From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans

It is a popular belief that exercise performance is limited by metabolic changes in the exercising muscles, so called peripheral fatigue. Exercise terminates when there is a catastrophic failure of homoeostasis in the exercising muscles. A revolutionary theory is presented that proposes that exercise performance is regulated by the central nervous system specifically to ensure that catastrophic physiological failure does not occur during normal exercise in humans

Spectral Preserver Problems in Uniform Algebras

There has been much interest in characterizing maps between Banach algebras that preserve a certain equation or family of elements. There is a rich history in such problems that assume the map to be linear, so called linear preserver problems. More recently, there has been an interest in not assuming the map is linear a priori and instead to assume it preserves some equation involving the spectrum, a portion of the spectrum, or the norm. After a brief introduction to uniform algebras, we give a rigorous development of the theory of boundaries. This includes a new alternative proof of the famous Shilov Theorem. Also a generalization of Bishop\u27s Lemma is given and proved. Two spectral preserver problems are introduced and solved for the class of uniform algebras. One of these problems is given in terms of a portion of the spectrum called the peripheral spectrum. The other is given by a norm condition. The first spectral preserver problem concerns weakly-peripherally multiplicative maps between uniform algebras. These are maps T from A to B such that the intersection of the peripheral spectra of TfTg and fg is not empty for all f and g in A. It is proven that if T is a weakly-peripherally multiplicative map (not necessarily linear) that preserves the family of peak functions then it is an isometric algebra isomorphism. The second of these preserver problems shows that if T is a map (not necessarily linear) between uniform algebras, A and B, such that the norm of TfTg + 1 equals the norm of fg + 1 for all f, g in A, then T is a weighted composition operator composed with a conjugation operator. In particular, if T1 = 1 and Ti = i then T is an isometric algebra isomorphism

Vendor Managed Inventory: Mitigating the Negative Impact on Cash Flow Caused by Inefficient Inventory Management

Insufficient inventory management systems can negatively affect the profitability of a business organization. Supply chain managers who do not have efficient inventory management systems risk insufficient cash flow and loss of profitability. Grounded in Goldratt’s theory of constraints, the purpose of this qualitative pragmatic inquiry was to explore strategies supply chain managers use to mitigate the negative impact on cash flow caused by inefficient inventory management systems. The participants were five manufacturing supply chain management professionals who have managed, implemented, or maintained traditional inventory management (TIM) programs or vendor-managed inventory (VMI) programs. Data were collected using semistructured interviews and publicly available company documents about TIM and VMI programs. Using thematic analysis, four themes were identified: (a) TIM programs are familiar and allow for visible internal control of inventory management; (b) TIM programs are inflexible, require oversight, and are costly; (c) VMI programs are adaptable, reliable, and cost-effective; and (d) VMI programs can lack full transparency and be challenged by demand spikes. A key recommendation is for supply chain managers to provide full transparency related to demand forecasting, leading to the accurate and deliberate exchange of viable information needed for an efficient and profitable inventory program. The implications for positive social change include the potential to maintain the continuity of supply chains and support employment in local communities by providing stable employment in manufacturing companies contributing to supply chains

Subnormal weighted translation semigroups

AbstractA weighted translation semigroup {St} on L2(R+) is defined by (Stf)(x) = (φ(x)φ(x − t))f(x − t) for x ⩾ t and 0 otherwise, where φ is a continuous nonzero scalar-valued function on R+. It is shown that {St} is subnormal if and only if φ2 is the product of an exponential function and the Laplace-Stieltjes transform of an increasing function of total variation one. A necessary and sufficient condition for similarity of weighted translation semigroups is developed

Large-scale structure of brown rat (Rattus norvegicus) populations in England: effects on rodenticide resistance

The brown rat (Rattus norvegicus) is a relatively recent (<300 years) addition to the British fauna, but by association with negative impacts on public health, animal health and agriculture, it is regarded as one of the most important vertebrate pest species. Anticoagulant rodenticides were introduced for brown rat control in the 1950s and are widely used for rat control in the UK, but long-standing resistance has been linked to control failures in some regions. One thus far ignored aspect of resistance biology is the population structure of the brown rat. This paper investigates the role population structure has on the development of anticoagulant resistance. Using mitochondrial and microsatellite DNA, we examined 186 individuals (from 15 counties in England and one location in Wales near the Wales–England border) to investigate the population structure of rural brown rat populations. We also examined individual rats for variations of the VKORC1 gene previously associated with resistance to anticoagulant rodenticides. We show that the populations were structured to some degree, but that this was only apparent in the microsatellite data and not the mtDNA data. We discuss various reasons why this is the case. We show that the population as a whole appears not to be at equilibrium. The relative lack of diversity in the mtDNA sequences examined can be explained by founder effects and a subsequent spatial expansion of a species introduced to the UK relatively recently. We found there was a geographical distribution of resistance mutations, and relatively low rate of gene flow between populations, which has implications for the development and management of anticoagulant resistance

Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust

Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images. Their full acceptance by clinicians remains however hampered by the lack of intelligible uncertainty assessment of the provided results. Most approaches to quantify their uncertainty, such as the popular Monte Carlo dropout, restrict to some measure of uncertainty in prediction at the voxel level. In addition not to be clearly related to genuine medical uncertainty, this is not clinically satisfying as most objects of interest (e.g. brain lesions) are made of groups of voxels whose overall relevance may not simply reduce to the sum or mean of their individual uncertainties. In this work, we propose to go beyond voxel-wise assessment using an innovative Graph Neural Network approach, trained from the outputs of a Monte Carlo dropout model. This network allows the fusion of three estimators of voxel uncertainty: entropy, variance, and model's confidence; and can be applied to any lesion, regardless of its shape or size. We demonstrate the superiority of our approach for uncertainty estimate on a task of Multiple Sclerosis lesions segmentation.Comment: Accepted for presentation at the Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC) at MICCAI 202