Mountain Livelihoods in a Time of Change: a Case Study of Upper Mustang in Nepal

A case study was conducted in a remote Himalayan village—Yara—in the Upper Mustang region of Nepal. The goal of this study was to understand and assess the livelihood strategies of local people in the village. The study focused on understanding the socio-economic and environmental driving factors of livelihood vulnerability, prevalent livelihood activities, emergent livelihood strategies, and resulting livelihood outcomes in the village. We used multiple data generation methods, which included both qualitative social science and quantitative biophysical components. For the qualitative component, we utilized multiple data generation methods including key informant interviews, semi-structured household interviews, group discussions, and field observations. For the quantitative piece, we employed remote sensing to assess changes in natural resources, including vegetation and snow/ice cover for a 19-year period. We also analyzed climatic parameters to understand the climate pattern in the study area for over 30 years. Findings from the qualitative research showed the increasing vulnerability of local livelihoods attributed to various factors including changing climate, fragile geology, and degradation of natural resources. Furthermore, other socio-ecological changes have also impacted the livelihoods of locals in the region, including changes in socio-cultural structure and ongoing migration. Livelihoods in the village have largely focused on subsistence-based activities, and do not properly meet current needs in terms of food and other commodities. As such, locals are increasingly attracted to modern livelihood activities in recent years and rely more heavily on different forms of migration to fulfill those changing needs. Beginning in 1992, with the opening of Upper Mustang to the outside world, local livelihoods have been transformed from living in complete isolation to increasing interaction with the outside world, and hence leading to changing needs and expectations. Moreover, infrastructure development has been changing at a rapid pace in the region in the last decade. With improved accessibility and the increasing impact of modernization, local\u27s connection and interaction with the outside world is quickly evolving, and hence, globalization has become a growing threat to local traditional culture in the region. Additionally, natural resources have degraded in the region attributed primarily to acute water scarcity for drinking and irrigation purposes. Further, the rangelands have degraded over time with a decline in both the quality and quantity of grass every year. With remote sensing analyses, we studied the historical trend of vegetation in rangelands, which showed a significant decreasing pattern over the last 19 years. Current degradation may be caused by a wide range of variables; climate changes and non-climatic conditions such as the growing stress of livestock on rangelands in the region. NDVI trend analysis provided some helpful information indicating the role of anthropogenic factors. In household interviews, the increasing number of livestock (mainly goats and sheep) also indicated the potential for overgrazing in this region. Changing climatic conditions have further exacerbated the rangeland vulnerability. For example, the decrease of snowfall and its timing alterations have led to changes in the availability of grass in pastures as local people stated. Additionally, the Pearson Correlation analysis showed less interrelation of rainfall with the vegetation growth suggesting that snow plays a fundamental role in vegetation growth in the rangelands. Snow/ice-covered mountains, the major contributor of water for locals, are melting while resulting in scarcity of water in the region. Moreover, changes in climate patterns (rainfall, temperature, and wind) were observed, with results providing further evidence of the increasing vulnerability of local livelihoods in the region. In Yara, local people have developed strategies and relied on traditional knowledge that has enabled them to sustain their livelihoods for generations in one of the most challenging and harsh socio-ecological systems on earth. Among adverse environmental, social, economic and, often political circumstances, these communities have developed strategies to cope, adapt and recover from local and global shocks. However, recent and ongoing rapid global changes have threatened the ability of these communities to respond effectively to risks and ensure sustainable livelihoods. The increasing livelihood vulnerability of these communities has highlighted the urgent need to find sustainable and resilient adaptation strategies to overcome growing changes that threaten traditional livelihoods and the ability of communities to cope with change. Further, different households in the area are experiencing livelihood vulnerability at diverse degrees, with poorer households having limited assets to be able to respond to changes and adopt new livelihood strategies. Hence, the gap between those with resources and those with limited assets continues to increase with recent socio-ecological changes, while putting at greater risk the overall livelihoods sustainability in the region. Institutions and processes could play a key role in helping reduce the gap while recognizing different levels of vulnerability and ability to respond to threats to livelihoods

Vehicle Tracking Using Video Surveillance

In numerous applications including the security of individual vehicles as well as public transportation frameworks, the ability to follow or track vehicles is very helpful. Using computer vision and deep learning algorithms, the project deals with the concept of vehicle tracking in real-time based on continuous video stream from a CCTV camera to track the vehicles. The tracking system is tracking by detection paradigm. YOLOv3 object detection is applied to achieve faster object detection for real-time tracking. By implementing and improving the ideas of Deep SORT tracking for better occlusion handling, a better tracking system suitable for real-time vehicle tracking is presented. So as to demonstrate the achievability and adequacy of the framework, this chapter presents exploratory consequences of the vehicle following framework and a few encounters on handy executions

Investigation of Phytophthora species: Phytophthora colocasiae on Taro and Phytophthora Recovered from Streams in Eastern Tennessee

