Grocery Store Activism: A WTO Compliant Means to Incentivize Social Responsibility

Despite the increases in global wealth attributable to globalization and increased international trade, the damage done by socially irresponsible production practices remains an area of concern for international human and labor rights advocates. Because international trade law under the World Trade Organization (WTO) imposes strict limitations on the policy options available to Member States, international human rights and international trade have been viewed as fundamentally at odds with one another. This Article argues that market-based incentives can be used to allow international trade to reinforce established human rights principles, rather than constantly undermining government attempts to formulate appropriate policy solutions. This Article proposes that the United States create and implement a voluntary, government-run system of human rights label. Like the content positive labels currently offered for organic products, this human rights labeling system would provide consumers with additional information in order to reward producers who had met certain standards. Unlike the current system that allows producers to place whatever “human rights” labels that they want on their products and allows numerous third-party certification schemes, a government-run system could serve to create one label that consumers will recognize as credible, consistent, and enforceable. Most importantly, the labeling system proposed by this Article does not run afoul of the United States’s commitments under the WTO. The two relevant agreements, the Agreement on Technical Barriers to Trade (TBT Agreement) and the General Agreement on Tariffs and Trade (GATT), are examined in depth for any possible conflicts. The Article concludes that because of the voluntary nature of the label, the proposed labeling scheme should be able to survive scrutiny by a WTO dispute settlement panel, if it such a challenge were to arise. Further, the Article argues that the label could be justified as a general exception, as provided for in Article XX of the GATT

The effects of low-level electromagnetic fields and ultraweak photon emission on biological systems.

The functionality of biological organisms is a product of minute-invisible forces and structures, which together form a cohesive ensemble that initiate the processes of life. The electromagnetic and photonic nature of biological life and its basic unit the cell may be considered a viable option for communication, survival and senescence. The basis of this investigation considers the dynamic nature of low-level electromagnetic fields and ultraweak photon emission as a mechanism for intracellular and intercellular interactions, which work under the premise of only demanding small quanta of energy. Metastatic cancerous cells have been observed to emit specific frequencies of photon emission compared to healthy cells and increase this emission in unfavorable conditions. The application of a specific sequence of patterns (MuKarb) at a specific intensity, observed in the dissolution of planarian worms, when applied to cancerous cells produce complete death of the exposed metastatic cells but not healthy cells. When such patterns of light at specific wavelengths are pulsed into the aforementioned cells, the emitted light from the cells in the pulsed pattern is observed relative to the duration of the light exposure. These effects become critical to the specificity of the appropriate pattern and intensity of the field, which has been linked to the importance of appropriate equipment configuration. The smallest iv changes in the current/voltage flow within the circuitry of the digital to analogue converter and electromagnetic field devices can make drastic changes with respect to the elimination of cancerous cells being observed or not. This phenomenon reflects the Aharanov-Bohm phase shifts in voltage within the electromagnetic field equipment and its importance in producing effects as a result of low-level electromagnetic fields. The application of specificity within low-level electromagnetic generating equipment has also been shown through the process of non-locality (entanglement) where appropriate and tuned apparatus are required to produce specific non-local effects. Successful non-local effects were observed through observing decreases in growth of melanoma cells through nontangible means, comparable to the manipulate local melanoma cells. These results converge on the premise and importance of properly tuned equipment for successful low-level electromagnetic field and photon exposures. Furthermore the interaction between the use of low-level electromagnetic fields and photons at specific pattern has shown the importance of interfering with the propagation of metastatic cells.Doctor of Philosophy (PhD) in Biomolecular Science

An Analytical Approach to Neuronal Connectivity

This paper describes how realistic neuromorphic networks can have their connectivity properties fully characterized in analytical fashion. By assuming that all neurons have the same shape and are regularly distributed along the two-dimensional orthogonal lattice with parameter $\Delta$, it is possible to obtain the accurate number of connections and cycles of any length from the autoconvolution function as well as from the respective spectral density derived from the adjacency matrix. It is shown that neuronal shape plays an important role in defining the spatial spread of network connections. In addition, most such networks are characterized by the interesting phenomenon where the connections are progressively shifted along the spatial domain where the network is embedded. It is also shown that the number of cycles follows a power law with their respective length. Morphological measurements for characterization of the spatial distribution of connections, including the adjacency matrix spectral density and the lacunarity of the connections, are suggested. The potential of the proposed approach is illustrated with respect to digital images of real neuronal cells.Comment: 4 pages, 6 figure

Experimental Demonstration That Aharanov-Bohm Phase Shift Voltages In Optical Coupler Circuits of Tuned Patterned Magnetic Fields Is Critical for Inhibition of Malignant Cell Growth

