Under the Iron Thumb: Forced Labor in Myanmar

The fight for human rights in Myanmar goes back to its independence in 1948. The Myanmar military (tatmadaw) has engaged in shocking violations of almost every right in the Universal Declaration of Human Rights. The issue of forced labor, however, is of particular concern. Forced labor is employed primarily in development projects, agricultural enterprises, and the military. It is used to impose collective punishment on civilians, to build highly profitable development that strengthens military rule, and to allow the military access and logistical support in the most remote regions of insurgent-occupied territories. Forced labor is a central means by which the tatmadaw attempts to control all facets of Burmese society

Opportunities and challenges associated with development of wood biomass energy production in Louisiana

Wood residue produced by forest products industry has been recognized as a potential fuel that can generate energy to run the industry. A survey was done among forest products industry to get a general idea about energy produced from woody biomass created from forest industry in Louisiana, USA. The industry was classified into primary and secondary forest products industry. The study provided information regarding utilization and wastage of wood residue. Survey response rate was 25 percent. It addressed problems faced by wood residue energy development and came up with solution to solve them. When survey results were compared to previous survey, done in 1994, it clearly showed an increase in production and utilization of wood residue. One more thing worth noting was the reduction in number of secondary forest products industry. The study estimated a production 15,076,937 tons of wood residue by the forest product industry. Results showed that majority of wood being produced in the industry went un-utilized. In primary forest products industry most respondent used their residue in energy production. But in secondary sector, residue was not utilized. Residue of secondary forest product industry such as wood chips and shavings were used in various sectors. Some of them were bedding for horse farms, mulching, for erosion control in canals and as fuel in furnaces. But nearly ninety percent of residue went to landfills. By contrast, there were industries which had a great demand for wood residue as a fuel. We discovered a need for better communication between producers and utilizers. This study also produced an interactive online directory, from which industry needing wood residue can contact producers. One major reason for non-utilization of wood residue in secondary sector was due to comparatively small production that was distributed widely across the state. Cost of transportation restricted them from being a viable option. Lack of information about producers and consumers also played a role

