128 research outputs found
5 questions with Shan Aman-Rana, an MPA teaching fellow in Economics
We spoke to Shan Aman-Rana, winner of the LSE Class Teacher Award in 2015-2016 and who was also nominated by her students as LSE’s most inspirational teacher. Shan is a Teaching Fellow in the Department of Economics. Read on to find out her answers to our five questions
Discretion in a bureaucracy: evidence from Pakistan
Most bureaucracies today are rule-based. This is the result of a powerful intellectual tradition that argues that allowing discretion in decision making could lead to favoritism and collusion, with substantial costs to the organization. This thesis draws on newly digitised data from one public sector bureaucracy, the Pakistan Administrative Services (PAS) in Punjab, and presents novel evidence on discretionary promotions and lateral job allocations of junior bureaucrats by their seniors. The first set of results show that when senior bureaucrats have discretion to promote juniors, they do so meritocratically. By showing that promotions of juniors by their seniors is meritocratic, the result challenges conventional ideas on discretion in bureaucracies and opens the debate on rules vs. discretion. A decadal analysis, of cohorts from 1980-2010, shows that discretionary promotions became meritocratic starting in the 1990s. The thesis then investigates the reasons behind meritocratic promotions by seniors. It investigates two potential channels i.e. direct self-interest of the senior through discretion in the choice of their team and reputation concerns of seniors on referrals of juniors. Results show that direct self-interest of the senior has a more important role to play in meritocratic promotions. However, reputation concerns of seniors on referrals of juniors, might be a driver of the change towards meritocracy starting in the 1990s. The thesis next tests whether seniors use not just public information but also their private information on juniors meritocratically. Results show that seniors do use their private information to promote juniors meritocratically. Seniors decipher not just hidden lemons from the stars but also hidden gems from the bottom of the distribution. The last part of the thesis studies lateral allocations of juniors by their seniors. It draws on newly digitized administrative data on stated preferences of junior bureaucrats for location of tax collection jobs. Based on this data, the study creates four different types of job locations: non-competitive & non-preferred by juniors; non-competitive & preferred; competitive & nonpreferred and competitive & preferred. Results show that lateral allocations by seniors are meritocratic, so that high type are moved out of competitive & non-preferred locations, while low type are moved out of competitive ones that they prefer. However, an investigation into how different types of juniors perform in tax collection in these locations, shows that this might not be the most efficient allocation. Results show that in lateral allocations by seniors there is a tension between meritocracy and efficiency. Taken together these results have wider implications for how we think about the use of subjective judgment in organizations
Are initial allocation rules important for public service delivery and the allocation of talent within bureaucracies?
I investigate whether the seniority of the first set of colleagues affects a civil servant's tax collection and career. I find that seniority of first colleagues matters positively for tax collection and the allocation of talent within bureaucracies. A policy implication is to increase job rotation on entry
Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks
Histopathology tissue samples are widely available in two states:
paraffin-embedded unstained and non-paraffin-embedded stained whole slide RGB
images (WSRI). Hematoxylin and eosin stain (H&E) is one of the principal stains
in histology but suffers from several shortcomings related to tissue
preparation, staining protocols, slowness and human error. We report two novel
approaches for training machine learning models for the computational H&E
staining and destaining of prostate core biopsy RGB images. The staining model
uses a conditional generative adversarial network that learns hierarchical
non-linear mappings between whole slide RGB image (WSRI) pairs of prostate core
biopsy before and after H&E staining. The trained staining model can then
generate computationally H&E-stained prostate core WSRIs using previously
unseen non-stained biopsy images as input. The destaining model, by learning
mappings between an H&E stained WSRI and a non-stained WSRI of the same biopsy,
can computationally destain previously unseen H&E-stained images. Structural
and anatomical details of prostate tissue and colors, shapes, geometries,
locations of nuclei, stroma, vessels, glands and other cellular components were
generated by both models with structural similarity indices of 0.68 (staining)
and 0.84 (destaining). The proposed staining and destaining models can engender
computational H&E staining and destaining of WSRI biopsies without additional
equipment and devices.Comment: Accepted for publication at 2018 IEEE International Conference on
Machine Learning and Applications (ICMLA
Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic Patients
Sepsis is a life-threatening disease and one of the major causes of death in
hospitals. Imaging of microcirculatory dysfunction is a promising approach for
automated diagnosis of sepsis. We report a machine learning classifier capable
of distinguishing non-septic and septic images from dark field microcirculation
videos of patients. The classifier achieves an accuracy of 89.45%. The area
under the receiver operating characteristics of the classifier was 0.92, the
precision was 0.92 and the recall was 0.84. Codes representing the learned