The physical processes by which specific point duration magnetic fields affect aberrant expressions of living matter may involve non-classical mechanisms.The Aharanov-Bohm voltage for a quantum of energy that is convergent with the quotient of the protons magnetic moment to its charge multiplied by the viscosity of water at homeostatic temperatures applied across the distance of O-H bonds in conjunction with its phase modulation is about ±4.3 V. Application of frequency shifting, temporally-patterned magnetic fields produced by 3 ms point durations at average intensities of ~28 mG (that are equivalent to Nernst thresholds for plasma membranes) generated through optocoupler light emitting diodes produced the strongest inhibition of malignant cells growth when the pre-coupler value for the circuit maintenance was ±4.3 V compared to increments of voltage below or above this value. Spatial expansion of the effective zone for growth diminishment also occurred with this pre-voltage level. These results indicate that phase modulation of the electrons mediating cellular molecular pathways may be central to the etiology and potential treatment of malignant cells but not for normal cells dynamics. Consideration of quantum effects rather than classical electromagnetic theory may be a more effective strategy for impeding the physical bases for the molecular pathways that define malignant cells

Performance of networks of artificial neurons: The role of clustering

The performance of the Hopfield neural network model is numerically studied on various complex networks, such as the Watts-Strogatz network, the Barab{\'a}si-Albert network, and the neuronal network of the C. elegans. Through the use of a systematic way of controlling the clustering coefficient, with the degree of each neuron kept unchanged, we find that the networks with the lower clustering exhibit much better performance. The results are discussed in the practical viewpoint of application, and the biological implications are also suggested.Comment: 4 pages, to appear in PRE as Rapid Com

Genome-scale metabolic model of the rat liver predicts effects of diet restriction.

Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver\u27s energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected hub genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver\u27s response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease

Mff is an essential factor for mitochondrial recruitment of Drp1 during mitochondrial fission in mammalian cells

Localization of the dynamin-related GTPase Drp1 to mitochondria relies on the mitochondrial fission factor Mff

Topology and Computational Performance of Attractor Neural Networks

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world and scale-free topologies. The random net is the most efficient for storage and retrieval of patterns by the entire network. However, in the scale-free case retrieval errors are not distributed uniformly: the portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. Implications for brain function and social dynamics are suggestive.Comment: 2 figures included. Submitted to Phys. Rev. Letter

Global and regional brain metabolic scaling and its functional consequences

Background: Information processing in the brain requires large amounts of metabolic energy, the spatial distribution of which is highly heterogeneous reflecting complex activity patterns in the mammalian brain. Results: Here, it is found based on empirical data that, despite this heterogeneity, the volume-specific cerebral glucose metabolic rate of many different brain structures scales with brain volume with almost the same exponent around -0.15. The exception is white matter, the metabolism of which seems to scale with a standard specific exponent -1/4. The scaling exponents for the total oxygen and glucose consumptions in the brain in relation to its volume are identical and equal to $0.86\pm 0.03$, which is significantly larger than the exponents 3/4 and 2/3 suggested for whole body basal metabolism on body mass. Conclusions: These findings show explicitly that in mammals (i) volume-specific scaling exponents of the cerebral energy expenditure in different brain parts are approximately constant (except brain stem structures), and (ii) the total cerebral metabolic exponent against brain volume is greater than the much-cited Kleiber's 3/4 exponent. The neurophysiological factors that might account for the regional uniformity of the exponents and for the excessive scaling of the total brain metabolism are discussed, along with the relationship between brain metabolic scaling and computation.Comment: Brain metabolism scales with its mass well above 3/4 exponen

Genetically altered AMPA-type glutamate receptor kinetics in interneurons disrupt long-range synchrony of gamma oscillation

Gamma oscillations synchronized between distant neuronal populations may be critical for binding together brain regions devoted to common processing tasks. Network modeling predicts that such synchrony depends in part on the fast time course of excitatory postsynaptic potentials (EPSPs) in interneurons, and that even moderate slowing of this time course will disrupt synchrony. We generated mice with slowed interneuron EPSPs by gene targeting, in which the gene encoding the 67-kDa form of glutamic acid decarboxylase (GAD67) was altered to drive expression of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptor subunit GluR-B. GluR-B is a determinant of the relatively slow EPSPs in excitatory neurons and is normally expressed at low levels in γ-aminobutyric acid (GABA)ergic interneurons, but at high levels in the GAD-GluR-B mice. In both wild-type and GAD-GluR-B mice, tetanic stimuli evoked gamma oscillations that were indistinguishable in local field potential recordings. Remarkably, however, oscillation synchrony between spatially separated sites was severely disrupted in the mutant, in association with changes in interneuron firing patterns. The congruence between mouse and model suggests that the rapid time course of AMPA receptor-mediated EPSPs in interneurons might serve to allow gamma oscillations to synchronize over distance