A Moral Program for Myself as a Person and as a Professional Essay

A Moral Program for Myself as a Person and as a Professional - Essay Example Nevertheless, in order to attain this betterment, I need to come up with a moral program for my personal and professional lives. Whether it is applying the ethical principles of Aristotle, Kant and Mill, or combating moral illiteracy within my department, I plan to use my newfound information to its greatest potential. Therefore, this article first elucidates on the moral program that I would implement in my professional life as a nurse. Consequently, the second part is on a program fitted for my personal life as a single mother to a four-year-old child. Out of all the philosophers that we studied during the course, Aristotles virtue ethics is the most suitable theory for my profession. According to Solomon (1992), Aristotle believed that â€Å"virtuous acts required conscious choice and moral purpose or motivation† (p. 321). In this regard, this is the most crucial aspect that I must exemplify in my professional life as a nurse. Furthermore, the six dimensions of virtue ethics are community, excellence, role identity, holism, integrity and judgment are crucial for an exemplary career as a nurse. According to Solomon (1992), Aristotles virtue ethics has its foundation â€Å"upon the character of a moral agent as a driving force for ethical behavior† (p. 326). As registered nurses, we have a code of ethics, which are similar to Aristotles virtue ethics. From a general point of view, the nursing code of ethics calls for a nurse to practice with sympathy and reverence for the natural dignity, value and distinctiveness of every human being (American Nurses Association [ANA], 2011, p. 3). In this regard, I need to engage Aristotle’s virtue ethics as a nurse in order to practice compassion and respect my patients. In addition, ANA (2011) notes that the second provision in this code of ethics provides that â€Å"the nurse’s primary commitment is to the patient, and not to the company or hospital,

The Benefits of increasing Drinking Age Research Paper

The Benefits of increasing Drinking Age - Research Paper Example In many developed nations such as USA and Australia, the legal age for consuming alcohol is 21, but there are sections of society, which claim that lowering drinking age is the best solution to curb this habit among youngsters and specifically students. However, those who propose lowering drinking age as a feasible solution in this regard does not understand the salient disadvantages associated with allowing drinking at teen-age. Alcohol consumption is no more a habit or just a beverage option among youngsters; it has become a way of life, a part of the culture in today's scenario (Alcohol and Drug Information Service). There is a dire need to restrict their access to alcohol because it is a proven fact that starting to drink early can impose several short-term as well as long-term disadvantages on human health and society. This paper is an attempt to evaluate the benefits of increasing the drinking age from various aspects of an individual’s life as well as the impact on gove rnment and society in a broader spectrum. Health-related benefits of increasing drinking age: Increasing drinking age restricts young students from consuming alcohol at an early age, and as they reach adulthood, the craving for alcohol is likely to die-down or controlled. Various critics of increasing drinking age argue that when people can vote and marry at 18, why cannot they drink according to their choice? The problem is that voting and marriage do not harm a person’s psyche, mental development, and physiological health. However, consuming alcohol is susceptible to infinite life-risking implications from every possible aspect of human health and also considerably deters public welfare. The most significant point in the debate upon lowering or increasing drinking age is that, Is drinking suitable for individual health at all? Then the other point that arises is that will it benefit young people in any way if they are allowed. to drink at the age of 18? The fact which canno t be ignored is that alcohol in itself is extremely injurious to health, and its impact can be devastating. Frances Webb and Ellie Whitney claimed that â€Å"Age does matter. Young people do not benefit their health by drinking; rather, they increase their risk of dying from all causes; young non-drinkers are found to have a lower risk of dying than even light drinkers† (101). There is enough substance in this claim from Webb and Whitney, since if medical science research is anything to abide by, then it is true that drinking is not a healthy habit at all, instead, it becomes the base for various life-threatening ailments. It is a reality that alcohol consumption paves the way for more than 60 fatal diseases in the human body (Freeman). James Garbutt, a psychiatry professor and researcher of Alcohol studies at the University of North Carolina, revealed that â€Å"Alcohol does all kinds of things in the body, and we're not fully aware of all its effects. It's a pretty complic ated little molecule† (Freeman). Diseases like Anemia, Cancer, Cardiovascular problems, Gout, Depression, Nerve damage, Dementia, high-blood pressure, Pancreatitis, and Cirrhosis are all caused by alcohol consumption, and the virus gets triggered more intensively if one starts drinking at an early stage of life (Freeman).  

