Somebody\u27s Waiting for You

VERSE 1In a cool shady nook by the side of a brook, two sweet maidens were fishing aloneThey talked as they fished, and the younger girl wished for the sweetheart, she never had knownThe other girl said, with a toss of her head, “Cheer up dear, there’s no cause to be blueYour love you’ve not met, but he’ll come to you yet, for there’s somebody waiting for you.” CHORUSSomewhere, somebody’s waiting for you, you, you.Somewhere, somebody’s longing, whose heart is trueSometime you’ll love somebody, who loves you tooSomewhere, somebody’s waiting for you, you. VERSE 2Then a youth, passing by, heard her sister’s reply, and he joined in their chat, half in fun.He said, “It is true, someone’s waiting for you, and I wish you thought, I was the one.”She paused for a while, and she said, with a smile, “I’m not sure, but you may be, it’s true.But if you are wrong, why, you won’t worry long, for there’s somebody waiting for you.” CHORU

Tackin\u27 \u27em down : song

https://digitalcommons.library.umaine.edu/mmb-vp/3735/thumbnail.jp

Give A Little Credit To The Navy : Song

https://digitalcommons.library.umaine.edu/mmb-vp/1518/thumbnail.jp

Design Methodology of Neural Network for Signal Processing

Abstract:There is various new & advance technologies in medical science we are trying to process the information artificially as our biological system performs inside our body. The main focus of the paper is on the implementation of Neural Network Architecture (NNA) with on chip learning in analog VLSI for generic signal processing applications. In the paper we used analog components like Gilbert Cell Multiplier (GCM), Neuron activation Function (NAF) are used to implement artificial NNA. Artificial intelligence through a biological word is realized based on mathematical equations and artificial neurons. The analog component is used for the compress of multipliers and adder in neural network, which is along with the tan-sigmoid function circuit using MOS transistor in sub threshold region. To trained the neural architecture we used the back propagation algorithm in analog domain with new techniques of weight storage. Layout design and verification of the proposed design is carried out using microwind3.1 software tool. The technology used in designing the layout is 45nm CMOS technology

Emmalina! the moon is shining, Emmalina!

(Published By Jerome H. Remick

At first you hold your Sweetie tight and \u27Eagle rock\u27 [first line of chorus]

Performance Medium: Piano and Voice (with lyrics

Internalized Weight Stigma and its Ideological Correlates Among Weight Loss Treatment Seeking Adults

There are significant economic and psychological costs associated with the negative weight-based social stigma that exists in American society. This pervasive anti-fat bias has been strongly internalized among the overweight/obese. While the etiology of weight stigma is complex, research suggests that it is often greater among individuals who embrace certain etiological views of obesity or ideological views of the world. This investigation examined 1) the level of internalized weight stigma among overweight/obese treatment seeking adults, and 2) the association between internalized weight stigma and perceived weight controllability and ideological beliefs about the world (\u27just world beliefs\u27, Protestant work ethic). Forty-six overweight or obese adults (BMI \u3eor=27 kg/m2) participating in an 18- week behavioral weight loss program completed implicit (Implicit Associations Test) and explicit (Obese Person\u27s Trait Survey) measures of weight stigma. Participants also completed two measures of ideological beliefs about the world ( Just World Beliefs , Protestant Ethic Scale) and one measure of beliefs about weight controllability (Beliefs about Obese Persons). Significant implicit and explicit weight bias was observed. Greater weight stigma was consistently associated with greater endorsement of just world beliefs, Protestant ethic beliefs and beliefs about weight controllability. Results suggest that the overweight/obese treatment seeking adults have internalized the negative weight-based social stigma that exists in American society. Internalized weight stigma may be greater among those holding specific etiological and ideological beliefs about weight and the world

Weight Bias and Weight Loss Treatment Outcomes in Treatment-Seeking Adults

BACKGROUND: Few studies have explored the relationship between weight bias and weight loss treatment outcomes. PURPOSE: This investigation examined the relationship between implicit and explicit weight bias and (a) program attrition, (b) weight loss, (c) self-monitoring adherence, (d) daily exercise levels and overall caloric expenditure, (e) daily caloric intake, and (f) daily caloric deficit among overweight/obese treatment-seeking adults. METHODS: Forty-six overweight/obese adults (body mass index \u3e or = 27 kg/m(2)) participating in an 18-week, stepped-care, behavioral weight loss program completed implicit and explicit measures of weight bias. Participants were instructed to self-monitor and electronically report daily energy intake, exercise, and energy expenditure. RESULTS: Greater weight bias was associated with inconsistent self-monitoring, greater caloric intake, lower energy expenditure and exercise, creation of a smaller caloric deficit, higher program attrition, as well as less weight loss during the self-help phase of the stepped-care treatment. CONCLUSIONS: Weight bias may interfere with overweight/obese treatment-seeking adults\u27 ability to achieve optimal health

Successful Weight Loss with Self-Help: A Stepped-Care Approach

In a stepped-care approach to treatment, patients are transitioned to more intensive treatments when less intensive treatments fail to meet treatment goals. Self-help programs are recommended as an initial, low intensity treatment phase in stepped-care models. This investigation examined the effectiveness of a self-help, stepped-care weight loss program. Fifty-eight overweight/obese adults (BMI ≥27 kg/m(2)) participated in a weight loss program. Participants were predominately Caucasian (93.1%) and female (89.7%) with a mean BMI of 36.6 (SD=7.1). Of those completing the program, 57% of participants (N=21) who remained in self-help maintained an 8% weight loss at follow-up. Participants who were stepped-up self-monitored fewer days and reported higher daily caloric intake than self-help participants. Once stepped-up, weight loss outcomes were equivalent between individuals who remained in self-help compared to those who were stepped-up. Individuals who were stepped-up benefited from early intensive intervention when unsuccessful at losing weight with self-help