Honey bee colony losses

No description supplie

Managing interactions between household food security and preschooler health:

Food security does not assure good nutrition. The nutritional status of an individual is influenced not only by food but also by nonfood factors, such as clean water, sanitation, and health care. The effect of all of these factors must be considered in efforts to rid the world of malnutrition. Food security will result in good nutrition only if nonfood factors are effectively dealt with. In this paper, Lawrence Haddad, Saroj Bhattarai, Maarten Immink, and Shubh Kumar show how malnutrition among preschool children is determined by a complex interaction of illness and lack of food. The authors look at three countries —Ethiopia, Pakistan, and the Philippines — to study how food availability and diarrhea interact and what this interaction means for preschooler malnutrition. Their results show that the links between food consumption, diarrhea, and malnutrition are stronger than most economic studies have assumed. When diarrhea is prevalent, the effects of food shortages on child malnutrition are worse, and when food is scarce, the effects of diarrhea on child malnutrition are worse.Food security Ethiopia., Malnutrition in children Ethiopia., Food security Pakistan., Malnutrition in children Pakistan., Food security Philippines., Malnutrition in children Philippines.,

Robotic 3D printing with earth: A case study for optimisation of 3D printing building blocks

The interest in 3D printed earthen buildings in developed countries has increased due to the demand for healthy, comfortable and sustainable buildings constructed with low carbon materials and laboursaving methods. However, the amount of research about this field is still limited. Our research aims to contribute to this field by optimising the robotic 3D printing process by investigating issues such as buckling while printing, adequate soil mix recipe for printing, print and extrusion speed calibration. This paper illustrates the process and the results of the temporary research project and the Robotic Cob Printing Workshop with MSc Computational Methods in Architecture (CMA) students at the Welsh School of Architecture, Cardiff University, in March 2022. The project aims to achieve structural stability with less material by using the geometry and the infill of the building block while exploring the role of computational design, robotic extrusion and material understanding in robotic 3D printing with earth as a low-carbon novel building method

Relativistic linear stability equations for the nonlinear Dirac equation in Bose-Einstein condensates

We present relativistic linear stability equations (RLSE) for quasi-relativistic cold atoms in a honeycomb optical lattice. These equations are derived from first principles and provide a method for computing stabilities of arbitrary localized solutions of the nonlinear Dirac equation (NLDE), a relativistic generalization of the nonlinear Schr\"odinger equation. We present a variety of such localized solutions: skyrmions, solitons, vortices, and half-quantum vortices, and study their stabilities via the RLSE. When applied to a uniform background, our calculations reveal an experimentally observable effect in the form of Cherenkov radiation. Remarkably, the Berry phase from the bipartite structure of the honeycomb lattice induces a boson-fermion transmutation in the quasi-particle operator statistics.Comment: 6 pages, 3 figure

Dynamin-related protein 1 is required for normal mitochondrial bioenergetic and synaptic function in CA1 hippocampal neurons.

Disrupting particular mitochondrial fission and fusion proteins leads to the death of specific neuronal populations; however, the normal functions of mitochondrial fission in neurons are poorly understood, especially in vivo, which limits the understanding of mitochondrial changes in disease. Altered activity of the central mitochondrial fission protein dynamin-related protein 1 (Drp1) may contribute to the pathophysiology of several neurologic diseases. To study Drp1 in a neuronal population affected by Alzheimer's disease (AD), stroke, and seizure disorders, we postnatally deleted Drp1 from CA1 and other forebrain neurons in mice (CamKII-Cre, Drp1lox/lox (Drp1cKO)). Although most CA1 neurons survived for more than 1 year, their synaptic transmission was impaired, and Drp1cKO mice had impaired memory. In Drp1cKO cell bodies, we observed marked mitochondrial swelling but no change in the number of mitochondria in individual synaptic terminals. Using ATP FRET sensors, we found that cultured neurons lacking Drp1 (Drp1KO) could not maintain normal levels of mitochondrial-derived ATP when energy consumption was increased by neural activity. These deficits occurred specifically at the nerve terminal, but not the cell body, and were sufficient to impair synaptic vesicle cycling. Although Drp1KO increased the distance between axonal mitochondria, mitochondrial-derived ATP still decreased similarly in Drp1KO boutons with and without mitochondria. This indicates that mitochondrial-derived ATP is rapidly dispersed in Drp1KO axons, and that the deficits in axonal bioenergetics and function are not caused by regional energy gradients. Instead, loss of Drp1 compromises the intrinsic bioenergetic function of axonal mitochondria, thus revealing a mechanism by which disrupting mitochondrial dynamics can cause dysfunction of axons

Training deep neural density estimators to identify mechanistic models of neural dynamics

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-- trained using model simulations-- to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features, and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics

Isotopic Production Cross Sections in Proton-Nucleus Collisions at 200 MeV

Intermediate mass fragments (IMF) from the interaction of $^{27}$Al, $^{59}$Co and $^{197}$Au with 200 MeV protons were measured in an angular range from 20 degree to 120 degree in the laboratory system. The fragments, ranging from isotopes of helium up to isotopes of carbon, were isotopically resolved. Double differential cross sections, energy differential cross sections and total cross sections were extracted.Comment: accepted by Phys. Rev.

Microwave device investigations

Materials, devices and novel schemes for generation, amplification and detection of microwave and millimeter wave energy are studied. Considered are: (1) Schottky-barrier microwave devices; (2) intermodulation products in IMPATT diode amplifiers; and (3) harmonic generation using Read diode varactors

On the number of contacts of a floating polymer chain cross-linked with a surface adsorbed chain on fractal structures

We study the interaction problem of a linear polymer chain, floating in fractal containers that belong to the three-dimensional Sierpinski gasket (3D SG) family of fractals, with a surface-adsorbed linear polymer chain. Each member of the 3D SG fractal family has a fractal impenetrable 2D adsorbing surface, which appears to be 2D SG fractal. The two-polymer system is modelled by two mutually crossing self-avoiding walks. By applying the Monte Carlo Renormalization Group (MCRG) method, we calculate the critical exponents $\phi$, associated with the number of contacts of the 3D SG floating polymer chain, and the 2D SG adsorbed polymer chain, for a sequence of SG fractals with $2\le b\le 40$. Besides, we propose the codimension additivity (CA) argument formula for $\phi$, and compare its predictions with our reliable set of the MCRG data. We find that $\phi$ monotonically decreases with increasing $b$, that is, with increase of the container fractal dimension. Finally, we discuss the relations between different contact exponents, and analyze their possible behaviour in the fractal-to-Euclidean crossover region $b\to\infty$.Comment: 15 pages, 3 figure