Analyze the article Essay Example | Topics and Well Written Essays - 500 words

Analyze the article - Essay Example A drop in the stock market has increased adverse selection and moral hazards because it has resulted in a weakening of the market value of firms' net worth, so lenders are less eager to lend, as deficits from loans are likely to be acute. This decline in lending has then triggered investment and aggregate yield to decline. Also, the waning corporate net worth has increased moral hazard inducements for companies to make risky investments because they now have less to lose. Again this increase in moral hazard makes lending less attractive. The failure of financial institutions in the mortgage debacle, together with the drop in the stock market has led to uncertainty in financial markets. It is more difficult to determine good from bad credit, which again has resulted to a fall in lending, investment and cumulative activity. The source of the current bank panic therefore, is asymmetric information. The result is that loan funds have been reduced and the price of intermediation has risen, which has caused a drop in investment and a decline in aggregate economic activity (Mishkin).

The Benefits of increasing Drinking Age Research Paper

The Benefits of increasing Drinking Age - Research Paper Example In many developed nations such as USA and Australia, the legal age for consuming alcohol is 21, but there are sections of society, which claim that lowering drinking age is the best solution to curb this habit among youngsters and specifically students. However, those who propose lowering drinking age as a feasible solution in this regard does not understand the salient disadvantages associated with allowing drinking at teen-age. Alcohol consumption is no more a habit or just a beverage option among youngsters; it has become a way of life, a part of the culture in today's scenario (Alcohol and Drug Information Service). There is a dire need to restrict their access to alcohol because it is a proven fact that starting to drink early can impose several short-term as well as long-term disadvantages on human health and society. This paper is an attempt to evaluate the benefits of increasing the drinking age from various aspects of an individual’s life as well as the impact on gove rnment and society in a broader spectrum. Health-related benefits of increasing drinking age: Increasing drinking age restricts young students from consuming alcohol at an early age, and as they reach adulthood, the craving for alcohol is likely to die-down or controlled. Various critics of increasing drinking age argue that when people can vote and marry at 18, why cannot they drink according to their choice? The problem is that voting and marriage do not harm a person’s psyche, mental development, and physiological health. However, consuming alcohol is susceptible to infinite life-risking implications from every possible aspect of human health and also considerably deters public welfare. The most significant point in the debate upon lowering or increasing drinking age is that, Is drinking suitable for individual health at all? Then the other point that arises is that will it benefit young people in any way if they are allowed. to drink at the age of 18? The fact which canno t be ignored is that alcohol in itself is extremely injurious to health, and its impact can be devastating. Frances Webb and Ellie Whitney claimed that â€Å"Age does matter. Young people do not benefit their health by drinking; rather, they increase their risk of dying from all causes; young non-drinkers are found to have a lower risk of dying than even light drinkers† (101). There is enough substance in this claim from Webb and Whitney, since if medical science research is anything to abide by, then it is true that drinking is not a healthy habit at all, instead, it becomes the base for various life-threatening ailments. It is a reality that alcohol consumption paves the way for more than 60 fatal diseases in the human body (Freeman). James Garbutt, a psychiatry professor and researcher of Alcohol studies at the University of North Carolina, revealed that â€Å"Alcohol does all kinds of things in the body, and we're not fully aware of all its effects. It's a pretty complic ated little molecule† (Freeman). Diseases like Anemia, Cancer, Cardiovascular problems, Gout, Depression, Nerve damage, Dementia, high-blood pressure, Pancreatitis, and Cirrhosis are all caused by alcohol consumption, and the virus gets triggered more intensively if one starts drinking at an early stage of life (Freeman).  

