Features for detection of Parkinson's disease tremor from local field potentials of the subthalamic nucleus

Deep Brain Stimulation (DBS) is a treatment routinely used to alleviate the symptoms of Parkinson's disease (PD). In this type of treatment, electrical pulses are applied through electrodes implanted into the basal ganglia of the patient. As the symptoms are not permanent in most patients, it is desirable to develop an on-demand stimulator, applying pulses only when onset of the symptoms is detected. This study evaluates a feature set created for the detection of tremor - a cardinal symptom of PD. The designed feature set was based on standard signal features and researched properties of the electrical signals recorded from subthalamic nucleus (STN) within the basal ganglia, which together included temporal, spectral, statistical, autocorrelation and fractal properties. The most characterized tremor related features were selected using statistical testing and backward algorithms then used for classification on unseen patient signals. The spectral features were among the most efficient at detecting tremor, notably spectral bands 3.5-5.5 Hz and 0-1 Hz proved to be highly significant. The classification results for determination of tremor achieved 94% sensitivity with specificity equaling one.

On computational algorithms for pole assignment

A number of computationally reliable direct methods for pole assignment by feedback have recently been developed. These direct procedures do not necessarily produce robust solutions to the problem, however, in the sense that the assigned poles are insensitive to perturbalions in the closed-loop system. This difficulty is illustrated here with results from a recent algorithm presented in this TRANSACTIONS and its causes are examined. A measure of robustness is described, and techniques for testing and improving robustness are indicated.

Modelling of Johne's disease control options in beef cattle: a decision support approach

Johne's disease in cattle is a contagious wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's infection is characterised by a long subclinical phase and can therefore go undetected for long periods of time during which substantial production losses can occur. The protracted nature of Johne's infection therefore presents a challenge for both veterinarians and farmers when discussing control options due to a paucity of information and limited test performance when screening for the disease. The objectives were to model Johne's control decisions in suckler beef cattle using a decision support approach, thus implying equal focus on ‘end user’ (veterinarian) participation whilst still focusing on the technical disease modelling aspects during the decision support model development. The model shows how Johne's disease is likely to affect a herd over time both in terms of physical and financial impacts. In addition, the model simulates the effect on production from two different Johne's control strategies; herd management measures and test and cull measures. The article also provides and discusses results from a sensitivity analysis to assess the effects on production from improving the currently available test performance. Output from running the model shows that a combination of management improvements to reduce routes of infection and testing and culling to remove infected and infectious animals is likely to be the least-cost control strategy.

Brill Greek, Adobe Arno Pro, Adobe Text/Brevier Greek typefaces

Typeface design: a series of collaborative projects commissioned by Adobe, Inc. and Brill to develop extensive polytonic Greek typefaces. The two Adobe typefaces can be seen as extension of previous research for the Garamond Premier Pro family (2005), and concludes a research theme started in 1998 with work for Adobe’s Minion Pro Greek. These typefaces together define the state of the art for text-intensive Greek typesetting for wide character set texts (from classical texts, to poetry, to essays, to prose). They serve both as exemplar for other developers, and as vehicles for developing the potential of Greek text typography, for example with the parallel inclusion of monotonic and polytonic characters, detailed localised punctuation options, fluid handling of case-conversion issues, and innovative options such as accented small caps (originally requested by bibliographers, and subsequently rolled out to a general user base). The Brill typeface (for the established academic publisher) has an exceptionally wide character set to cover several academic disciplines, and is intended to differentiate sufficiently from its partner Latin typeface, while maintaining a clear texture in both offset and low-resolution print-on-demand reproduction. This work involved substantial amounts of testing and modifying the design, especially of diacritics, to maintain clarity the readability of unfamiliar words. All together these typefaces form a study in how Greek typesetting meets contemporary typographic requirements, while resonating with historically accurate styles, where these are present. Significant research in printing archives helped to identify appropriate styles, as well as originate variants that are coherent stylistically, even when historical equivalents were absent.