Oomycetes, also known as water molds, are morphologically similar to fungi. Unlike fungi, they are diploid and more closely related to plants. Several oomycetes are pathogenic to plants as well as aquatic animals. Members of the genus Phytophthora are a threat to many economically important crops and natural forest systems. The research presented in this thesis addresses intraspecific and interspecific variation in natural populations of Phytophthora. Chapter two summarizes genetic diversity and population structure for Phytophthora colocasiae attacking taro in Hawaii, Vietnam and Hainan Island, China based on novel single nucleotide polymorphism (SNP) markers. Phytophthora colocasiae causes Taro Leaf Blight, one of the most important diseases limiting this globally important source of food. Genetic analysis of P. colocasiae recovered from different locations showed that clonal lineages are widely distributed within populations and some clonal lineages are shared between the countries. Chapter three reports species diversity for Phytophthora and Pythium recovered from ten streams in eastern Tennessee in 2010 and 2011. This work is based on a program to monitor natural waterways for the sudden oak death pathogen, P. ramorum; a serious threat for many naturally occurring plants in east Tennessee. Molecular tools were used for identifying species recovered from the streams. During this survey, several known and unknown Phytophthora and Pythium species were identified along with a newly proposed genus Phytopythium

Data Augmentation through Pseudolabels in Automatic Region Based Coronary Artery Segmentation for Disease Diagnosis

Coronary Artery Diseases(CADs) though preventable are one of the leading causes of death and disability. Diagnosis of these diseases is often difficult and resource intensive. Segmentation of arteries in angiographic images has evolved as a tool for assistance, helping clinicians in making accurate diagnosis. However, due to the limited amount of data and the difficulty in curating a dataset, the task of segmentation has proven challenging. In this study, we introduce the idea of using pseudolabels as a data augmentation technique to improve the performance of the baseline Yolo model. This method increases the F1 score of the baseline by 9% in the validation dataset and by 3% in the test dataset.Comment: arXiv admin note: text overlap with arXiv:2310.0474

Dynamic Extreme Aneuploidy (DEA) in the vegetable pathogen Phytophthora capsici and the potential for rapid asexual evolution

Oomycete plant pathogens are difficult to control and routine genetic research is challeng- ing. A major problem is instability of isolates. Here we characterize \u3e600 field and single zoospore isolates of Phytophthora capsici for inheritance of mating type, sensitivity to mefe- noxam, chromosome copy number and heterozygous allele frequencies. The A2 mating type was highly unstable with 26% of 241 A2 isolates remaining A2. The A1 mating type was stable. Isolates intermediately resistant to mefenoxam produced fully resistant single-spore progeny. Sensitive isolates remained fully sensitive. Genome re-sequencing of single zoo- spore isolates revealed extreme aneuploidy; a phenomenon dubbed Dynamic Extreme Aneuploidy (DEA). DEA is characterized by the asexual inheritance of diverse intra-genomic combinations of chromosomal ploidy ranging from 2N to 3N and heterozygous allele fre- quencies that do not strictly correspond to ploidy. Isolates sectoring on agar media showed dramatically altered heterozygous allele frequencies. DEA can explain the rapid increase of advantageous alleles (e.g. drug resistance), mating type switches and copy neutral loss of heterozygosity (LOH). Although the mechanisms driving DEA are unknown, it can play an important role in adaptation and evolution and seriously hinders all aspects of P. capsici research

Protein-protein interaction and gene co-expression maps of ARFs and Aux/IAAs in Arabidopsis

The phytohormone auxin regulates nearly all aspects of plant growth and development. Based on the current model in Arabidopsis thaliana, Auxin/indole-3-acetic acid (Aux/IAA) proteins repress auxin-inducible genes by inhibiting auxin response transcription factors (ARFs). Experimental evidence suggests that heterodimerization between Aux/IAA and ARF proteins are related to their unique biological functions. The objective of this study was to generate the Aux/IAA-ARF protein-protein interaction map using full length sequences and locate the interacting protein pairs to specific gene co-expression networks in order to define tissue-specific responses of the Aux/IAA-ARF interactome. Pairwise interactions between 19 ARFs and 29 Aux/IAAs resulted in the identification of 213 specific interactions of which 79 interactions were previously unknown. The incorporation of co-expression profiles with protein-protein interaction data revealed a strong correlation of gene co-expression for 70% of the ARF-Aux/IAA interacting pairs in at least one tissue/organ, indicative of the biological significance of these interactions. Importantly, ARF4-8 and 19, which were found to interact with almost all Aux-Aux/IAA showed broad co-expression relationships with Aux/IAA genes, thus, formed the central hubs of the co-expression network. Our analyses provide new insights into the biological significance of ARF-Aux/IAA associations in the morphogenesis and development of various plant tissues and organs

Protein-protein interaction and gene co-expression maps of ARFs and Aux/IAAs in Arabidopsis