Explaining Coordination Success and Failures in Disaster

학위논문 (석사) -- 서울대학교 대학원 : 행정대학원 글로벌행정전공, 2020. 8. 고길곤.Nepal is highly vulnerable to number of disasters because of uneven topography, fragile geophysical structure, high angle of slopes, complex geology, variable climatic conditions, unplanned urbanization and settlement. The government has emphasized multi agency approach in disaster management. Therefore, the capacity to cope with the adverse effects of a disaster largely depends upon the preparedness and coordination among multiple agency. The main objectives of the paper were to analyze disaster management system in Nepal and factors affecting coordination in disaster. This study has pursued to understand current status of coordination among different actors and existing barriers in coordination. Furthermore, it also focused on existing problems in disaster management system and ways to improve disaster management in Nepal. This study used Qualitative descriptive design to answer the research questions. The narrative literature was reviewed from published journal, article, laws, regulations, polices, action plan and institutional mechanism to identify existing disaster management system in Nepal. Apart from this, semi structured interviews were conducted to gather depth information with key persons from different agency involved in disaster management. The study revealed that coordination among different actors during response phase is good however, coordination in risk reduction and post disaster is in shadow. There is need of national platform and disaster authority to carry out the tasks of coordination effectively. National policy regarding relief distribution is indispensable for standardization in relief distribution across the country. It is concluded that government should focus on disaster risk mapping, replacing traditional live saving equipment, and advancing disaster management information system to minimize loss of lives and property from disasters.네팔은 고르지 못한 지형, 취약한 지반, 높은 경사각, 복잡한 지질, 다양한 기후 조건, 계획되지 않은 도시화 및 정착 때문에 많은 재난에 매우 취약하다. 정부는 여러 기관에게 재난관리에 대한 접근을 강조해 왔다. 그러므로, 재해의 역효과에 대처하는 능력은 주로 다양한 기관들 사이의 준비와 조정에 달려 있다. 본 논문의 주요 목적은 네팔의 재난 관리 시스템과 재난의 조정에 영향을 미치는 요소들을 분석하는 것이다. 본 연구는 서로 다른 행위자들과 조정에서 존재하는 장벽들 사이의 조정 현황을 이해하기 위해 추구하였고, 또한 네팔의 재난 관리 시스템의 현존하는 문제와 재난 관리 개선 방법에 초점을 맞췄다. 본 연구는 이러한 연구의 질문에 답하기 위해 질적 연구를 사용하였다. 본 연구의 방식은 네팔의 기존 재난관리 시스템을 확인하기 위한 간행물, 기사, 법률, 규정, 정책, 행동계획 및 제도적 메커니즘에서 검토되었다. 이와는 별도로, 재해 관리에 관여하는 여러 기관의 주요 인사들과 심층 정보를 수집하기 위해 반 구조적 인터뷰를 실시하였다. 본 연구는 반응 단계가 좋을 때, 서로 다른 행위자들 간의 조율이 좋다는 것을 보여주었다. 그러나 리스크 감소와 재해 후의 조정은 그늘에 가려져 있다고 할 수 있다. 조정의 과제를 효과적으로 수행하기 위해서는 국가 플랫폼과 재난 당국이 필요하다. 구호물자에 관한 국가 정책은 전국의 구호물자 표준화를 위해 마찬가지로 필수적이다. 따라서 재해로 인한 인명 및 재산의 손실을 최소화하기 위해 재해 위험 지도화, 기존 생활 구조 장비 교체, 재해 관리 정보 시스템 고도화에 주력해야 한다고 본 논문은 결론을 내렸다.Chapter one: Introduction 1 1.1 Background 1 1.2 Statement of the problem 2 1.3 Objectives of the study 3 1.4 Scope of the study 3 1.5 Research question 4 Chapter Two: Theoretical Background and Literature review 5 2.1 Disaster Management 5 2.2 Factors affecting Disaster Management 7 2.2.1 Political Factors 8 2.2.2 Technological Factor 8 2.2.3 Social Factor 9 2.2.4 Economic Factor 9 2.2.5 Legal Factors 10 2.2.6 Managerial Factor 10 2.3 Disaster Management System in Nepal 12 2.3.1 Legal and Regulatory Framework 13 2.3.2 Policies and Action Plan 16 2.3.3 Disaster Risk Management Institutions 17 2.4 Importance of coordination in Disaster Management 21 2.5 Factors affecting Disaster Coordination 24 2.5.1 Motivation 24 2.5.2 Communication 25 2.5.3 Trust 26 2.5.4 Institution 27 2.5.5 Information Management 28 Chapter Three: Research Design and Methodology 30 3.1. Research Design 30 3.2 Conceptual Framework 30 3.3 Data collection 33 3.4 Sampling Frame and Technique 33 3.5 overview of Interview 34 Chapter Four: Findings and Discussion 36 4.1 Key points from the interview 36 4.1.1 NON-Government organizations 36 4.1.2 Nepal Army 39 4.1.3 Nepal Police 40 4.1.4 Armed police force: 42 4.1.5 Ministry of Home Affairs 43 4.2 Finding Summary 47 Research question 1: 47 Research question 2: 48 Research question 3: 50 Research question 4: 51 Chapter Five: Conclusion and Recommendation 54 5.1 Conclusion 54 A. Establishment of Disaster Authority 54 B. Formulation of Relief Distribution Policy 55 C. Developing advanced disaster management information system 55 D. Adequate resources for Disaster management 55 E. Disaster Risk Mapping 56 5.2 Recommendation 56 5.3 Limitations of the study 57 References 59 Abstract in Korean 65Maste