Realism and Its Role in US War Against Iraq Essay Example for Free

Realism and Its Role in US War Against Iraq Essay Presence of biological warfare, inhumane leadership, anti-democracy; these were the reasons which were proclaimed in the past explaining US war against Iraq. I believe that US spearheaded by then President Bush played Realists in their decision-making vis a vis the issue at hand. Tony Blair himself admitted few months after US won Iraq over their Head of State, Saddam Hussein, that there were no biological warfare proven to be under the custody of the latter’s government. Moreover, most nations believe that despite Hussein’s dictatorial means, he was nonetheless feared hence was able to maintain peaceful coexistence between two Islamic yet conflicting groups- the Sunni and Shi’ite. As regards, the question of the absence of democratic government in Iraq, isn’t the establishment and sustainability of any government dependent on its constituents/nationals? Who is the United States to take away the chance from Iraq’s own people to deal with their own government and its leader should there be a question of legitimacy? Perhaps, guided by Realist perspective of International Relations, the following reasons are more truthful; security, statism, and self-help. Military power according to Realism is a measure of political power relations among states alongside economic power. States are rational and unitary actors whose decisions are always based on a calculation of survival and national security. There is the absence of universal principles while the only guide of states in an anarchic set-up is pragmatic assessment of other state’s actions in solving problems. How then are these helpful in the analysis of US intentions toward Iraq? US seeking to maintain its global dominance would have to sustain military power. While Liberals and Idealists thought world peace could be attained and that no more wars shall ever exist, US apparently showed that war is still a solution and a means to furthering state gains. Oil is Iraq’s source of wealth and power. If that was the only missing link to US’ superiority, by all means, US would get hold of it. Oil promotes military and economic power. It also gives US security against threats from North Korea. Hence, for me, it was the desire of the Bush administration to retain hegemonic status- free from external threats of every form that made US enter into a catastrophic war.