An insight into the public acceptance of nutrigenomic-based personalised nutrition.

It is predicted that non-communicable diseases will account for over 73 % of global mortality in 2020. Given that the majority of these deaths occur in developed countries such as the UK, and that up to 80 % of chronic disease could be prevented through improvements in diet and lifestyle, it is imperative that dietary guidelines and disease prevention strategies are reviewed in order to improve their efficacy. Since the completion of the human genome project our understanding of complex interactions between environmental factors such as diet and genes has progressed considerably, as has the potential to individualise diets using dietary, phenotypic and genotypic data. Thus, there is an ambition for dietary interventions to move away from population-based guidance towards 'personalised nutrition'. The present paper reviews current evidence for the public acceptance of genetic testing and personalised nutrition in disease prevention. Health and clear consumer benefits have been identified as key motivators in the uptake of genetic testing, with individuals reporting personal experience of disease, such as those with specific symptoms, being more willing to undergo genetic testing for the purpose of personalised nutrition. This greater perceived susceptibility to disease may also improve motivation to change behaviour which is a key barrier in the success of any nutrition intervention. Several consumer concerns have been identified in the literature which should be addressed before the introduction of a nutrigenomic-based personalised nutrition service. Future research should focus on the efficacy and implementation of nutrigenomic-based personalised nutrition.

Problem-based learning approaches in meteorology

Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a current field course module, this project describes the implementation of two test Problem-Based Learning activities and testing and improvement using several different and complementary means of evaluation. By the end of a 2-year program of design, implementation, testing, and reflection and re-evaluation, two robust, engaging activities have been developed that provide an enhanced and diverse learning environment in the field course. The results suggest that Problem-Based Learning techniques would be a useful addition to the meteorology curriculum and suggestions for courses and activities that may benefit from this approach are included in the conclusions.

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

Developing a mobile visualization environment for construction applications

There is a renewed interest in immersive visualization to navigate digital data-sets associated with large building and infrastructure projects. Following work with a fully immersive visualization facility at the University, this paper details the development of a complementary mobile visualization environment. It articulates progress on the requirements for this facility; the overall design of hardware and software; and the laboratory testing and planning for user pilots in construction applications. Like our fixed facility, this new light-weight mobile solution enables a group of users to navigate a 3D model at a 1:1 scale and to work collaboratively with structured asset information. However it offers greater flexibility as two users can assemble and start using it at a new location within an hour. The solution has been developed and tested in a laboratory and will be piloted in engineering design review and stakeholder engagement applications on a major construction project.

Multiplexed femtomolar quantitation of human cytokines in a fluoropolymer microcapillary film

Sensitive quantitation of multiple cytokines can provide important diagnostic information during infection, inflammation and immunopathology. In this study sensitive immunoassay detection of human cytokines IL-1β, IL-6, IL-12p70 and TNFα is shown for singleplex and multiplex formats using a novel miniaturized ELISA platform. The platform uses a disposable plastic multi-syringe aspirator (MSA) integrating 8 disposable fluoropolymer microfluidic test strips, each containing an array of ten 200 mean i.d. microcapillaries coated with a set of monoclonal antibodies. Each MSA device thus performs 10 tests on 8 samples, delivering 80 measurements. Unprecedented levels of sensitivity were obtained with the novel fluoropolymer microfluidic material and simple colorimetric detection in a flatbed scanner. The limit of detection for singleplex detection ranged from 2.0 to 15.0 pg/ml, i.e. 35 and 713 femtomolar for singleplex cytokine detection, and the intra- and inter-assay coefficient of variation (CV) remained within 10%. In addition, a triplex immunoassay was developed for measuring IL-1β, IL-12p70 and TNFα simultaneously from a given sample in the pg/ml range. These assays permit high sensitivity measurement with rapid <15 min assay or detection from undiluted blood serum. The portability, speed and low-cost of this system are highly suited to point-of-care testing and field diagnostics applications.

