ABSTRACT: Thyroid cancer is the most common endocrine cancer and majority of thyroid neoplasms arise from follicular epithelial cells. Thyroid lesions mostly show overlapping features, which leads to a difficulty in diagnosis. Distinction between these lesions is important for appropriate management and prognosis. In this study, we found statistically significant association of extent and intensity of HBME-1 for different thyroid nodular lesions which share similar morphological features (p<0.05 and p<0.01). This makes it a good marker for differentiation of non-neoplastic and neoplastic nodular lesions of thyroid where overlapping features cause difficulty in diagnosis. \nMETHODOLOGY: Seventy-three (73) selected cases from lobectomy and thyroidectomy specimens from 2008 to 2012 were analyzed by immunohistochemical (IHC) staining with HBME-1.\nCONCLUSION: HBME-1 is a good marker to distinguish neoplastic from non-neoplastic follicular epithelial derived nodular thyroid lesions and discriminate neoplastic lesions.

UNICEF (2014) stated that 28 million stunted children are in East Asia-Pacific. They were 36 % in Indonesia and 16% in Thailand. Thailand is not only facing under-nutrition problem, but also over-nutrition. Evidence shows that about 80 per cent of children with malnutrition who have been identified through active case finding. The aim of this research is investigating the differences and similarities of case-finding model (process, strength, weakness, opportunity, threat, and effectiveness) of malnourished children, i.e. under-nutrition and over-nutrition, in Indonesia and Thailand. The research approach is qualitative approach; the focus is on case-finding model of malnourished children (under and over-nutrition). The data used mostly are secondary data (from previous studies and applicable policies), collected from document study, while supporting data are primary data, collected from in-depth interview or focus group discussion (FGD) with health/ community volunteers or medical/ health services officer. The conclusion of this research is the finding of nutrition case among Indonesia and Thailand community are conducted with similar model, which is by community empowerment through trained health cadre. The model and activity conducted are arranged as local condition and circumstances related with geography, community, socio culture and social capital which then resulting a policy, continued with program and activity. In Indonesia, the case finding and the solving still focusing on malnutrition status while in Thailand, particularly in urban area has been shifted towards obesity case solving.

Carnivorous fish have special dietary needs and a meat-centered diet, focused on the supply of animal proteins; this should constitute part of their food regimen.

Training has an important effect on commitments of organizations. Organizational outcomes can be achieved by performing training strategies and programs to enhance training. The objective of organizational training is to develop knowledge and skills of people so they can do their roles efficiently and effectively. Two specific goals and related seven specific practices of organizational training Process Area in Capability Maturity Model Integration (CMMI) will be analyzed in order to set common measures for them. The CMMI is a frame for assessment and improvement of software systems. We implement the Goal Questions Metrics (GQM) model on the two specific goals and related seven specific practices of organizational training Process Area in CMMI to set the measures.

Optimal control deals with the problem of finding a\ncontrol law for a given completely state controllable system\nsuch that a certain optimality criterion (performance index) \nand best possible behavior with respect to the this criterions\nachieved. If some states are not accessible for feedback, a state\nestimator to estimate these states can be used. If the system is\nnonlinear system, the conventional controller cannot predict\nthe systems behaviors with acceptable accuracy In this paper\ndifferent modified estimators based controller are presented. A\nmodified controllers such as Optimal estimator based on linear\nquadratic regulator with integral control (OELQRIC)is \ndesigned in this work. This controller will make linearized\nsystem operates as model reference for nonlinear systems. The\nobtained results are remarkably acceptable .

This paper presents a design and simulation of UPQC system for limitations of nonlinear load factors. The Neural Network controller is designed for tuning the PI controller parameters for achieving the optimal voltage in the solar power connected to the UPQC system. Solar power used to improve the power for load side power system designed in network. The MATLAB simulation software is used for simulation of results. From the simulation results, the Total Harmonics Distortion value is reduced from 2.77% to 1.29% in the voltage side similarly 4.88percent to 2.01percent in the current side. Also the waveform of the supply system is improved.

We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control, and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. The example we develop in greater detail is with regards to the creation and dissemination of knowledge. That there is uncertainty in this process, is perhaps, not to be debated. We formulate one methodology to put a value or price on knowledge, using well accepted techniques from finance. We then apply this valuation to the decision problem of selecting papers for publication from an overall pool of submissions.\nOur initial analysis shows that one of the better solutions, we can accomplish in this space, might be described by the prescription, “Don’t Simply Optimize, Also Randomize; best described by the term - Randoptimization”. We specifically show that the best decision we can make, with regards to the selection of articles by journals (and in a subsequent paper, with respect to school admissions), requires us to formulate a cutoff point, or, a region of optimal performance and randomly select from within that region of better results. The policy implication (for all fields) is to randomly select papers, based on publication limitations (journal space, reviewer load etc.) from an overall pool of submissions, that have a single shred of knowledge (or one unique idea) and have the editors and reviewers coach the authors to ensure a better final outcome.