Nasa desalting kit development, phase ii first progress report

NASA desalting kit development - container and processor desig

Dirac synchronization is rhythmic and explosive

G.B. acknowledges funding from the Alan Turing Institute and from Royal Society IEC \NSFC\191147. J.J.T. acknowledges financial support from the Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía and European Regional Development Funds, Ref. P20_00173. This work is also part of the Project of I+D+i Ref. PID2020-113681GB-I00, financed by MICIN/AEI/10.13039/ 501100011033 and FEDER “A way to make Europe". This research utilized Queen Mary’s Apocrita HPC facility, supported by QMUL Research-IT. https://doi.org/10.5281/zenodo. 438045.Topological signals defined on nodes, links and higher dimensional simplices define the dynamical state of a network or of a simplicial complex. As such, topological signals are attracting increasing attention in network theory, dynamical systems, signal processing and machine learning. Topological signals defined on the nodes are typically studied in network dynamics, while topological signals defined on links are much less explored. Here we investigate Dirac synchronization, describing locally coupled topological signals defined on the nodes and on the links of a network, and treated using the topological Dirac operator. The dynamics of signals defined on the nodes is affected by a phase lag depending on the dynamical state of nearby links and vice versa. We show that Dirac synchronization on a fully connected network is explosive with a hysteresis loop characterized by a discontinuous forward transition and a continuous backward transition. The analytical investigation of the phase diagram provides a theoretical understanding of this topological explosive synchronization. The model also displays an exotic coherent synchronized phase, also called rhythmic phase, characterized by non-stationary order parameters which can shed light on topological mechanisms for the emergence of brain rhythms.Alan Turing Institute and from Royal Society IEC \NSFC\191147. J.J.TConsejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía and European Regional Development Funds, Ref. P20_00173Project of I+D+i Ref. PID2020-113681GB-I00, financed by MICIN/AEI/10.13039/ 501100011033 and FEDER “A way to make Europe"QMUL Research-I

Dirac synchronization is rhythmic and explosive

G.B. acknowledges funding from the Alan Turing Institute and from Royal Society IEC \NSFC\191147. J.J.T. acknowledges financial support from the Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía and European Regional Development Funds, Ref. P20_00173. This work is also part of the Project of I+D+i Ref. PID2020-113681GB-I00, financed by MICIN/AEI/10.13039/ 501100011033 and FEDER “A way to make Europe". This research utilized Queen Mary’s Apocrita HPC facility, supported by QMUL Research-IT. https://doi.org/10.5281/zenodo. 438045.Topological signals defined on nodes, links and higher dimensional simplices define the dynamical state of a network or of a simplicial complex. As such, topological signals are attracting increasing attention in network theory, dynamical systems, signal processing and machine learning. Topological signals defined on the nodes are typically studied in network dynamics, while topological signals defined on links are much less explored. Here we investigate Dirac synchronization, describing locally coupled topological signals defined on the nodes and on the links of a network, and treated using the topological Dirac operator. The dynamics of signals defined on the nodes is affected by a phase lag depending on the dynamical state of nearby links and vice versa. We show that Dirac synchronization on a fully connected network is explosive with a hysteresis loop characterized by a discontinuous forward transition and a continuous backward transition. The analytical investigation of the phase diagram provides a theoretical understanding of this topological explosive synchronization. The model also displays an exotic coherent synchronized phase, also called rhythmic phase, characterized by non-stationary order parameters which can shed light on topological mechanisms for the emergence of brain rhythms.Alan Turing Institute and from Royal Society IEC \NSFC\191147. J.J.TConsejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía and European Regional Development Funds, Ref. P20_00173Project of I+D+i Ref. PID2020-113681GB-I00, financed by MICIN/AEI/10.13039/ 501100011033 and FEDER “A way to make Europe"QMUL Research-I