The Science Of Artificial Neural Networks Psychology Essay

The Science Of Artificial Neural Networks Psychology Essay The science of Artificial Neural Networks (ANNs), commonly referred as Neural Networks, stills a new and promising area of research. The concept of creation of neural networks exists for many decades. Nevertheless neural networks have become known and have been developed in international levels only in the recent years. It is noteworthy, scientist showing interest in neural networks, come from different scientific areas such as chemistry, medicine, physics, mathematics, engineering and the list goes on. That shows Neural Networks is a new challenge in science. No other science today combines and needs direct knowledge from such diverse areas. One of the main differences of the Artificial Neural Networks from the biological is that while ANNs learn through training and experience just like the biological ones but they follow different rules from regular computers. A Neural Network is a parallel data processing system consisted by multitude of artificial neurons, organized in structure s similar with the ones in human brain. They function as parallel computing devices made by many highly interconnected simple processors. Artificial Neurons are mainly organized in layers. The first of those layers called the input layer and is used to insert the data. Input layers are unable to proceed to any sort of computation as its elements do not comprise input weights or bias (threshold). The axon: mean of transfer of neural signals from the neuron. Its length can be tens of thousands of times the diameter of its body and it is characterized by high electrical resistance and very large capacitance. Every neuron has only one axon, however it can branch and thus enabling communication with many target cells or other neurons. The dendrite: short highly branched cell projections (filaments). Most neurons have many dendrites, attached on the soma and increase the surface area. There are approximately 10^3 to 10^4 dendrites per neuron, to receive information from other neurons through synapses they are covered with and transmit electrochemical stimulation to the soma. The axon terminal: located in the end of the axon and is responsible for transmitting signals on to other neurons. On axon terminals are attached the terminal buttons, that store the information in synaptic vesicles and secreting them in neurotransmitters. As mentioned above, the connection between neurons happens through the synapses. Neural synapses are a silent exchange of information. The electrical nerve impulses travel along neurons and transmitted by chemical transmitters (neurotransmitters) in the next neuron across a tiny gap, the synapses and are located between the neuron and the neighboring cell (target cell). Therefore dendrites are very close to each other but never in touch. It is estimated that there are approximately 10 billion neurons in the human cortex, and 60 trillion synapses or connections (Shepherd and Koch, 1990). A number of neurons and their connections form a neural network. The entire system of neural networks in the human body forms the Central Nervous System. This system goes through the whole human body with central points the brain and the spine. During lifetime, synapses are in constant dynamic equilibrium, new are created and old are destroyed. The creation of new synapse happens when the brain acquires more experiences from the surrounding environment, learns, recognizes and understands. On the other side, diseases cause the devastation of neurons and therefore the devastation of synapses. In comparison to other cells, neurons might not replaced by new ones, if destroyed. That means after the birth of a new individual, its neural system is fully developed within the first few months of its life. A neuron can be either active or inactive. When it is activated, it produces an electric signal. This signal has intensity of only a few mVolt. The way those electric signals are produced is pretty similar with the way a capacitor works. Between the external and internal surface of the cell of the neuron there is a dynamic difference. Although the mass of the human brain is only the 2% of human body mass, consumes more than the 20% of the oxygen that goes in the organism. The energy consumption in the brain is about 20 Watt in comparison to a computer that needs a lot more. The computational power of brain is measured by three possible approaches: The number of synapses (Kandel, 1985), the computational power of the retina and multiply it by their brain-to-retina ratio (Moravec, 1998b), and the total useful energy used by the brain per second by the amount of energy used for each basic operation to give the maximum operation per second (Merkle, 1989) From the three approaches above, is concluded that the estimated computational power of human brain is about 10^14 operations per second (Ng, 2009). It is interesting to mention how the electric pulses are created to stimulate neurons. On the membrane of the cell it is appeared to be an electric potential difference between its external and internal surface just like a capacitor. Most of the times the negative charges found in the internal surface as they cant penetrate the membrane and leave the cell. The membrane has many openings that allow ions and atoms to go through each element from its own channel. The endings of the channels are secured by gates which directing the flow of those elements. Proteins that act like pumps force the elements to travel in the opposite direction from their natural and thus neurons consume larger amounts of energy. Eventually the balanced movement of the elements along the surface of the membrane produces an electric current which is the corresponding electrical pulse that stimulates the neuron. Once the neuron has fired it returns to a state of potential equilibrium and in this state it cant be fired again until it recovers. Each neuron has a specific threshold or weight. When electric signals reach that point, sum up and if their weight value is same or larger than the one of the threshold the neuron stimulates. If the sum of the signals is smaller than the required value of the threshold, then the neuron stays inactive. Add images. Models of artificial neurons As mentioned earlier, ANNs are parallel data processing systems, consisting out of large numbers of artificial neurons, inspired by the biological neurons. A neuron is an information-processing unit that is fundamental to the operation of a neural network (Haykin, 1999, pg-10). A neuron may have many inputs, an internal structure consisting out of multiple layers but it always has a single output. Every single neuron accepts variable input signals x0, x1, x2 à ¢Ã¢â€š ¬Ã‚ ¦xn. This corresponds to the electric pulses of the biological brain. Every input signal is multiplied by the synaptic weights of the neuron, wi, where i=1,2,3..n, the input nodes. The weights represent the biological synapses and indicate the strength of the bond (the connection) between them. The range of value of a weight can be positive or negative depending on if the function of synapse suspend or propagate (transmit) the stimuli from other neurons, unlike the biological synapses that do not take negative values. This is because external