scholarly journals Morgellons: a novel dermatological perspective as the multisystem infective disease borreliosis

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 118 ◽  
Author(s):  
Peter Mayne ◽  
John S English ◽  
Edward J Kilbane ◽  
Jennie M Burke ◽  
Marianne J Middelveen ◽  
...  
Keyword(s):  
Medical Profession ◽  
Scientific Data ◽  
The Novel ◽  
Dermatitis Artefacta ◽  
Disease Complex ◽  
System Disease ◽  
Co Morbidity ◽  
Infective Disease ◽  
Concurrent Case ◽  
Novel Model

Morgellons disease (MD) is a term that has been used in the last decade to describe filaments that can be found in human epidermis. It is the subject of considerable debate within the medical profession and is often labeled as delusions of parasitosis or dermatitis artefacta. This view is challenged by recent published scientific data put forward between 2011-2013 identifying the filaments found in MD as keratin and collagen based and furthermore associated with spirochetal infection. The novel model of the dermopathy put forward by those authors is further described and, in particular, presented as a dermal manifestation of the multi-system disease complex borreliosis otherwise called Lyme disease. A differential diagnosis is drawn from a dermatological perspective. The requirements for a diagnosis of delusional disorder from a psychiatric perspective are clarified and the psychological or psychiatric co-morbidity that can be found with MD cases is presented. A concurrent case incidence is also included. Management of the multisytem disease complex is discussed both in general and from a dermatological perspective. Finally replacement of the term ‘Morgellons’ by ‘borrelial dermatitis’ is proposed within the profession.

A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy

2021 ◽  
Vol 40 (5) ◽  
pp. 10043-10061
Author(s):  
Xiaoping Shi ◽  
Shiqi Zou ◽  
Shenmin Song ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
The Novel ◽  
Genetic Operators ◽  
Multi Objective ◽  
Target Assignment ◽  
Solution Selection ◽  
Battlefield Environment ◽  
Sparse Problems ◽  
Novel Model ◽  
Error Parameter

 The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.

A novel fractional discrete grey model with an adaptive structure and its application in electricity consumption prediction

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yitong Liu ◽  
Yang Yang ◽  
Dingyu Xue ◽  
Feng Pan
Keyword(s):  
Fractional Order ◽  
Electricity Consumption ◽  
Grey Model ◽  
The Novel ◽  
Raw Data ◽  
Content Type ◽  
Power Load ◽  
Grey Models ◽  
Novel Model ◽  
Consumption Prediction

PurposeElectricity consumption prediction has been an important topic for its significant impact on electric policies. Due to various uncertain factors, the growth trends of electricity consumption in different cases are variable. However, the traditional grey model is based on a fixed structure which sometimes cannot match the trend of raw data. Consequently, the predictive accuracy is variable as cases change. To improve the model's adaptability and forecasting ability, a novel fractional discrete grey model with variable structure is proposed in this paper.Design/methodology/approachThe novel model can be regarded as a homogenous or non-homogenous exponent predicting model by changing the structure. And it selects the appropriate structure depending on the characteristics of raw data. The introduction of fractional accumulation enhances the predicting ability of the novel model. And the relative fractional order r is calculated by the numerical iterative algorithm which is simple but effective.FindingsTwo cases of power load and electricity consumption in Jiangsu and Fujian are applied to assess the predicting accuracy of the novel grey model. Four widely-used grey models, three classical statistical models and the multi-layer artificial neural network model are taken into comparison. The results demonstrate that the novel grey model performs well in all cases, and is superior to the comparative eight models.Originality/valueA fractional-order discrete grey model with an adaptable structure is proposed to solve the conflict between traditional grey models' fixed structures and variable development trends of raw data. In applications, the novel model has satisfied adaptability and predicting accuracy.

Assessing Bypassed Hydrocarbons

2021 ◽  
Author(s):  
Stanley Oifoghe ◽  
Nora Alarcon ◽  
Lucrecia Grigoletto
Keyword(s):  
Continental Shelf ◽  
Reservoir Characterization ◽  
Gamma Ray ◽  
West African ◽  
The Novel ◽  
The West ◽  
Present Case Study ◽  
Novel Model

Abstract Hydrocarbons are bypassed in known fields. This is due to reservoir heterogeneities, complex lithology, and limitations of existing technology. This paper seeks to identify the scenarios of bypassed hydrocarbons, and to highlight how advances in reservoir characterization techniques have improved assessment of bypassed hydrocarbons. The present case study is an evaluation well drilled on the continental shelf, off the West African Coastline. The targeted thin-bedded reservoir sands are of Cenomanian age. Some technologies for assessing bypassed hydrocarbon include Gamma Ray Spectralog and Thin Bed Analysis. NMR is important for accurate reservoir characterization of thinly bedded reservoirs. The measured NMR porosity was 15pu, which is 42% of the actual porosity. Using the measured values gave a permeability of 5.3mD as against the actual permeability of 234mD. The novel model presented in this paper increased the porosity by 58% and the permeability by 4315%.