Biomass energy production in Louisiana: a GIS study on the supply chain

One major drawback of biomass fuel is its bulky nature and the resulting high cost of transporting the fuel to the facility where the energy is being produced. Hence, supply chain of biomass residues plays a crucial role in determining the financial viability of bioenergy production. Transporting biomass for energy purposes more than 50 miles (80 km) is not considered economically feasible in most conditions. In the wood energy scenario, the maximum distance is more often restricted to distances of less than 200 km between production and consumption (via road). A study was done to determine logging residues and agricultural residues production for the 64 parishes in Louisiana and to compare the three different modes of transportation (freight) for wood biomass, namely rail, road and water. The average annual production for logging residues in the state from 2000 to 2010 was estimated around 3,073,978 bone dry tons (BDT) and for agricultural crop residue it was approximately 6,773,985 BDT annually (2005- 2011). The greatest production of logging residues was in the western and northern parishes of Louisiana, away from the population centers. The road network was the most extensive means of transportation. For long distances (greater than about 150 km), the Mississippi/Red River complexes could provide a very cheap source of transportation, followed by rail, but they had their own set of logistical problems. The river or rail networks were limited for the major logging residues producers (such as Winn, Vernon, Bienville, Union, etc.) and utilizing parishes. For agricultural residues, north-eastern and central parishes like Morehouse, Madison, Franklin, East Carroll and Pointe Coupee were the major producers. Soybean, rice, corn and sugarcane constituted the majority of the agricultural residue production. All the major agricultural parishes were in close proximity to ports in the state, which opened them to the waterway system

Increasing the productivity of rajma through proper sowing date and plant geometry

Rajma (Phaseolus vulgaris L.) cultivation is gaining popularity in Terai to Hills of Nepal. The poor plant establishment and yield due to the results of unsuitable sowing time and row spacing are the main reasons for lower productivity of it. Therefore, the date of sowing and row spacing trials were conducted in two consecutive years, 2017 and 2018 at the Grain Legumes Research Program, Khajura, Banke. A widespread and registered variety of rajma PDR 14 was used in the experiment. The experiment was laid out in a split-plot design with four sowing dates (a) 11th October, (b) 26th October, (c) 10th November and (d) 25th November as the main-factor, and three rows spacing (a) 30 cm, (b) 40 cm and (c) 50 cm as the sub-factor, consisted of three replications. The effect of the date of sowing on all the yield and yield attributing characters was found significant at a one percent significance level. Similarly, row spacing has resulted in a significant difference in grain yield. Rajma sown on 26th October (Kartik 9) produced 12, 38 and 64% higher grain yield than sown on 11th October, 10th November and 25th November, respectively. Moreover, rajma seeds sown on 26th October with 30 cm × 10 cm plant geometry produced the highest grain yield (2185 kg/ha). The narrow row spacing seemed well than the wider row in rajma production. There is a great potential to increase the production and productivity of rajma through an appropriate time of sowing and row spacing

Prescribing pattern of antidiabetic drugs in tertiary care hospital

Background: The aim of the current study was to investigate the prescribing pattern of anti-diabetic drugs in diabetic patients attending tertiary care teaching hospital in Kurnool.Methods: A prospective, cross-sectional, observational survey was carried out in 100 patients of diabetes mellitus attending diabetes outpatient/medicine outpatient departments, to assess their prescribing pattern of anti-diabetic drugs.Results: Average number of anti-diabetic drugs per prescription was 1.4. Metformin (biguanide) was the commonest prescribed individual drug among oral hypoglycemic agents. Fixed dose combination of biguanide and sulfonylurea was prescribed commonly. Monotherapy dominated over polytherapy and there was a higher percentage of use of insulin in type 2 diabetics.Conclusions: OHAs still dominate the prescribing pattern, but there was a shifting trend toward the use of insulin preparations in the management of type 2 diabetes mellitus. Intensification of current drug treatment as well as planning multiple drug interventions with lifestyle modification is necessary

Deep-sea benthic foraminiferal changes in the Eastern Indian Ocean (ODP Hole 757B): their links to deep Indonesian (Pacific) flow and high latitude glaciation during the Neogene