Traceability Technology Adoption in Supply Chain Networks

Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, or verifying sustainable supplier practices. Initiatives leading the implementation of traceability technologies must choose the least-costly set of firms —or seed set — to target for early adoption. Choosing this seed set is challenging because firms are part of supply chains interlinked in complex networks, yielding an inherent supply chain effect: benefits obtained from traceability are conditional on technology adoption by a subset of firms in a product’s supply chain. We prove that the problem of selecting the least-costly seed set in a supply chain network is hard to solve and even approximate within a polylogarithmic factor. Nevertheless, we provide a novel linear programming-based algorithm to identify the least-costly seed set. The algorithm is fixed-parameter tractable in the supply chain network’s treewidth, which we show to be low in real-world supply chain networks. The algorithm also enables us to derive easily-computable bounds on the cost of selecting an optimal seed set. Finally, we leverage our algorithms to conduct large-scale numerical experiments that provide insights into how the supply chain network structure influences diffusion. These insights can help managers optimize their technology diffusion strategy

Fuzzy algorithms: Application to adipose tissue quantification on MR images

Abstract Metabolic syndrome, which is related to abdominal obesity, is a fast growing disease in our western countries. Its presence greatly increases the risk of developing cardiovascular diseases. The accumulation of visceral adipose tissue plays a key role in the development of the metabolic syndrome. The increase of waist circumference is one of the five criteria of the metabolic syndrome diagnosis. But this increase can be due to visceral or subcutaneous adipose tissues. And these adipose tissues do not play the same rule in metabolic syndrome. The purpose of this study was to develop software for automatic and reliable quantification of visceral and subcutaneous adipose tissues, to detect patient with high risk to develop metabolic syndrome and to follow the evolution of adipose tissue repartition after treatment. A gradient echo magnetic resonance (MR) technique is used, with a TE such that fat and water are opposed in phase. The developed process is based on two fuzzy algorithms. First, we fuzzy generalized clustering algorithms allow to merge pixels according to their intensities. Then, fuzzy connectedness algorithm allows to merge pixels according to cost function related to distance, gradient distance and intensities. A validation is performed with a comparison between expert results made by manual drawing and purpose-made software results. Our software provides an automatic and reliable method to segment visceral and subcutaneous adipose tissue and additionally avoids in some case the problem of inhomogeneity of signal intensity

Eine Phantasie der Allmacht. Vom Versprechen des an die Technologie angepassten Lernens

Die Autoren analysieren nach der Methode der Objektiven Hermeneutik den das brasilianische Werbevideo der Lernplattform "Moodle". Es wird sowohl der Slogan als auch die Bildpräsentation und damit die Funktionsweise der Lernplattform sequenzanalytisch rekonstruiert. Dabei zeigt sich, wie die Lernplattform nicht nur die Funktion der Lehrenden entprofessionalisiert, sondern auch das Vermittelte zur Nebensache gerät. Die Art und Weise, wie die Plattform den Schüler und die Schülerin an sie bindet, wird als reine Anpassung gekennzeichnet. (DIPF/Orig.

Reconciling Utility with Privacy in Genomics

Direct-to-consumer genetic testing makes it possible for everyone to learn their genome sequences. In order to contribute to medical research, a growing number of people publish their genomic data on the Web, sometimes under their real identities. However, this is at odds not only with their own privacy but also with the privacy of their relatives. The genomes of relatives being highly correlated, some family members might be opposed to revealing any of the family's genomic data. In this paper, we study the trade-off between utility and privacy in genomics. We focus on the most relevant kind of variants, namely single nucleotide polymorphisms (SNPs). We take into account the fact that the SNPs of an individual contain information about the SNPs of his family members and that SNPs are correlated with each other. Furthermore, we assume that SNPs can have different utilities in medical research and different levels of sensitivity for individuals. We propose an obfuscation mechanism that enables the genomic data to be publicly available for research, while protecting the genomic privacy of the individuals in a family. Our genomic-privacy preserving mechanism relies upon combinatorial optimization and graphical models to optimize utility and meet privacy requirements. We also present an extension of the optimization algorithm to cope with the non-linear constraints induced by the correlations between SNPs. Our results on real data show that our proposed technique maximizes the utility for genomic research and satisfies family members' privacy constraints

