and diverse. Our aim here is not to establish or compete with state-of-the-art results, but merely to show that we can both reproduce the results of many existing algorithms and find novel regularities in time series data collections with very little effort.

Visualizing protein structures - tools and trends.

Molecular visualization is fundamental in the current scientific literature, textbooks and dissemination materials. It provides an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Tools for visual exploration of structural data have become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. This mini-review was written as a short and compact overview for scientists who need to visualize protein structures and want to make an informed decision which tool they should use. Here, we first describe a few 'Swiss Army knives' geared towards protein visualization for everyday use with an existing large user base, then focus on more specialized tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.

The cutting edge-an investigation into the pressure necessary for cutting skin with different knife blade types.

Sharp force trauma is routinely encountered in forensic practice. Often the question is posed, how much pressure or energy would have been necessary to inflict a cut with a specific knife, in order to further characterize the perpetrator or determine his intent to cause harm. This paper investigates two knife blades and its individual pressures needed to cut through the epidermis and dermis. In order to examine the necessary force for cutting through the skin, we performed experiments on a piglet skin-on-gelatin phantom. Two similarly small knives-a paring knife with a serrated blade and a Swiss Army pocket knife with a smooth blade-were moved over the phantom surface using a mobile cutting apparatus with varying weight on the load arm with the knife. The depth of the cut was to be determined according to a scale from zero to three: grade 0 = no cut; grade 1 = cut into epidermis only; grade 2 = cut into dermis; grade 3 = complete transection of the entire skin. Each cut inflicted at a specific pressure force was assessed closely in order to ascertain depth, calculate the velocity, and ultimately determine the point at which a cut would inflict grade 3 damage. The smooth blade of a pocket knife needed at least 1900g pressure in order to slice through pig skin mounted on a thick gelatin block, whereas a serrated blade of a paring knife managed to cut into or through the dermis at a comparatively lower force of 700g. Our study shows that at the same cutting velocity, a significant difference in pressure is necessary to inflict the same degree of damage.

Characteristics of method extractions in Java: a large scale empirical study

Extract method is the “Swiss army knife” of refactorings: developers perform method extraction to introduce alternative signatures, decompose long code, improve testability, among many other reasons. Although the rationales behind method extraction are well explored, we are not yet aware of its characteristics. Assessing this information can provide the basis to better understand this important refactoring operation as well as improve refactoring tools and techniques based on the actual behavior of developers. In this paper, we assess characteristics of the extract method refactoring. We rely on a state-of-the-art technique to detect method extraction, and analyze over 70K instances of this refactoring, mined from 124 software systems. We investigate five aspects of this operation: magnitude, content, transformation, size, and degree. We find that (i) the extract method is among the most popular refactorings; (ii) extracted methods are over represented on operations related to creation, validation, and setup; (iii) methods that are targets of the extractions are 2.2x longer than the average, and they are reduced by one statement after the extraction; and (iv) single method extraction represents most, but not all, of the cases. We conclude by proposing improvements to refactoring detection, suggestion, and automation tools and techniques to support both practitioners and researchers.