bias, b, are applied when the weights added. Bias or threshold, is the standard value of the internal potential energy of the neuron that the sum of the combined output must be reached in order the activation (or squashing) function to be activated. An important element of the neuronal body is the adder .At the adder, all the input signals, influenced by weight vectors are summing up together and produce a resultant combined output u. When the sum of weight is big (0 Therefore, the product u is given by the relationship: The result of combined output u, pass through the activation function, denoted with the letter  Ã¢â‚¬  ( ). The activation function is a non linear function where the resultant combined output u takes its final value y. The calculated activation output signal of the neuron is shown as: and where Therefore, Activation functions There are several activation functions, however three of the most basic types are the following 🙠 they slightly vary from book to book) The threshold activation function, which gives as an output 1, if the adder produce a value greater than the one of the threshold. This is expressed as: The Piecewise-Linear function, where the unity is assumed to be the amplification factor inside the linear region of operation (Haykin, 1999, pg:14) The Sigmoid function, which is expressed as: Where  Ã‚ ¡ is is the slope parameter of the sigmoid function. This function is one of the most important and most commonly used as it provides non-linearity to the neuron. Some other activation functions are, the rump function, the bipolar sigmoid function, and the signum function. The signum function gives a positive or negative output, with values usually ranging from 1 to -1 depending on the value of the summation of the weights on the threshold. This can be applied to the activation functions mentioned above and more specifically to the threshold faction giving: Add images and graphs A simple neural network In this paragraph, neural networks will be introduced, starting from their simplest form. Every neural network consists out of hundreds or thousands of tiny units, the neurons. Each neuron has an input where the electric signals are received. A neuron may have more than one input but no matter how many layers of neurons and synaptic connections are in between (the body), there is always one output value. The neurons of a layer between each input and output are not connected to each other however each layer is interconnected with the layer of the next and the previous level. In its simplest form, a neuron has no layers but is limited only to an input and an output. Every signal that leaves an output and enters an input has a value, the weights. The weights represent the importance of each signal reaching the threshold of an input. Depending on the value of weight (wn), the contribution of the electric signal can be great or small for the function of the system. Artificial intelligence and neural networks Historical background (The study of the brain and the biological neurons has started thousands of years ago.) However, as artificial neural networks started to be developing the past century, the historical background still not as broad as in other sciences. The first union of mathematical logic and neuropsychology, commenced in 1943 by Warren S. McCulloch and Walter Pitts. McCulloch was a pioneer neuroanatomist and psychiatrist. Pitts was a young mathematical prodigy, who joined McCulloch in 1942. (Haykin, 1999, pg: 38). Together they created the first model a neural network that was represented by a great number of interconnected neurons. In their well-known paper, A logical calculus of the ideas immanent in nervous activity, (1943), came up with theorems that describe the function of neurons and the neural networks. As a result of those theorems, neural networks and artificial intelligence ideas established a new era of research began. The paper of McCulloch and Pitts, triggered the interest of many scientists like von Neumann, Wiener and Uttley in their effort to extract information of the function of biological neurons and create corresponding artificial ones. In 1949 another idea appeared by D. Hebb who published the book The Organisation of Behavior. Although his book had greater influence on the psychological rather than the engineering community, he introduced the concept of postulate and learning and the synaptic modification rule, which suggests that the connectivity of the brain changes continually thorough its entire life in the process of learning new tasks. From 1950 to 1979, a number of remarkable books were written about neural networks developing the ideas of neurons abilities, such as learning and memorising. Some of these books are the Design for a Brain: The origin of Adaptive Behaviors, (1952) by Ashby, that still exciting to read nowadays, and the Learning Machines, (1965) by Nilsson, one of the best-written expositions about linearly separable patterns in hypersurfaces. (Haykin, 1999, pg: 40). A novel model, the perceptron, introduced in 1958 by F. Rosenblatt. The perceptron is a very simple model of supervised learning, which has only one input and one output built around a nonlinear neuron (Haykin pg 135). Although this model appeared to have many limitations the idea of training the neurons encouraged many scientists for building larger neural networks. In 1969, Minsky and Papert in their book Perceptron they make a complete evaluation of the features and uses of the perceptrons. It proved with mathematics that there were fundamental limitations on the computational ability of single-layered perceptrons and therefore those limitations assumed to carry on in the multilayered levels of perceptrons. A period followed were scientists start losing hope about neural networks and turned to other knowledge based systems. In 1982, neural networks make an interesting come back when John Hopfield proved in a strict mathematical way that by time a neural network can be adjusted to use the minimum energy to function just like human brain does. In addition, Hopfield proved that a simple neural network can be used as storage devise. Such networks are called the Hopfield networks. A very important work was published in 1986 by Rumelhart and McClelland. The two-volume book, Parallel Distributed Processing: Explorations in the Microstructures of Cognitions, shows new methods of training neural networks and introduces the idea of parallel data processor. This theory had a great influence in the use of back-propagation learning as and allowed the development of multilayered networks (perceptrons). The books published by McCulloch- Pitts (1943), Hopfield (1982) and Rumelhart-McClelland (1986), are the most influential in the revolution of neural networks. Since 1980 to nowadays, Neural Networks have been established as a new independent science branch. Conferences and magazines appeared with complete interest on artificial neural networks while the first commercial companies dedicated to the improvement of them, created, supported by thousands of members worldwide especially in America, Europe and Japan. Learning processes/ training Fundamental ideas The present, looking to future Ann applications areas Anns in civil engineering Can it be applied in? Benefits/disadvantages Program Observations comments summary references

