I Would Prefer Not to Help You

Bartleby, the Scrivener recounts a story of a scrivener who would prefer not to do anything, whether that be parts of his job, changing his location, or eating his dinner. The narrator’s reaction to Bartleby’s lazy desires seem to be admirable, but his selfish motivation and false compassion are evident. The way the narrator views and treats Bartleby is consistent with the standards of philanthropy of the wealthy during the mid-nineteenth century. The narrator truly believes he has helped Bartleby to the best of his ability, yet fails to connect with Bartleby outside of offering him money and future assistance if required. This may be blamed on the narrator’s lack of relationship with God. People below the narrator’s socioeconomic status were viewed solely on how they could benefit him and his business and were expected to conform to the narrator’s standards. Bartleby the Scrivener, though a melancholy story leading to Bartleby’s death, can be used to see an accurate picture of philanthropy in the 1850s

Huntington\u27s Disease--A Review

Huntington’s disease is degenerative and effects both cognitive and motor functioning, beginning in the 20s and continuing a decline for about two decades until death. In this disease, the huntingtin gene on chromosome four codes for an abnormally elongated repeating CAG polypeptide sequence. This mutation causes an atrophy in the brain that translates into decreasing control of movements and other aspects of cognition. To date, there is no cure for Huntington’s disease, but there are treatments for many symptoms that accompany the disease. Even still, there are promising new methods that may be more beneficial to patients in the future

Possible beneficial effects of biomass for bioenergy crops

Debate about biomass for heat and/or power generation often revolves around the potential for greenhouse gas (GHG) emission mitigation versus the detrimental effects of growing the crops on biodiversity and landscape aesthetics. This mini review aims to highlight some of the possible beneficial effects of growing bioenergy crops, including other options than the most talked about miscanthus or salix/populus. To keep the text short, it explicitly does not deal with the issue of GHG emission mitigation by substituting non-renewable energy sources with a renewable source and omits all negative impacts that biomass crops may have, highlighting only possible benefits. This strong bias allows for more detailed examination of less common aspects and options concerning biomass production. The review deals with six different topics: - biodiversity; with a focus on the effects of resources made directly available by biomass crops and by accompanying changes in landscape structure and rotation times - water and nutrient management; in the context of biomass production in shelterbelts or riparian buffer strips for non-point source pollution mitigation and flood peak mitigation - phytoremediation; including brownfield recultivation and landfill leachate treatment - farm diversification and agroforestry; introducing options for multi-use forestry in combination with other biomass crops and use of coppice woodlands in livestock keeping - farm animal welfare; farmer experiences and ongoing research - public amenity; examining the potential role of biomass crops for swine odor mitigation and other more unusual applications It is concluded that, dependent on regulation and the production systems, large scale biomass for bioenergy production can have considerable positive effects in many areas and offers options for innovative farm management and nature conservation as well as interesting nonstandard applications. Bioenergy crops on organic farms look especially promising for biodiversity conservation

Model Creation and Equivalence Proofs of Cellular Automata and Artificial Neural Networks

Computational methods and mathematical models have invaded arguably every scientific discipline forming its own field of research called computational science. Mathematical models are the theoretical foundation of computational science. Since Newton's time, differential equations in mathematical models have been widely and successfully used to describe the macroscopic or global behaviour of systems. With spatially inhomogeneous, time-varying, local element-specific, and often non-linear interactions, the dynamics of complex systems is in contrast more efficiently described by local rules and thus in an algorithmic and local or microscopic manner. The theory of mathematical modelling taking into account these characteristics of complex systems has to be established still. We recently presented a so-called allagmatic method including a system metamodel to provide a framework for describing, modelling, simulating, and interpreting complex systems. Implementations of cellular automata and artificial neural networks were described and created with that method. Guidance from philosophy were helpful in these first studies focusing on programming and feasibility. A rigorous mathematical formalism, however, is still missing. This would not only more precisely describe and define the system metamodel, it would also further generalise it and with that extend its reach to formal treatment in applied mathematics and theoretical aspects of computational science as well as extend its applicability to other mathematical and computational models such as agent-based models. Here, a mathematical definition of the system metamodel is provided. Based on the presented formalism, model creation and equivalence of cellular automata and artificial neural networks are proved. It thus provides a formal approach for studying the creation of mathematical models as well as their structural and operational comparison.Comment: 13 pages, 1 tabl