A Greedy Heuristic for a Three-Level Multi-Period Single-Sourcing Problem

In this paper we consider a model for integrating transportation and inventory decisions in a three-level logistics network consisting of plants, warehouses, and retailers (or customers). Our model includes production and throughout capacity constraints, and minimizes production, holding, and tansportation costs in a dynamic environment. We show that the problem can be reformulated as a certain type of assignment problem with convex objective function. Based on this observation, we propose a greedy heuristic for the problem, and illustrate its behaviour on a class of randomly generated problem instances. These experiments suggest that the heuristic may be asymptotically feasible and optimal with probability one in the number of customers

Incorporation of lysozyme into a mucoadhesive electrospun patch for rapid protein delivery to the oral mucosa

The delivery of biopharmaceuticals to the oral mucosa offers a range of potential applications including antimicrobial peptides to treat resistant infections, growth factors for tissue regeneration, or as an alternative to injections for systemic delivery. Existing formulations targeting this site are typically non-specific and provide little control over dose. To address this, an electrospun dual-layer mucoadhesive patch was investigated for protein delivery to the oral mucosa. Lysozyme was used as a model antimicrobial protein and incorporated into poly(vinylpyrrolidone)/Eudragit RS100 polymer nanofibers using electrospinning from an ethanol/water mixture. The resulting fibrous membranes released the protein at a clinically desirable rate, reaching 90 ± 13% cumulative release after 2 h. Dual fluorescent fibre labelling and confocal microscopy demonstrated the homogeneity of lysozyme and polymer distribution. High encapsulation efficiency and preservation of enzyme activity were achieved (93.4 ± 7.0% and 96.1 ± 3.3% respectively). The released lysozyme inhibited the growth of the oral bacterium Streptococcus ratti, providing further evidence of retention of biological activity and illustrating a potential application for treating and preventing oral infections. An additional protective poly(caprolactone) backing layer was introduced to promote unidirectional delivery, without loss of enzyme activity, and the resulting dual-layer patches displayed long residence times using an in vitro test, showing that the adhesive properties were maintained. This study demonstrates that the drug delivery system has great potential for the delivery of therapeutic proteins to the oral mucosa

Snorer diarisation based on deep neural network embeddings

Acoustic analysis of sleep breathing sounds using a smartphone at home provides a much less obtrusive means of screening for sleep-disordered breathing (SDB) than assessment in a sleep clinic. However, application in a home environment is confounded by the problem that a bed partner may also be present and snore. This paper proposes a novel acoustic analysis system for snorer diarisation, a concept extrapolated from speaker diarisation research, which allows screening for SDB of both the user and the bed partner using a single smartphone. The snorer diarisation system involves three steps. First, a deep neural network (DNN) is employed to estimate the number of concurrent snorers in short segments of monaural audio recordings. Second, the identified snore segments are clustered using snorer embeddings, a feature representation that allows different snorers to be discriminated. Finally, a snore transcription is automatically generated for each snorer by combining consecutive snore segments. The system is evaluated on both synthetic snore mixtures and real two-snorer recordings. The results show that it is possible to accurately screen a subject and their bed partner for SDB in the same session from recordings of a single smartphone

Polynomial Time Algorithms For Some Multi-Level Lot-Sizing Problems With Production Capacities

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated, in the presence of production capacities and for different transportation cost functions. The model we study is a generalization of the traditional single-item economic lot-sizing model, adding stationary production capacities at the manufacturer, as well as multiple intermediate storage levels (including the retailer level), and transportation between these levels. Allowing for general concave production costs and linear holding costs, we provide polynomialtime algorithms for the cases where the transportation costs are either linear, or are concave with a fixed-charge structure. In the latter case, we make the additional common and reasonable assumption that the variable transportation and inventory costs are such that holding inventories at higher levels in the supply chain is more attractive from a variable cost perspective. The running times of the algorithms are remarkably insensitive to the number of levels in the supply chain

Obstructive sleep apnea screening with breathing sounds and respiratory effort: a multimodal deep learning approach

Obstructive sleep apnea (OSA) is a chronic and prevalent condition with well-established comorbidities. Due to limited diagnostic resources and high cost, a significant OSA population lives undiagnosed, and accurate and low-cost methods to screen for OSA are needed. We propose a novel screening method based on breathing sounds recorded with a smartphone and respiratory effort. Whole night recordings are divided into 30-s segments, each of which is classified for the presence or absence of OSA events by a multimodal deep neural network. Data fusion techniques were investigated and evaluated based on the apnea-hypopnea index estimated from whole night recordings. Real-world recordings made during home sleep apnea testing from 103 participants were used to develop and evaluate the proposed system. The late fusion system achieved the best sensitivity and specificity when screening for severe OSA, at 0.93 and 0.92, respectively. This offers the prospect of inexpensive OSA screening at home

Chemical and structural characterization of SeIV biotransformations by Stenotrophomonas bentonitica into Se0 nanostructures and volatiles Se species

Microorganisms such as Stenotrophomonas bentonitica could influence the safety of the deep geological repository system by producing nanoparticles and volatile compounds of selenium

Methyl Selenol as Precursor in Selenite Reduction to Se/S Species by Methane-oxidizing Bacteria.