This study analyses 26.5 Ma record of deep-sea benthic foraminifera from 194 samples from Ocean Drilling Program Hole 757B (latitude 17°01.458' S, longitude 88°10.899' E, water depth of 1652.1 m) located on the Ninetyeast Ridge, southeastern Indian Ocean below equatorial divergence zone. The data document important changes in benthic foraminiferal population at Hole 757B since the late Oligocene. The welloxygenated, oligotrophic species including Cibicides cicatricosus, C. pseudoungerianus and Oridorsalis umbonatus were dominant during the late Oligocene to the early Miocene. These species began to decline as site 757 moved northward into the influence of the Indonesian Throughflow (ITF) beneath surface and subsurface water masses from the Pacific Ocean. Cibicides cicatricosus and C. pseudoungerianus disappeared in the late Miocene (10-8 Ma) at Hole 757B. The lower bathyal to abyssal species Nuttallides umbonifera shows a major increase at ~11.5 Ma coinciding with a significant increase in Neodymium (Nd) isotope values, indicating substantial transport of deep Pacific water to the Indian Ocean through the Indonesian seaway. Nuttallides umbonifera decreases drastically during 3-2.8 Ma, though the Nd isotope values do not show a decrease. We relate this change to a low sample resolution in the latter study. This event coincides with the final closure of the Indonesian seaway and a switch in shallow ITF source from warm, saline South Pacific to cool, fresh North Pacific thermocline water, which triggered global cooling and major expansion of Northern Hemisphere glaciation

Large Scale Machine Learning in Biology

Rapid technological advances during the last two decades have led to a data-driven revolution in biology opening up a plethora of opportunities to infer informative patterns that could lead to deeper biological understanding. Large volumes of data provided by such technologies, however, are not analyzable using hypothesis-driven significance tests and other cornerstones of orthodox statistics. We present powerful tools in machine learning and statistical inference for extracting biologically informative patterns and clinically predictive models using this data. Motivated by an existing graph partitioning framework, we first derive relationships between optimizing the regularized min-cut cost function used in spectral clustering and the relevance information as defined in the Information Bottleneck method. For fast-mixing graphs, we show that the regularized min-cut cost functions introduced by Shi and Malik over a decade ago can be well approximated as the rate of loss of predictive information about the location of random walkers on the graph. For graphs drawn from a generative model designed to describe community structure, the optimal information-theoretic partition and the optimal min-cut partition are shown to be the same with high probability. Next, we formulate the problem of identifying emerging viral pathogens and characterizing their transmission in terms of learning linear models that can predict the host of a virus using its sequence information. Motivated by an existing framework for representing biological sequence information, we learn sparse, tree-structured models, built from decision rules based on subsequences, to predict viral hosts from protein sequence data using multi-class Adaboost, a powerful discriminative machine learning algorithm. Furthermore, the predictive motifs robustly selected by the learning algorithm are found to show strong host-specificity and occur in highly conserved regions of the viral proteome. We then extend this learning algorithm to the problem of predicting disease risk in humans using single nucleotide polymorphisms (SNP) -- single-base pair variations -- in their entire genome. While genome-wide association studies usually aim to infer individual SNPs that are strongly associated with disease, we use popular supervised learning algorithms to infer sufficiently complex tree-structured models, built from single-SNP decision rules, that are both highly predictive (for clinical goals) and facilitate biological interpretation (for basic science goals). In addition to high prediction accuracies, the models identify 'hotspots' in the genome that contain putative causal variants for the disease and also suggest combinatorial interactions that are relevant for the disease. Finally, motivated by the insufficiency of quantifying biological interpretability in terms of model sparsity, we propose a hierarchical Bayesian model that infers hidden structured relationships between features while simultaneously regularizing the classification model using the inferred group structure. The appropriate hidden structure maximizes the log-probability of the observed data, thus regularizing a classifier while increasing its predictive accuracy. We conclude by describing different extensions of this model that can be applied to various biological problems, specifically those described in this thesis, and enumerate promising directions for future research