Clinical, radiologic, pathologic, and molecular characteristics of long-term survivors of diffuse intrinsic pontine glioma (DIPG): a collaborative report from the International and European Society for Pediatric Oncology DIPG registries

Purpose Diffuse intrinsic pontine glioma (DIPG) is a brainstem malignancy with a median survival of < 1 year. The International and European Society for Pediatric Oncology DIPG Registries collaborated to compare clinical, radiologic, and histomolecular characteristics between short-term survivors (STSs) and long-term survivors (LTSs). Materials and Methods Data abstracted from registry databases included patients from North America, Australia, Germany, Austria, Switzerland, the Netherlands, Italy, France, the United Kingdom, and Croatia. Results Among 1,130 pediatric and young adults with radiographically confirmed DIPG, 122 (11%) were excluded. Of the 1,008 remaining patients, 101 (10%) were LTSs (survival ≥ 2 years). Median survival time was 11 months (interquartile range, 7.5 to 16 months), and 1-, 2-, 3-, 4-, and 5-year survival rates were 42.3% (95% CI, 38.1% to 44.1%), 9.6% (95% CI, 7.8% to 11.3%), 4.3% (95% CI, 3.2% to 5.8%), 3.2% (95% CI, 2.4% to 4.6%), and 2.2% (95% CI, 1.4% to 3.4%), respectively. LTSs, compared with STSs, more commonly presented at age < 3 or > 10 years (11% v 3% and 33% v 23%, respectively; P < .001) and with longer symptom duration ( P < .001). STSs, compared with LTSs, more commonly presented with cranial nerve palsy (83% v 73%, respectively; P = .008), ring enhancement (38% v 23%, respectively; P = .007), necrosis (42% v 26%, respectively; P = .009), and extrapontine extension (92% v 86%, respectively; P = .04). LTSs more commonly received systemic therapy at diagnosis (88% v 75% for STSs; P = .005). Biopsies and autopsies were performed in 299 patients (30%) and 77 patients (10%), respectively; 181 tumors (48%) were molecularly characterized. LTSs were more likely to harbor a HIST1H3B mutation (odds ratio, 1.28; 95% CI, 1.1 to 1.5; P = .002). Conclusion We report clinical, radiologic, and molecular factors that correlate with survival in children and young adults with DIPG, which are important for risk stratification in future clinical trials

Temporal blastemal cell gene expression analysis in the kidney reveals new Wnt and related signaling pathway genes to be essential for Wilms' tumor onset

Wilms' tumors (WTs) originate from metanephric blastema cells that are unable to complete differentiation, resulting in triphasic tumors composed of epithelial, stromal and blastemal cells, with the latter harboring molecular characteristics similar to those of the earliest kidney development stages. Precise regulation of Wnt and related signaling pathways has been shown to be crucial for correct kidney differentiation. In this study, the gene expression profile of Wnt and related pathways was assessed in laser-microdissected blastemal cells in WTs and differentiated kidneys, in human and in four temporal kidney differentiation stages (i.e. E15.5, E17.5, P1.5 and P7.5) in mice, using an orthologous cDNA microarray platform. A signaling pathway-based gene signature was shared between cells of WT and of earliest kidney differentiation stages, revealing genes involved in the interruption of blastemal cell differentiation in WT. Reverse transcription-quantitative PCR showed high robustness of the microarray data demonstrating 75 and 56% agreement in the initial and independent sample sets, respectively. The protein expression of CRABP2, IGF2, GRK7, TESK1, HDGF, WNT5B, FZD2 and TIMP3 was characterized in WTs and in a panel of human fetal kidneys displaying remarkable aspects of differentiation, which was recapitulated in the tumor. Taken together, this study reveals new genes candidate for triggering WT onset and for therapeutic treatment targets