The phytohormone auxin regulates nearly all aspects of plant growth and development. Based on the current model in Arabidopsis thaliana, Auxin/indole-3-acetic acid (Aux/IAA) proteins repress auxin-inducible genes by inhibiting auxin response transcription factors (ARFs). Experimental evidence suggests that heterodimerization between Aux/IAA and ARF proteins are related to their unique biological functions. The objective of this study was to generate the Aux/IAA-ARF protein-protein interaction map using full length sequences and locate the interacting protein pairs to specific gene co-expression networks in order to define tissue-specific responses of the Aux/IAA-ARF interactome. Pairwise interactions between 19 ARFs and 29 Aux/IAAs resulted in the identification of 213 specific interactions of which 79 interactions were previously unknown. The incorporation of co-expression profiles with protein-protein interaction data revealed a strong correlation of gene co-expression for 70% of the ARF-Aux/IAA interacting pairs in at least one tissue/organ, indicative of the biological significance of these interactions. Importantly, ARF4-8 and 19, which were found to interact with almost all Aux-Aux/IAA showed broad co-expression relationships with Aux/IAA genes, thus, formed the central hubs of the co-expression network. Our analyses provide new insights into the biological significance of ARF-Aux/IAA associations in the morphogenesis and development of various plant tissues and organs

Population Structure of Peronospora effusa in the Southwestern United States

Peronospora effusa is an obligate pathogen that causes downy mildew on spinach and is considered the most economically important disease of spinach. The objective of the current research was to assess genetic diversity of known historical races and isolates collected in 2014 from production fields in Yuma, Arizona and Salinas Valley, California. Candidate neutral single nucleotide polymorphisms (SNPs) were identified by comparing sequence data from reference isolates of known races of the pathogen collected in 2009 and 2010. Genotypes were assessed using targeted sequencing on genomic DNA extracted directly from infected plant tissue. Genotyping 26 historical and 167 contemporary samples at 46 SNP loci revealed 82 unique multi-locus genotypes. The unique genotypes clustered into five groups and the majority of isolates collected in 2014 were genetically closely related, regardless of source location. The historical samples, representing several races, showed greater genetic differentiation. Overall, the SNP data indicate much of the genotypic variation found within fields was produced during asexual development, whereas overall genetic diversity may be influenced by sexual recombination on broader geographical and temporal scales

Response To The Pandemic: Housing For Health In The Va Tent Community

In response to the COVID-19 pandemic, an innovative approach to providing integrated primary care services was initiated in the Veterans Administration Greater Los Angeles Healthcare System (Figure 1). The Care, Treatment and Rehabilitation Services, a unique street medicine program, was placed within an encampment that is supported by the West Los Angeles VA health care services including onsite provision of 24/7 security, stability of tent sites, 3 meals a day, unlimited water, hygiene stations, face masks, showers and housing placement services.http://deepblue.lib.umich.edu/bitstream/2027.42/170780/1/AFM-348-21_PP.pdfDescription of AFM-348-21_PP.pdf : Main ArticleSEL

Genomic Selection for Wheat Blast in a Diversity Panel, Breeding Panel and Full-Sibs Panel

Wheat blast is an emerging threat to wheat production, due to its recent migration to South Asia and Sub-Saharan Africa. Because genomic selection (GS) has emerged as a promising breeding strategy, the key objective of this study was to evaluate it for wheat blast phenotyped at precision phenotyping platforms in Quirusillas (Bolivia), Okinawa (Bolivia) and Jashore (Bangladesh) using three panels: (i) a diversity panel comprising 172 diverse spring wheat genotypes, (ii) a breeding panel comprising 248 elite breeding lines, and (iii) a full-sibs panel comprising 298 full-sibs. We evaluated two genomic prediction models (the genomic best linear unbiased prediction or GBLUP model and the Bayes B model) and compared the genomic prediction accuracies with accuracies from a fixed effects model (with selected blast-associated markers as fixed effects), a GBLUP + fixed effects model and a pedigree relationships-based model (ABLUP). On average, across all the panels and environments analyzed, the GBLUP + fixed effects model (0.63 +/- 0.13) and the fixed effects model (0.62 +/- 0.13) gave the highest prediction accuracies, followed by the Bayes B (0.59 +/- 0.11), GBLUP (0.55 +/- 0.1), and ABLUP (0.48 +/- 0.06) models. The high prediction accuracies from the fixed effects model resulted from the markers tagging the 2NS translocation that had a large effect on blast in all the panels. This implies that in environments where the 2NS translocation-based blast resistance is effective, genotyping one to few markers tagging the translocation is sufficient to predict the blast response and genome-wide markers may not be needed. We also observed that marker-assisted selection (MAS) based on a few blast-associated markers outperformed GS as it selected the highest mean percentage (88.5%) of lines also selected by phenotypic selection and discarded the highest mean percentage of lines (91.8%) also discarded by phenotypic selection, across all panels. In conclusion, while this study demonstrates that MAS might be a powerful strategy to select for the 2NS translocation-based blast resistance, we emphasize that further efforts to use genomic tools to identify non-2NS translocation-based blast resistance are critical