Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks

Digital Supply Chain Surveillance (DSCS) is the proactive monitoring and analysis of digital data that allows firms to extract information related to a supply network, without the explicit consent of firms involved in the supply chain. AI has made DSCS to become easier and larger-scale, posing significant opportunities for automated detection of actors and dependencies involved in a supply chain, which in turn, can help firms to detect risky, unethical and environmentally unsustainable practices. Here, we define DSCS, review priority areas using a survey conducted in the UK. Visibility, sustainability, resilience are significant areas that DSCS can support, through a number of machine-learning approaches and predictive algorithms. Despite anecdotal narrative on the importance of explainability of algorithmic results, practitioners often prefer accuracy over explainability; however, there are significant differences between industrial sectors and application areas. Using a case study, we highlight a number of concerns on the unchecked use of AI in DSCS, such as bias or misinterpretation resulting in erroneous conclusions, which may lead to suboptimal decisions or relationship damage. Building on this, we develop and discuss a number of illustrative cases to highlight risks that practitioners should be aware of, proposing key areas of further research

Age-related macular degeneration and smoking cessation advice by eye care providers: a pilot study

This is the final version of the article. Available from the publisher via the link in this record.Smoking is a modifiable risk factor for age-related macular degeneration (AMD), the leading cause of irreversible vision loss in the United States. We conducted a pilot study among eye care providers and AMD patients to assess smoking cessation preferences and cessation services offered at a large academic medical center. Most patients who smoke reported never being advised to quit smoking, although most eye care providers reported that they had advised smokers to quit. Two-thirds of providers expressed a desire for additional training and resources to support patient quit attempts, indicating the need for the integration of smoking cessation opportunities in the clinic setting.Support for this study was provided in part by a National Eye Institute grant (no. R21-EY019096)

Rapid Screening of Complex DNA Samples by Single-Molecule Amplification and Sequencing

Microbial cloning makes Sanger sequencing of complex DNA samples possible but is labor intensive. We present a simple, rapid and robust method that enables laboratories without special equipment to perform single-molecule amplicon sequencing, although in a low-throughput manner, from sub-picogram quantities of DNA. The method can also be used for quick quality control of next-generation sequencing libraries, as was demonstrated for a metagenomic sample

Coronary Artery Plaque Characterization from CCTA Scans Using Deep Learning and Radiomics

Assessing coronary artery plaque segments in coronary CT angiography scans is an important task to improve patient management and clinical outcomes, as it can help to decide whether invasive investigation and treatment are necessary. In this work, we present three machine learning approaches capable of performing this task. The first approach is based on radiomics, where a plaque segmentation is used to calculate various shape-, intensity- and texture-based features under different image transformations. A second approach is based on deep learning and relies on centerline extraction as sole prerequisite. In the third approach, we fuse the deep learning approach with radiomic features. On our data the methods reached similar scores as simulated fractional flow reserve (FFR) measurements, which - in contrast to our methods - requires an exact segmentation of the whole coronary tree and often time-consuming manual interaction. In literature, the performance of simulated FFR reaches an AUC between 0.79–0.93 predicting an abnormal invasive FFR that demands revascularization. The radiomics approach achieves an AUC of 0.84, the deep learning approach 0.86 and the combined method 0.88 for predicting the revascularization decision directly. While all three proposed methods can be determined within seconds, the FFR simulation typically takes several minutes. Provided representative training data in sufficient quantities, we believe that the presented methods can be used to create systems for fully automatic non-invasive risk assessment for a variety of adverse cardiac events

Quantifying Inactive Lithium in Lithium Metal Batteries

Inactive lithium (Li) formation is the immediate cause of capacity loss and catastrophic failure of Li metal batteries. However, the chemical component and the atomic level structure of inactive Li have rarely been studied due to the lack of effective diagnosis tools to accurately differentiate and quantify Li+ in solid electrolyte interphase (SEI) components and the electrically isolated unreacted metallic Li0, which together comprise the inactive Li. Here, by introducing a new analytical method, Titration Gas Chromatography (TGC), we can accurately quantify the contribution from metallic Li0 to the total amount of inactive Li. We uncover that the Li0, rather than the electrochemically formed SEI, dominates the inactive Li and capacity loss. Using cryogenic electron microscopies to further study the microstructure and nanostructure of inactive Li, we find that the Li0 is surrounded by insulating SEI, losing the electronic conductive pathway to the bulk electrode. Coupling the measurements of the Li0 global content to observations of its local atomic structure, we reveal the formation mechanism of inactive Li in different types of electrolytes, and identify the true underlying cause of low Coulombic efficiency in Li metal deposition and stripping. We ultimately propose strategies to enable the highly efficient Li deposition and stripping to enable Li metal anode for next generation high energy batteries

Nanopods: A New Bacterial Structure and Mechanism for Deployment of Outer Membrane Vesicles

Background: Bacterial outer membrane vesicles (OMV) are packets of periplasmic material that, via the proteins and other molecules they contain, project metabolic function into the environment. While OMV production is widespread in proteobacteria, they have been extensively studied only in pathogens, which inhabit fully hydrated environments. However, many (arguably most) bacterial habitats, such as soil, are only partially hydrated. In the latter, water is characteristically distributed as films on soil particles that are, on average thinner, than are typical OMV (ca. ≤10 nm water film vs. 20 to >200 nm OMV;). Methodology/Principal Findings: We have identified a new bacterial surface structure, termed a "nanopod", that is a conduit for projecting OMV significant distances (e.g., ≥6 µm) from the cell. Electron cryotomography was used to determine nanopod three-dimensional structure, which revealed chains of vesicles within an undulating, tubular element. By using immunoelectron microscopy, proteomics, heterologous expression and mutagenesis, the tubes were determined to be an assembly of a surface layer protein (NpdA), and the interior structures identified as OMV. Specific metabolic function(s) for nanopods produced by Delftia sp. Cs1-4 are not yet known. However, a connection with phenanthrene degradation is a possibility since nanopod formation was induced by growth on phenanthrene. Orthologs of NpdA were identified in three other genera of the Comamonadaceae family, and all were experimentally verified to form nanopods. Conclusions/Significance: Nanopods are new bacterial organelles, and establish a new paradigm in the mechanisms by which bacteria effect long-distance interactions with their environment. Specifically, they create a pathway through which cells can effectively deploy OMV, and the biological activity these transmit, in a diffusion-independent manner. Nanopods would thus allow environmental bacteria to expand their metabolic sphere of influence in a manner previously unknown for these organisms

Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network

The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the past, we present the first statistical study from a developmental perspective, with findings that raise interesting suggestions on the establishment of long-distance connections and network hubs. Here, we analyze the neuro-development for temporal and spatial features, using birth times of neurons and their three-dimensional positions. Comparisons of growth in C. elegans with random spatial network growth highlight two findings relevant to neural network development. First, most neurons which are linked by long-distance connections are born around the same time and early on, suggesting the possibility of early contact or interaction between connected neurons during development. Second, early-born neurons are more highly connected (tendency to form hubs) than later born neurons. This indicates that the longer time frame available to them might underlie high connectivity. Both outcomes are not observed for random connection formation. The study finds that around one-third of electrically coupled long-range connections are late forming, raising the question of what mechanisms are involved in ensuring their accuracy, particularly in light of the extremely invariant connectivity observed in C. elegans. In conclusion, the sequence of neural network development highlights the possibility of early contact or interaction in securing long-distance and high-degree connectivity

Collapse of superconductivity in a hybrid tin-graphene Josephson junction array

When a Josephson junction array is built with hybrid superconductor/metal/superconductor junctions, a quantum phase transition from a superconducting to a two-dimensional (2D) metallic ground state is predicted to happen upon increasing the junction normal state resistance. Owing to its surface-exposed 2D electron gas and its gate-tunable charge carrier density, graphene coupled to superconductors is the ideal platform to study the above-mentioned transition between ground states. Here we show that decorating graphene with a sparse and regular array of superconducting nanodisks enables to continuously gate-tune the quantum superconductor-to-metal transition of the Josephson junction array into a zero-temperature metallic state. The suppression of proximity-induced superconductivity is a direct consequence of the emergence of quantum fluctuations of the superconducting phase of the disks. Under perpendicular magnetic field, the competition between quantum fluctuations and disorder is responsible for the resilience at the lowest temperatures of a superconducting glassy state that persists above the upper critical field. Our results provide the entire phase diagram of the disorder and magnetic field-tuned transition and unveil the fundamental impact of quantum phase fluctuations in 2D superconducting systems.Comment: 25 pages, 6 figure

High JC virus load in tongue carcinomas may be a risk factor for tongue tumorigenesis

The John Cunningham virus (JCV) asymptomatically infects a large proportion (~90%) of the population worldwide but may be activated in immunodeficient patients, resulting in progressive multifocal leukoencephalopathy. Recent reports demonstrated its oncogenic role in malignancies. In this paper, the presence of JCV-targeting T antigen was investigated in tongue carcinoma (TC, n = 39), dysplastic tongue epithelium (DTE, n = 15) and glossitis (n = 15) using real-time polymerase chain reaction (PCR) and in situ PCR and immunohistochemistry, and JCV copies were analyzed with the clinicopathological parameters of TCs. The results demonstrated that glossitis and DTEs had significantly lower copies of JCV (410.5 ± 44.3 and 658.3 ± 53.3 copies/μg DNA respectively) than TCs (981.5 ± 14.0, p  < 0.05). When they were divided into three groups with 0–200 copies/μg DNA (low), 201–1,000 (moderate) and more than 1001 (high), TCs showed 3 (7.6%) in the low group, 21 (53.8%) in the moderate group and 15 (38.4%) in the high group and glossitis showed 11 (73.3%) in the low group, 0 (0%) in the moderate group and 4 (26.6%) in the high group. The DTEs occupied an intermediate position between them (p < 0.001). In situ PCR demonstrated that the nuclei of TC and DTE cells are sporadically T-antigen positive but not in nasal turbinate epithelial cells. Immunohistochemistry for T-antigen protein revealed four positive cases only in TCs. The existence of JCV T-antigen DNA was not associated with the clinicopathological variables of TCs. In conclusion, the presence of JCV may be a risk factor of tongue carcinogenesis

Shot noise in mesoscopic systems

This is a review of shot noise, the time-dependent fluctuations in the electrical current due to the discreteness of the electron charge, in small conductors. The shot-noise power can be smaller than that of a Poisson process as a result of correlations in the electron transmission imposed by the Pauli principle. This suppression takes on simple universal values in a symmetric double-barrier junction (suppression factor 1/2), a disordered metal (factor 1/3), and a chaotic cavity (factor 1/4). Loss of phase coherence has no effect on this shot-noise suppression, while thermalization of the electrons due to electron-electron scattering increases the shot noise slightly. Sub-Poissonian shot noise has been observed experimentally. So far unobserved phenomena involve the interplay of shot noise with the Aharonov-Bohm effect, Andreev reflection, and the fractional quantum Hall effect.Comment: 37 pages, Latex, 10 figures (eps). To be published in "Mesoscopic Electron Transport," edited by L. P. Kouwenhoven, G. Schoen, and L. L. Sohn, NATO ASI Series E (Kluwer Academic Publishing, Dordrecht