A wide range of microorganisms have been shown to transform selenium-containing oxyanions to reduced forms of the element, particularly selenium-containing nanoparticles. Such reactions are promising for detoxification of environmental contamination and production of valuable selenium-containing products such as nanoparticles for application in biotechnology. It has previously been shown that aerobic methane-oxidising bacteria, including Methylococcus capsulatus (Bath), are able to perform methane-driven conversion of selenite (SeO32-) to selenium-containing nanoparticles and methylated selenium species. Here, the biotransformation of selenite by Mc. capsulatus (Bath) has been studied in detail via a range of imaging, chromatographic and spectroscopic techniques. The results indicate that the nanoparticles are produced extracellularly and have a composition distinct from nanoparticles previously observed from other organisms. The spectroscopic data from the methanotroph-derived nanoparticles are best accounted for by a bulk structure composed primarily of octameric rings in the form Se8-xSx with an outer coat of cell-derived biomacromolecules. Among a range of volatile methylated selenium and selenium-sulfur species detected, methyl selenol (CH3SeH) was found only when selenite was the starting material, although selenium nanoparticles (both biogenic and chemically produced) could be transformed into other methylated selenium species. This result is consistent with methyl selenol being an intermediate in methanotroph-mediated biotransformation of selenium to all the methylated and particulate products observed.ImportanceAerobic methane-oxidizing bacteria are ubiquitous in the environment. Two well characterised strains, Mc. capsulatus (Bath) and Methylosinus trichosporium OB3b, representing gamma- and alpha-proteobacterial methanotrophs, can convert selenite, an environmental pollutant, to volatile selenium compounds and selenium containing particulates. Both conversions can be harnessed for bioremediation of selenium pollution using biological or fossil methane as the feedstock and these organisms could be used to produce selenium-containing particles for food, and biotechnological applications. Using an extensive suite of techniques we identified precursors of selenium nanoparticle formation, and also that these nanoparticles are made up of eight membered mixed selenium and sulfur rings

The Phonon Drag Effect in Single-Walled Carbon Nanotubes

A variational solution of the coupled electron-phonon Boltzmann equations is used to calculate the phonon drag contribution to the thermopower in a 1-D system. A simple formula is derived for the temperature dependence of the phonon drag in metallic, single-walled carbon nanotubes. Scattering between different electronic bands yields nonzero values for the phonon drag as the Fermi level varies.Comment: 8 pages, 4 figure

Bioactive protein and peptide release from a mucoadhesive electrospun membrane

Protein-based biologics constitute a rapidly expanding category of therapeutic agents with high target specificity. Their clinical use has dramatically increased in recent years, but administration is largely via injection. Drug delivery across the oral mucosa is a promising alternative to injections, in order to avoid the gastrointestinal tract and first-pass metabolism. Current drug delivery formulations include liquid sprays, mucoadhesive tablets and films, which lack dose control in the presence of salivary flow. To address this, electrospun membranes that adhere tightly to the oral mucosa and release drugs locally have been developed. Here, we investigated the suitability of these mucoadhesive membranes for peptide or protein release. Bradykinin (0.1%) or insulin (1, 3, and 5%) were incorporated by electrospinning from ethanol/water mixtures. Immersion of membranes in buffer resulted in the rapid release of bradykinin, with a maximal release of 70 ± 12% reached after 1 h. In contrast, insulin was liberated more slowly, with 88 ± 11, 69.0 ± 5.4, and 63.9 ± 9.0% cumulative release of the total encapsulated dose after 8 h for membranes containing 1, 3, and 5% w/w insulin, respectively. Membrane–eluted bradykinin retained pharmacological activity by inducing rapid intracellular calcium release upon binding to its cell surface receptor on oral fibroblasts, when examined by flow cytometry. To quantify further, time-lapse confocal microscopy revealed that membrane–eluted bradykinin caused a 1.58 ± 0.16 fold-change in intracellular calcium fluorescence after 10 s compared to bradykinin solution (2.13 ± 0.21), relative to placebo. In conclusion, these data show that electrospun membranes may be highly effective vehicles for site-specific administration of biotherapeutic proteins or peptides directly to the oral mucosa for either local or systemic drug delivery applications