feature space of trained classifier were visualized using t-SNE embedding and
were separable and distinguished between images from critically ill and
non-septic patients. Using an unsupervised convolutional autoencoder,
independent of the clinical diagnosis, we also report clustering of learned
features from a compressed representation associated with healthy images and
those with microcirculatory dysfunction. The feature space used by our trained
classifier to distinguish between images from septic and non-septic patients
has potential diagnostic application.Comment: Accepted for publication at 2018 IEEE International Conference on
Machine Learning and Applications (IEEE ICMLA
Open reduction and internal fixation of fracture femur in a patient with severe ankylosing spondylitis utilizing continuous caudal epidural anaesthesia
We describe a patient with severe ankylosing spondylitis scheduled to undergo open reduction and internal fixation. We emphasise on alternative anaesthetic management in view of non-availability of fiberoptic bronchoscope and unwillingness of patient to go to higher centre. Regional (continuous caudal epidural) anesthesia has been used as technique of choice
Vitamin D Deficiency in HCV Antiviral Treatment Responders versus Non-Responders
Background: Hepatitis C virus (HCV) is a major cause of chronic liver disease (CLD). Pakistan has a high burden of infectious diseases, including HCV. Its prevalence varies according to geographic regions in the country from about 2·4% to 6·5%. The objective of the study was to compare the frequency of vitamin D deficiency in responders and non-responders of antiviral treatment for chronic hepatitis C.Material and Methods: This comparative cross-sectional study was conducted in Hepatitis Clinic, Jinnah hospital, Lahore from 20th May to 20th November 2013. After ethical approval, participants were selected by using purposive non-probability sampling, 52 responder patients i.e. who were labeled negative for HCV RNA by PCR after 12 weeks of antiviral treatment and 52 non-responder patients were included in this study. Data was collected by using pretested structured questionnaire. Vitamin D3 levels were measured by ELISA and a cut-off value of below 30ng/ml was labeled as Vitamin D deficiency. SPSS version 21 was used to analyze data with p value less than 0.05 taken as statistically significant.Results: Out of 104 patients (mean age 35±8.1 years), 61.5% were males and 38.5 % were females. There was a significant difference in frequency of vitamin D deficiency in treatment responder group when compared to non-responders (p = 0.016). Mean level of vitamin D was 21.8±10.8ng/ml in responders whereas it was 15.6±7.5 in non-responders with a statistically significant difference (p = 0.001).Conclusion: This study concludes that there is a significant vitamin D deficiency among treatment non-responders as compared to treatment responders in patients with chronic hepatitis C
Linking of different ethnicities, races and religions to lipid profile patterns and hypolipidaemic drug usage patterns in coronary artery disease patients
Background: Coronary artery disease (CAD) is the consequence of atherosclerosis in which inadequate blood flow in the coronary arteries leads to myocardial necrosis. The impact of ethnic on CAD might be underestimated within Indian communities. There have never been any studies done associating them to lipid profile patterns in the Indian setup hence this study is the first of its kind to work towards attending the absence of data in this direction.The study aimed to evaluate the presence of ethnic differences in lipid profile patterns and hypolipidemic drug use in CAD patients.Methods: An 8-week cross-sectional prospective study was conducted in the cardiology OPD of a tertiary care hospital. Adult CAD patients prescribed with at least one hypolipidaemic drug, having their lipid profile values and willing to give informed consent were selected. The prescription pattern was noted, and the lipid profile values of the patients classified as per ATP III guidelines by NCEP. Atherogenic dyslipidaemia was considered when patients had triglyceride levels >150 mg/dl and HDL<40 mg/dl. The collected data was analyzed using SPSS. P value less than 0.05 was considered as statistically significant.Results: A total of 123 patients enrolled. Out of these, 115 were Hindus and among Hindus, most were Brahmins (34). The most prescribed hypolipidaemic drug was Rosuvastatin. Thirty six patients had high triglyceride levels out of which 35 were Hindus. Low HDL (<40 mg/dl) was present in 70 patients out of which 64 were Hindus. Atherogenic dyslipidaemia was seen in 44 patients. Majority of them belonged to the age group of 51-60 years (43.2%) and were Patels. Total cholesterol and LDL were high in 1 and 2 Jains respectively. Lipid values were higher in Tier-3 city patients.Conclusion: Hindu patients in this study showed a poorer lipid profile while among the castes, Jains and Patel’s fared poorly. It was seen that atherogenic dyslipidemia is on a rise in the Indian population
Promptformer: Prompted Conformer Transducer for ASR
Context cues carry information which can improve multi-turn interactions in
automatic speech recognition (ASR) systems. In this paper, we introduce a novel
mechanism inspired by hyper-prompting to fuse textual context with acoustic
representations in the attention mechanism. Results on a test set with
multi-turn interactions show that our method achieves 5.9% relative word error
rate reduction (rWERR) over a strong baseline. We show that our method does not
degrade in the absence of context and leads to improvements even if the model
is trained without context. We further show that leveraging a pre-trained
sentence-piece model for context embedding generation can outperform an
external BERT model
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