Multivariate Analysis of Finnish Dialect Data An Overview of Lexical Variation

During the process of writing a comprehensive dictionary ofFinnish dialects, a large set of maps describing the regionaldistribution of the dialect words have been compiled in electronicform. In this article, we set out to analyse this corpus ofdata in order to gain new insight on the variation of Finnishdialects. We use a wide range of multivariate data analysismethods, including principal components analysis, independentcomponents analysis, clustering, and multidimensional scaling.We explain how to preprocess the data to overcome the problemof uneven sampling caused by the way the data has been collected.We discuss the results obtained by these methods and comparethem to the traditional view of Finnish dialect groups.     

Analysis of EMG and acceleration signals for quantifying the effects of deep brain stimulation in Parkinson's disease

Deep brain stimulation (DBS) is effective in reducing motor symptoms in Parkinson's disease (PD). However, objective methods for quantifying its efficacy are lacking. We present a principal component (PC)-based tracking method for quantifying the effects of DBS in PD by using electromyography (EMG) and acceleration measurements. Ten parameters capturing PD characteristic signal features were initially extracted from isometric EMG and acceleration recordings. Using a PC approach, the original parameters were transformed into a smaller number of PCs. Finally, the effects of DBS were quantified by examining the PCs in a low-dimensional feature space. The EMG and acceleration data from 13 PD patients with DBS ON and OFF, and 13 healthy age-matched controls were used for analysis. Clinical evaluation of patients showed that their motor symptoms were effectively reduced with DBS. The analysis results showed that the signal characteristics of 12 patients were more similar to those of the healthy controls with DBS ON than with DBS OFF. These observations indicate that the PC-based tracking method can be used to objectively quantify the effects of DBS on the neuromuscular function of PD patients. Further studies are suggested to estimate the clinical sensitivity of the method to different types of PD.     

Effect of 2-propanol and water contents on the crystallization and particle size of titanium dioxide synthesized at low-temperature

Two series of titanium dioxide, TiO₂, powder were prepared at a temperature of 50 °C without any catalyst. The effects of 2-propanol and water contents on the formation of crystalline powder mixture of anatase and brookite were systematically studied. The characteristics of produced powder were determined by employing X-ray diffraction, transmission electron microscopy, nitrogen adsorption test and Fourier transform infrared spectroscopy.     

Scale-up of manufacturing of printed enzyme electrodes for enzymatic power source applications

Production of printable enzymatic power sources was scaled up from laboratory to roll-to-roll (R2R) pilot production. The anode and cathode enzymes were glucose oxidase (GOx) and laccase, respectively. The best laboratory-scale cells had a maximum power and energy density of 1.4 ± 0.1 µW cm^?2 and 5.5 ± 0.2 µWh cm^?2, respectively. These values are 5 and 28 times higher compared to our previously published values. The R2R-produced cells had a maximum power and energy density of 0.40 ± 0.03 µW cm^?2 and 0.6 ± 0.1 µWh cm^?2, respectively. This is 11 % of the best laboratory manufactured cells. It is suspected that the decrease in electrochemical performance originates from the lower mediator amount and higher drying temperature than that of the laboratory produced cells. However, the trials conducted in this work showed that printed enzymatic active layers can be fabricated and dried with a rotary screen-printing machine in R2R process. Hence, fully printed GOx//laccase power sources could be produced from R2R on a large scale for printed electronics applications.     

Real‐Time Label‐Free Monitoring of Nanoparticle Cell Uptake

The surface plasmon resonance technique in combination with whole cell sensing is used for the first time for real‐time label‐free monitoring of nanoparticle cell uptake. The uptake kinetics of several types of nanoparticles relevant to drug delivery applications into HeLa cells is determined. The cell uptake of the nanoparticles is confirmed by confocal microscopy. The cell uptake of silica nanoparticles and polyethylenimine–plasmid DNA polyplexes is studied as a function of temperature, and the uptake energies are determined by Arrhenius plots. The phase transition temperature of the HeLa cell membrane is detected when monitoring cell uptake of silica nanoparticles at different temperatures. The HeLa cell uptake of the mesoporous silica nanoparticles is energy‐independent at temperatures slightly higher than the phase transition temperature of the HeLa cell membrane, while the uptake of polyethylenimine–DNA polyplexes is energy‐dependent and linear as a function of temperature with an activation energy of Ea = 62 ± 7 kJ mol^?1 = 15 ± 2 kcal mol^?1. The HeLa cell uptake of red blood cell derived extracellular vesicles is also studied as a function of the extracellular vesicle concentration. The results show a concentration dependent behavior reaching a saturation level of the extracellular vesicle uptake by HeLa cells.     

Unsupervised segmentation and quantification of anatomical knee features: data from the Osteoarthritis Initiative

This paper presents a fully automated method for segmenting articular knee cartilage and bone from in vivo 3-D dual echo steady state images. The magnetic resonance imaging (MRI) datasets were obtained from the Osteoarthritis Initiative (OAI) pilot study and include longitudinal images from controls and subjects with knee osteoarthritis (OA) scanned twice at each visit (baseline, 24 month). Initially, human experts segmented six MRI series. Five of the six resultant sets served as reference atlases for a multiatlas segmentation algorithm. The methodology created precise knee segmentations that were used to extract articular cartilage volume, surface area, and thickness as well as subchondral bone plate curvature. Comparison to manual segmentation showed Dice similarity coefficient (DSC) of 0.88 and 0.84 for the femoral and tibial cartilage. In OA subjects, thickness measurements showed test-retest precision ranging from 0.014 mm (0.6%) at the femur to 0.038 mm (1.6%) at the femoral trochlea. In the same population, the curvature test-retest precision ranged from 0.0005 mm(-1) (3.6%) at the femur to 0.0026 mm(-1) (11.7%) at the medial tibia. Thickness longitudinal changes showed OA Pearson correlation coefficient of 0.94 for the femur. In conclusion, the fully automated segmentation methodology produces reproducible cartilage volume, thickness, and shape measurements valuable for the study of OA progression.     

A House is not a Home: The Housing Experiences of African and Caribbean Mothers Living with HIV

HIV-positive mothers living in Toronto, ON, face myriad economic and social challenges that put them at risk for housing instability and homelessness. These challenges are exacerbated for mothers from African and Caribbean communities as they navigate a web of shelter, housing, health care and social care systems that do not adequately address their social positioning as HIV-positive and racialized mothers. To date, there is a dearth of research that has taken a cultural, ethnoracial and gendered lens to explore these issues, and consequently, little is known about their experiences of housing instability as it intersects with issues related to motherhood, poverty, sexism, racism, immigration status and HIV-related stigma and discrimination. This paper presents findings from the HIV, Housing and Families community-based research study and highlights the unique and complex housing issues African and Caribbean mothers facing by living with HIV in Toronto. Implications for policy and practice are also discussed.