Self-balancing beam permits safe, easy load handling under overhang

The use of a self-balancing I-beam with a counterweight and motor simplifies moving heavy loads that are inaccessible for cranes. The beam cannot be overloaded, as the counterweight will not balance the load, and thus acts as an automatic safety device

Trends in Computer-Aided Diagnosis Using Deep 2 Learning Techniques: A Review of Recent Studies on 3 Algorithm Development 4

With recent focus on deep neural network architectures for development of algorithms for computer-aided diagnosis (CAD), we provide a review of studies within the last 3 years (2015-2017) reported in selected top journals and conferences. 29 studies that met our inclusion criteria were reviewed to identify trends in this field and to inform future development. Studies have focused mostly on cancer-related diseases within internal medicine while diseases within gender-/age-focused fields like gynaecology/pediatrics have not received much focus. All reviewed studies employed image datasets, mostly sourced from publicly available databases (55.2%) and few based on data from human subjects (31%) and non-medical datasets (13.8%), while CNN architecture was employed in most (70%) of the studies. Confirmation of the effect of data manipulation on quality of output and adoption of multi-class rather than binary classification also require more focus. Future studies should leverage collaborations with medical experts to aid future with actual clinical testing with reporting based on some generally applicable index to enable comparison. Our next steps on plans for CAD development for osteoarthritis (OA), with plans to consider multi-class classification and comparison across deep learning approaches and unsupervised architectures were also highlighted

Entirely off-grid and solar-powered DNA sequencing of microbial communities during an ice cap traverse expedition

Microbial communities in remote locations remain under-studied. This is particularly true on glaciers and icecaps, which cover approximately 11% of the Earth’s surface. The principal reason for this is the inaccessibility of most of these areas due to their extreme isolation and challenging environmental conditions. While remote research stations have significantly lowered the barrier to studying the microbial communities on icecaps, their use has led to a bias for data collection in the near vicinity of these institutions. Here, miniaturisation of a DNA sequencing lab suitable for off-grid metagenomic studies is demonstrated. Using human power alone, this lab was transported across Europe’s largest ice cap (Vatnajökull, Iceland) by ski and sledge. After 11 days of unsupported polar-style travel, a metagenomic study of a geothermal hot spring gorge was conducted on the remote northern edge of the ice cap. This tent-based metagenomic study resulted in over 24 h of Nanopore sequencing, powered by solar power alone. This study demonstrates the ability to conduct DNA sequencing in remote locations, far from civilised resources (mechanised transport, external power supply, internet connection, etc.), whilst greatly reducing the time from sample collection to data acquisition

Collective excitations of Bose-Einstein condensed gases at finite temperatures

We have applied the Popov version of the Hartree-Fock-Bogoliubov (HFB) approximation to calculate the finite-temperature excitation spectrum of a Bose-Einstein condensate (BEC) of $^{87}$Rb atoms. For lower values of the temperature, we find excellent agreement with recently-published experimental data for the JILA TOP trap. In contrast to recent comparison of the results of HFB--Popov theory with experimental condensate fractions and specific heats, there is disagreement of the theoretical and recent experimental results near the BEC phase transition temperature.Comment: 4 pages, Latex, with 4 figures. More info at http://amo.phy.gasou.edu/bec.htm

Elasticity of Stiff Biopolymers

We present a statistical mechanical study of stiff polymers, motivated by experiments on actin filaments and the considerable current interest in polymer networks. We obtain simple, approximate analytical forms for the force-extension relations and compare these with numerical treatments. We note the important role of boundary conditions in determining force-extension relations. The theoretical predictions presented here can be tested against single molecule experiments on neurofilaments and cytoskeletal filaments like actin and microtubules. Our work is motivated by the buckling of the cytoskeleton of a cell under compression, a phenomenon of interest to biology.Comment: Submitted for publication, five pages, three figure

Collective Modes in a Dilute Bose-Fermi Mixture

We here study the collective excitations of a dilute spin-polarized Bose-Fermi mixture at zero temperature, considering in particular the features arising from the interaction between the two species. We show that a propagating zero-sound mode is possible for the fermions even when they do not interact among themselves.Comment: latex, 6 eps figure

Double Field Theory Formulation of Heterotic Strings

We extend the recently constructed double field theory formulation of the low-energy theory of the closed bosonic string to the heterotic string. The action can be written in terms of a generalized metric that is a covariant tensor under O(D,D+n), where n denotes the number of gauge vectors, and n additional coordinates are introduced together with a covariant constraint that locally removes these new coordinates. For the abelian subsector, the action takes the same structural form as for the bosonic string, but based on the enlarged generalized metric, thereby featuring a global O(D,D+n) symmetry. After turning on non-abelian gauge couplings, this global symmetry is broken, but the action can still be written in a fully O(D,D+n) covariant fashion, in analogy to similar constructions in gauged supergravities.Comment: 28 pages, v2: minor changes, version published in JHE

Safe food and feed through an integrated toolbox for mycotoxin management: the MyToolBox approach

There is a pressing need to mobilise the wealth of knowledge from the international mycotoxin research conductedover the past 25-30 years, and to perform cutting-edge research where knowledge gaps still exist. This knowledgeneeds to be integrated into affordable and practical tools for farmers and food processors along the chain inorder to reduce the risk of mycotoxin contamination of crops, feed and food. This is the mission of MyToolBox – a four-year project which has received funding from the European Commission. It mobilises a multi-actorpartnership (academia, farmers, technology small and medium sized enterprises, food industry and policystakeholders) to develop novel interventions aimed at achieving a significant reduction in crop losses due tomycotoxin contamination. Besides a field-to-fork approach, MyToolBox also considers safe use options ofcontaminated batches, such as the efficient production of biofuels. Compared to previous efforts of mycotoxin reduction strategies, the distinguishing feature of MyToolBox is to provide the recommended measures to theend users along the food and feed chain in a web-based MyToolBox platform (e-toolbox). The project focuseson small grain cereals, maize, peanuts and dried figs, applicable to agricultural conditions in the EU and China. Crop losses using existing practices are being compared with crop losses after novel pre-harvest interventionsincluding investigation of genetic resistance to fungal infection, cultural control (e.g. minimum tillage or cropdebris treatment), the use of novel biopesticides suitable for organic farming, competitive biocontrol treatment and development of novel modelling approaches to predict mycotoxin contamination. Research into post-harvestmeasures includes real-time monitoring during storage, innovative sorting of crops using vision-technology, novelmilling technology and studying the effects of baking on mycotoxins at an industrial scale