Party building and candidate selection : intraparty politics and promoting gender equality in Myanmar

This study examines why women remain underrepresented in Myanmar politics. It looks at structural and cultural aspects, revealing the dynamics of intraparty politics, especially the role and processes of candidate selection that affect both demand and supply of women candidates at local and national party levels. The findings are based on qualitative analysis of 72 in-depth interviews with members of nine political parties. Results suggest familial succession and family networks are common channels for recruitment. Additionally, those with backgrounds in social or religious groups, or as teachers are more likely to seek office.Knowledge for Democracy Myanma

A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye, single-frame (without signal averaging), and multi-frame (75x signal averaging) volume scans were obtained. A custom deep learning network was then designed and trained with 2,328 "clean B-scans" (multi-frame B-scans), and their corresponding "noisy B-scans" (clean B-scans + gaussian noise) to de-noise the single-frame B-scans. The performance of the de-noising algorithm was assessed qualitatively, and quantitatively on 1,552 B-scans using the signal to noise ratio (SNR), contrast to noise ratio (CNR), and mean structural similarity index metrics (MSSIM). Results: The proposed algorithm successfully denoised unseen single-frame OCT B-scans. The denoised B-scans were qualitatively similar to their corresponding multi-frame B-scans, with enhanced visibility of the ONH tissues. The mean SNR increased from $4.02 \pm 0.68$ dB (single-frame) to $8.14 \pm 1.03$ dB (denoised). For all the ONH tissues, the mean CNR increased from $3.50 \pm 0.56$ (single-frame) to $7.63 \pm 1.81$ (denoised). The MSSIM increased from $0.13 \pm 0.02$ (single frame) to $0.65 \pm 0.03$ (denoised) when compared with the corresponding multi-frame B-scans. Conclusions: Our deep learning algorithm can denoise a single-frame OCT B-scan of the ONH in under 20 ms, thus offering a framework to obtain superior quality OCT B-scans with reduced scanning times and minimal patient discomfort

Local Dexamethasone Administration Delays Allogeneic Islet Graft Rejection in the Anterior Chamber of the Eye of Non-Human Primates

Pancreatic islet transplantation into the anterior chamber of the eye (ACE) has been shown to improve glycemic control and metabolic parameters of diabetes in both murine and primate models. This novel transplantation site also allows the delivery of therapeutic agents, such as immunosuppressive drugs, locally to prevent islet graft rejection and circumvent unwanted systemic side effects. Local intravitreal administration of micronized dexamethasone implant was performed prior to allogeneic islet transplantation into the ACEs of non-human primates. Two study groups were observed namely allogeneic graft without immunosuppression (n = 4 eyes) and allogeneic graft with local immunosuppression (n = 8 eyes). Survival of islet grafts and dexamethasone concentration in the ACE were assessed in parallel for 24 weeks. Allogeneic islet grafts with local dexamethasone treatment showed significantly better survival than those with no immunosuppression (median survival time- 15 weeks vs 3 weeks, log-rank test p<0.0001). Around 73% of the grafts still survived at week 10 with a single local dexamethasone implant, where the control group showed no graft survival. Dexamethasone treated islet grafts revealed a good functional response to high glucose stimulation despite there was a transient suppression of insulin secretion from week 8 to 12. Our findings show a significant improvement of allografts survival in the ACE with local dexamethasone treatment. These results highlight the feasibility of local administration of pharmacological compounds in the ACE to improve islet graft survival and function. By eliminating the need for systemic immunosuppression, these findings may impact clinical islet transplantation in the treatment of diabetes, and the ACE may serve as a novel therapeutic islet transplantation site with high potential for local pharmacological intervention

Some Problems in Density Functional Theory

Though calculations based on density functional theory (DFT) are used remarkably widely in chemistry, physics, materials science, and biomolecular research and though the modern form of DFT has been studied for almost 60 years, some mathematical problems remain. For context, we provide an outline of the basic structure of DFT, then pose several questions regarding both its time-independent and time-dependent forms. Progress on any of these would aid in development of better approximate functionals and in interpretation

Comparing patient and healthcare worker experiences during a dengue outbreak in Singapore: understanding the patient journey and the introduction of a point-of-care test (POCT) toward better care delivery.

BACKGROUND: In the aftermath of an upsurge in the number of dengue cases in 2013 and 2014, the SD BIOLINE Dengue Duo rapid diagnostic Point-of-Care Test (POCT) kit was introduced in Tan Tock Seng Hospital, Singapore in June 2013. It is known that the success of POCT usage is contingent on its implementation within the health system. We evaluated health services delivery and the Dengue Duo rapid diagnostic test kit application in Singapore from healthcare workers' perspectives and patient experiences of dengue at surge times. METHODS: Focus group discussions were conducted with dengue patients, from before and after the POCT implementation period. In-depth interviews with semi-structured components with healthcare workers were carried out. A patient centred process mapping technique was used for evaluation, which mapped the patient's journey and was mirrored from the healthcare worker's perspective. RESULTS: Patients and healthcare workers confirmed a wide range of symptoms in adults, making it challenging to determine diagnosis. There were multiple routes to help seeking, and no 'typical patient journey', with patients either presenting directly to the hospital emergency department, or being referred there by a primary care provider. Patients groups diagnosed before and after POCT implementation expressed some differences between speed of diagnoses and attitudes of doctors, yet shared negative feelings about waiting times and a lack of communication and poor information delivery. However, the POCT did not in its current implementation do much to help waiting times. Healthcare workers expressed that public perceptions of dengue in recent years was a major factor in changing patient management, and that the POCT kit was helpful in improving the speed and accuracy of diagnoses. CONCLUSIONS: Health service delivery for dengue patients in Singapore was overall perceived to be of an acceptable clinical standard, which was enhanced by the introduction of the POCT. However, improvements can be focused on Adapting to outbreaks by reducing and rendering Waiting experiences more comfortable; Advancing education about symptom recognition, while also Recognising better communication strategies; and Expanding follow-up care options. This is presented as the Dengue AWARE model of care delivery

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method

DeshadowGAN: a deep learning approach to remove shadows from optical coherence tomography images

Purpose: To remove blood vessel shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device for both eyes of 13 subjects. A custom generative adversarial network (named DeshadowGAN) was designed and trained with 2328 B-scans in order to remove blood vessel shadows in unseen B-scans. Image quality was assessed qualitatively (for artifacts) and quantitatively using the intralayer contrast—a measure of shadow visibility ranging from 0 (shadow-free) to 1 (strong shadow). This was computed in the retinal nerve fiber layer (RNFL), the inner plexiform layer (IPL), the photoreceptor (PR) layer, and the retinal pigment epithelium (RPE) layer. The performance of DeshadowGAN was also compared with that of compensation, the standard for shadow removal. Results: DeshadowGAN decreased the intralayer contrast in all tissue layers. On average, the intralayer contrast decreased by 33.7 ± 6.81%, 28.8 ± 10.4%, 35.9 ± 13.0%, and 43.0 ± 19.5% for the RNFL, IPL, PR layer, and RPE layer, respectively, indicating successful shadow removal across all depths. Output images were also free from artifacts commonly observed with compensation. Conclusions: DeshadowGAN significantly corrected blood vessel shadows in OCT images of the ONH. Our algorithm may be considered as a preprocessing step to improve the performance of a wide range of algorithms including those currently being used for OCT segmentation, denoising, and classification. Translational Relevance: DeshadowGAN could be integrated to existing OCT devices to improve the diagnosis and prognosis of ocular pathologies