A Mild Hydration of Nitriles Catalysed by Copper (ll) Acetate

A simple, mild and general procedure for the hydration of nitriles to amides using copper as catalyst and promoted by N,N-diethylhydroxylamine is described. The reaction can be conducted in water at low temperature in short reaction times. This new procedure allows amides to be obtained from a wide range of substrates in excellent yields

A Flair to Remember: Innovative Use of Technology during COVID-19 Focus on Weddings

Student blog series from MSc in Event Management students at TU Dublin. In this blog post Carla Rosas, Danielle Lynch, MJ Adekanmbi and Simioluwa Opayemi interview event planner Gabriella Olukoya from luxury events company A Flair to Remember. Gabriella gives vital insight on the current state of the wedding industry and also on how to ‘flip the script’ and use the ‘negatives’ and make them positives to elevate an events company. As a current ‘Regional Finalist’ for Wedding Planner of the Year, Gabby is a prime example of ‘Creating Success’ during COVID-19 by adding and implementing technology into their events company

A solar powered handheld plasma source for microbial decontamination applications

A fully portable atmospheric pressure air plasma system is reported to be suitable for the microbial decontamination of both surfaces and liquids. The device operates in quiescent air, and includes an integrated battery which is charged from a solar cell and weighs less than 750 g, making it highly amenable for a wide variety of applications beyond the laboratory. Using particle imaging velocimetry to visualise air flows around the device, the geometric configuration of the plasma generating electrodes was enhanced to induce a gas flow on the order of 0.5 m s-1 directed towards a sample placed downstream, thus improving the transport of plasma generated reactive species to the sample. The microbial decontamination efficiency of the system was assessed using potable water samples inoculated with common waterborne organisms Escherichia coli and Pseudomonas fluorescens. The reduction in the number of microorganisms was found to be in the range of 2-8 log and was strongly dependent on the plasma generation conditions

Collaborative Computation in Self-Organizing Particle Systems

Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this model has focused on shape formation and other spatial configuration problems (e.g., coating and compression). In this work we study foundational computational tasks that exceed the capabilities of the individual constant size memory of a particle, such as implementing a counter and matrix-vector multiplication. These tasks represent new ways to use these self-organizing systems, which, in conjunction with previous shape and configuration work, make the systems useful for a wider variety of tasks. They can also leverage the distributed and dynamic nature of the self-organizing system to be more efficient and adaptable than on traditional linear computing hardware. Finally, we demonstrate applications of similar types of computations with self-organizing systems to image processing, with implementations of image color transformation and edge detection algorithms

"Spontaneous scar dehiscence of a repaired bladder rupture in a 5 yr old girl – a case study"

Spontaneous scar dehiscence of a previous repaired urinary bladder rupture is described in a 5 yr old girl approximately 4 yrs after the original repair, she presented at the hospital with the chief complain of pain and distension of the abdomen. No underlying aetiology could be related to the event, her blood urea and creatinine levels were found to be raised. A diagnostic peritoneal tap showed non bloody straw colour urine in the peritoneal cavity. Emergent laparotomy was carried out and the site of scar dehiscence was closed in layers

Approximate Consensus in Highly Dynamic Networks: The Role of Averaging Algorithms

In this paper, we investigate the approximate consensus problem in highly dynamic networks in which topology may change continually and unpredictably. We prove that in both synchronous and partially synchronous systems, approximate consensus is solvable if and only if the communication graph in each round has a rooted spanning tree, i.e., there is a coordinator at each time. The striking point in this result is that the coordinator is not required to be unique and can change arbitrarily from round to round. Interestingly, the class of averaging algorithms, which are memoryless and require no process identifiers, entirely captures the solvability issue of approximate consensus in that the problem is solvable if and only if it can be solved using any averaging algorithm. Concerning the time complexity of averaging algorithms, we show that approximate consensus can be achieved with precision of $\varepsilon$ in a coordinated network model in $O(n^{n+1} \log\frac{1}{\varepsilon})$ synchronous rounds, and in $O(\Delta n^{n\Delta+1} \log\frac{1}{\varepsilon})$ rounds when the maximum round delay for a message to be delivered is $\Delta$. While in general, an upper bound on the time complexity of averaging algorithms has to be exponential, we investigate various network models in which this exponential bound in the number of nodes reduces to a polynomial bound. We apply our results to networked systems with a fixed topology and classical benign fault models, and deduce both known and new results for approximate consensus in these systems. In particular, we show that for solving approximate consensus, a complete network can tolerate up to 2n-3 arbitrarily located link faults at every round, in contrast with the impossibility result established by Santoro and Widmayer (STACS '89) showing that exact consensus is not solvable with n-1 link faults per round originating from the same node