Gender Differences and Gender Stereotypes from a Psychological Perspect

Gender Differences and Gender Stereotypes from a Psychological Perspective Gender Differences and Gender Stereotypes Gender differences and gender stereotypes are fascinating in that one must sift through the theories, assumptions and inevitable confusion to distinguish the reality from the assumption. Men and women are obviously different, especially inherently, but how? And why? And which differences are more individualized than generalized? Even more interesting is to observe how the differences between men and women have evolved, especially over the past 30 years- since the sexual revolution. A generous amount of research has been done since then, and this research is continually updated as men and women evolve themselves. Our understanding of the innate gender differences as opposed to the acquired one is still growing, yet it still seems tainted by such misunderstanding. There is a lot of research regarding stereotypical views of men and women, and psychological testing has helped integrate and differentiate the documented "real" behavior. Even through the sexual revolution, there still exists gender-role stereotypes, although the stereotyping has decreased in recent years. Surprisingly, stereotypes are adhered to by people of every status, educated or not. Americans generally believe that men are aggressive, independent, unemotional, dominant, active, and overly self-confident. On the other hand, women are thought of to be gentle, religious, neat and dependent. Americans in general seem to believe that males and females have distinguishing opposing characteristics. Aggressiveness is one behavior which is consistently noted in psychological gender differences. The majority of people seem to believe th... ..."100% masculine" or "100% feminine." There is no argument about men and women being physically different, yet there has been much debate involving the intangible differences between the two differences. Over the centuries, stereotyping of men’s and women’s intangible aspects has evolved. This stereotyping has influenced our society so much. The studies which are done refuting the fact that stereotyping of a gender is not always valid turns out to be invalid, since the studies themselves have been influenced by stereotyping. It is hard to argue whether the stereotypes traits of each gender are true or not. However, it is important for us to overlook the stereotyping of the two genders and focus on each individual and respect their individuality, whether they demonstrate more masculinity, femininity, or either, which may or may not fit their gender stereotyping. Gender Differences and Gender Stereotypes from a Psychological Perspect Gender Differences and Gender Stereotypes from a Psychological Perspective Gender Differences and Gender Stereotypes Gender differences and gender stereotypes are fascinating in that one must sift through the theories, assumptions and inevitable confusion to distinguish the reality from the assumption. Men and women are obviously different, especially inherently, but how? And why? And which differences are more individualized than generalized? Even more interesting is to observe how the differences between men and women have evolved, especially over the past 30 years- since the sexual revolution. A generous amount of research has been done since then, and this research is continually updated as men and women evolve themselves. Our understanding of the innate gender differences as opposed to the acquired one is still growing, yet it still seems tainted by such misunderstanding. There is a lot of research regarding stereotypical views of men and women, and psychological testing has helped integrate and differentiate the documented "real" behavior. Even through the sexual revolution, there still exists gender-role stereotypes, although the stereotyping has decreased in recent years. Surprisingly, stereotypes are adhered to by people of every status, educated or not. Americans generally believe that men are aggressive, independent, unemotional, dominant, active, and overly self-confident. On the other hand, women are thought of to be gentle, religious, neat and dependent. Americans in general seem to believe that males and females have distinguishing opposing characteristics. Aggressiveness is one behavior which is consistently noted in psychological gender differences. The majority of people seem to believe th... ..."100% masculine" or "100% feminine." There is no argument about men and women being physically different, yet there has been much debate involving the intangible differences between the two differences. Over the centuries, stereotyping of men’s and women’s intangible aspects has evolved. This stereotyping has influenced our society so much. The studies which are done refuting the fact that stereotyping of a gender is not always valid turns out to be invalid, since the studies themselves have been influenced by stereotyping. It is hard to argue whether the stereotypes traits of each gender are true or not. However, it is important for us to overlook the stereotyping of the two genders and focus on each individual and respect their individuality, whether they demonstrate more masculinity, femininity, or either, which may or may not fit their gender stereotyping.