scholarly journals CONTROL NOVEL MODEL OF KNEE CPM DEVICE

2009 ◽  
Vol 12 (4) ◽  
pp. 18-29
Author(s):  
Thanh Diep Cong Tu
Keyword(s):  
Weight Ratio ◽  
Artificial Muscle ◽  
Network Control ◽  
Continuous Passive Motion ◽  
The Novel ◽  
Highly Nonlinear ◽  
Cord Injury ◽  
And Control ◽  
Novel Model ◽  
Interesting Alternative

In recent years, CPM - Continuous Passive Motion has been proved to be one of the most effective therapeutic methods for patients who have problems with motion such as spinal cord injury, ankle and knee injury, parkinson and so on. Many commercial CPM devices are found in market but all of them use motors as the main actuators. The lack of human compliance of electric actuators, which are commonly used in these machines, makes them potentially harmful to patients. An interesting alternative, to electric actuators for medical purposes, particularly promising for rehabilitation, is a pneumatic artificial muscle (PAM) actuator because of its high power/weight ratio and compliance properties. However, the highly nonlinear and hysteresis of PAM make it the challenging for design and control. In this study, a PID compensation using neural network control is studied to improve the control performance of the novel model of Knee CPM device.

The Novel Model of Building and Energy Engineering with New Building Materials Based on IPv6 Technology

2013 ◽  
Vol 738 ◽  
pp. 141-144
Author(s):  
Guo Fang Kuang ◽  
Zhao Feng Sun
Keyword(s):  
Building Materials ◽  
High Efficiency ◽  
New Technology ◽  
The Novel ◽  
Ip Address ◽  
Construction Engineering ◽  
Encryption And Authentication ◽  
Effective Use ◽  
Novel Model ◽  
Energy Engineering

New building materials variety and yield is developing with hitherto unknown speed, construction engineering development if the effective use of new building materials will be excellent performance of new technology. Novel building materials can significantly reduce the weight of buildings, to promote the light construction structure created the conditions. IPv6 is not only a good solution to the problem of the lack of IP address, but also due to the introduction of encryption and authentication mechanisms to make it a better improvement in the network. The paper presents the novel model of building and energy engineering based on IPv6 technology. Experimental results show that the proposed method has high efficiency.

An Improved Quick Artificial Bee Colony Algorithm for Portfolio Selection

2019 ◽  
Vol 18 (01) ◽  
pp. 1950007
Author(s):  
Dit Suthiwong ◽  
Maleerat Sodanil ◽  
Gerald Quirchmayr
Keyword(s):  
Artificial Bee Colony ◽  
Stock Exchange ◽  
Continuous Model ◽  
The Novel ◽  
Stock Selection ◽  
Bee Colony ◽  
De Algorithm ◽  
Using Data ◽  
Novel Model ◽  
Model Robustness

Computation Intelligence has inspired many researchers to develop the capability of computers to learn and solve a complex task in real-world problems. In this work, we propose an Artificial Bee Colony (ABC) to deal with the Stock Selection problem. We apply a Sigmoid-based Discrete-Continuous model with ABC to select appropriate features for stock scoring. The empirical study tests the performance of ABC compared with Genetic Algorithm (GA) and Differential Evolution (DE) algorithm by using data from the Stock Exchange Thailand. The empirical results show that the novel model stock selection significantly outperforms in terms of both investment return, diversity and model robustness.

Off-Label Prescription Advertising, the FDA and the First Amendment: A Study in the Values of Commercial Speech Protection

2011 ◽  
Vol 37 (2-3) ◽  
pp. 315-357 ◽  
Author(s):  
Coleen Klasmeier ◽  
Martin H. Redish
Keyword(s):  
Prescription Drugs ◽  
Medical Profession ◽  
Scientific Data ◽  
Efficacy And Safety ◽  
Medical Purpose ◽  
Off Label Use ◽  
Off Label ◽  
Commercial Speech ◽  
Hand Off ◽  
The One

In order to protect the nation from harmful or worthless drugs and devices, the Food and Drug Administration (FDA or the Agency) is legislatively authorized to restrict the sale of prescription drugs or medical devices to those whose efficacy and safety have been reviewed and approved by the Agency. Drugs and devices are approved for a specific medical purpose. In numerous instances, however, the medical profession has discovered that treatments approved for one purpose may also serve other valuable medical purposes. Indeed, on a number of occasions such “off-label” treatments have proven to be essential to the successful treatment of some very serious illnesses.In these off-label situations, the FDA is faced with a dilemma. On the one hand, off-label use of prescription drug and devices gives rise to a series of major problems for the FDA. While the drug and devices in question have been vetted and approved by the FDA for their designated purpose, at no point has the FDA reviewed the supporting scientific data to determine efficacy for the off-label purpose.

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