Green criminology: shining a critical lens on environmental harm

Green criminology provides for inter-disciplinary and multi-disciplinary engagement with environmental crimes and wider environmental harms. Green criminology applies a broad ‘‘green’’ perspective to environmental harms, ecological justice, and the study of environmental laws and criminality, which includes crimes affecting the environment and non-human nature. Within the ecological justice and species justice perspectives of green criminology there is a contention that justice systems need to do more than just consider anthropocentric notions of criminal justice, they should also consider how justice systems can provide protection and redress for the environment and other species. Green criminological scholarship has, thus, paid direct attention to theoretical questions of whether and how justice systems deal with crimes against animals and the environment; it has begun to conceptualize policy perspectives that can provide contemporary ecological justice alongside mainstream criminal justice. Moving beyond mainstream criminology’s focus on individual offenders, green criminology also explores state failure in environmental protection and corporate offending and environmentally harmful business practices. A central discussion within green criminology is that of whether environmental harm rather than environmental crime should be its focus, and whether green ‘‘crimes’’ should be seen as the focus of mainstream criminal justice and dealt with by core criminal justice agencies such as the police, or whether they should be considered as being beyond the mainstream. This article provides an introductory overview that complements a multi- and inter-disciplinary article collection dedicated to green criminological thinking and research

FHL1 reduces dystrophy in transgenic mice overexpressing FSHD muscular dystrophy region gene 1 (FRG1)

Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal-dominant disease with no effective treatment. The genetic cause of FSHD is complex and the primary pathogenic insult underlying the muscle disease is unknown. Several disease candidate genes have been proposed including DUX4 and FRG1. Expression analysis studies of FSHD report the deregulation of genes which mediate myoblast differentiation and fusion. Transgenic mice overexpressing FRG1 recapitulate the FSHD muscular dystrophy phenotype. Our current study selectively examines how increased expression of FRG1 may contribute to myoblast differentiation defects. We generated stable C2C12 cell lines overexpressing FRG1, which exhibited a myoblast fusion defect upon differentiation. To determine if myoblast fusion defects contribute to the FRG1 mouse dystrophic phenotype, this strain was crossed with skeletal muscle specific FHL1-transgenic mice. We previously reported that FHL1 promotes myoblast fusion in vitro and FHL1-transgenic mice develop skeletal muscle hypertrophy. In the current study, FRG1 mice overexpressing FHL1 showed an improvement in the dystrophic phenotype, including a reduced spinal kyphosis, increased muscle mass and myofiber size, and decreased muscle fibrosis. FHL1 expression in FRG1 mice, did not alter satellite cell number or activation, but enhanced myoblast fusion. Primary myoblasts isolated from FRG1 mice showed a myoblast fusion defect that was rescued by FHL1 expression. Therefore, increased FRG1 expression may contribute to a muscular dystrophy phenotype resembling FSHD by impairing myoblast fusion, a defect that can be rescued by enhanced myoblast fusion via expression of FHL1

Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data

<p>Abstract</p> <p>Background</p> <p>A key stage for all microarray analyses is the extraction of feature-intensities from an image. If this step goes wrong, then subsequent preprocessing and processing stages will stand little chance of rectifying the matter. Illumina employ random construction of their BeadArrays, making feature-intensity extraction even more important for the Illumina platform than for other technologies. In this paper we show that using raw Illumina data it is possible to identify, control, and perhaps correct for a range of spatial-related phenomena that affect feature-intensity extraction.</p> <p>Results</p> <p>We note that feature intensities can be unnaturally high when in the proximity of a number of phenomena relating either to the images themselves or to the layout of the beads on an array. Additionally we note that beads neighbour beads of the same type more often than one might expect, which may cause concern in some models of hybridization. We highlight issues in the identification of a bead's location, and in particular how this both affects and is affected by its intensity. Finally we show that beads can be wrongly identified in the image on either a local or array-wide scale, with obvious implications for data quality.</p> <p>Conclusions</p> <p>The image processing issues identified will often pass unnoticed by an analysis of the standard data returned from an experiment. We detail some simple diagnostics that can be implemented to identify problems of this nature, and outline approaches to correcting for such problems. These approaches require access to the raw data from the arrays, not just the summarized data usually returned, making the acquisition of such raw data highly desirable.</p

Erratum to: Surface layer proteins from virulent Clostridium difficile ribotypes exhibit signatures of positive selection with consequences for innate immune response

“Upon publication of the original article [1], it was noticed that there was an error in the author name. The author’s name should be "Micheál Mac Aogáin" instead of Micheál MacAogain.