Immobilized Kidney 28-kDa Endostatin- Related (KES28kDa) Fragment Promotes Endothelial Cell Survival

Background/Objective: Renal ischemia-hypoxia is a leading cause of acute kidney injury (AKI). Ischemia causes extracellular matrix breakdown of the tubular basement membrane. Endostatin (ES) is the C-terminal fragment of collagen XVIII generated by proteolytic cleavage. Recent studies have demonstrated that ES expression is upregulated in ischemic kidneys. The present study aimed to characterize ES from ischemic kidneys. Methods: Ischemic renal failure was induced via 45 min of occlusion of the left renal artery and vein. After the ischemic period, blood was collected. Kidneys were harvested and used for immunohistochemical testing and protein extraction. Three-step purification was used. Soluble and immobilized purified ES were tested in cell viability and adhesion assays. Results: The soluble KES28kDa inhibited endothelial cell proliferation: 25 versus 12.5 mu g (p < 0.05); 12.5 versus 3.15 mu g (p < 0.05). Immobilization of KES28kDa supports endothelial cell survival over the control p = 0.021). Human umbilical vein endothelial cells plated on immobilized KES28kDa showed an increase in membrane ruffles and stress fibers. Conclusion: These data demonstrate the local synthesis of a 28-kDa ES-related fragment following AKI and suggest its role in endothelium survival. Copyright (C) 2010 S. Karger AG, Basel

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.

Inference for a skew extension of the Grubbs model

In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.

Individuell utprovning av inkontinenshjälpmedel i kommunala särskilda boenden

The purpose of this study was to examine the extent to which incontinence aids, used in local authority/municipal nursing homes, were adapted to the resident’s urine-leakage volume and to find out how nurses perceived the current situation concerning individual testing of incontinence aids in municipal nursing homes. The study method was a quantitative empirical study and was carried out in two phases. The first phase was a weighing test, carried out in three nursing homes, whereby the incontinence aids used by 25 residents during a 48 hour period were weighed. The second phase was the completion of a questionnaire by the municipal nurses working in the same local authority. The questionnaire covered: the division of responsibilities; routines for testing incontinence aids, and the level of knowledge concerning individual incontinence aid testing. Only 22 % of the pads used during the observation were properly adapted to the patients’ urinary leakage volume, while 76 % of incontinence aids were larger than necessary in relation to the real volume of urinary leakage. The municipal nurses, who have a key role and formal responsibility for individual incontinence aid testing, considered that there was insufficient knowledge within the organisation concerning individual incontinence aid testing, and that the division of responsibilities in this area was unclear. There were great variations relating to the extent of the nurses’ involvement in individual incontinence aid testing, and the nurses stated that increased involvement in individual incontinence aid testing was dependent on more time being made available for this task. Only a minority of the nurses thought that the requisitioning of incontinence aids was preceded by individual testing of the incontinence pads within the organisation. The majority of nurses considered that this was not the case or were unsure of the situation.

Design/Evaluation of A Methodology For Performance Optimization Of Indexable Carbide Inserts

In this project, two broad facets in the design of a methodology for performance optimization of indexable carbide inserts were examined. They were physical destructive testing and software simulation.For the physical testing, statistical research techniques were used for the design of the methodology. A five step method which began with Problem definition, through System identification, Statistical model formation, Data collection and Statistical analyses and results was indepthly elaborated upon. Set-up and execution of an experiment with a compression machine together with roadblocks and possible solution to curb road blocks to quality data collection were examined. 2k factorial design was illustrated and recommended for process improvement. Instances of first-order and second-order response surface analyses were encountered. In the case of curvature, test for curvature significance with center point analysis was recommended. Process optimization with method of steepest ascent and central composite design or process robustness studies of response surface analyses were also recommended.For the simulation test, AdvantEdge program was identified as the most used software for tool development. Challenges to the efficient application of this software were identified and possible solutions proposed. In conclusion, software simulation and physical testing were recommended to meet the objective of the project.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.