Ore estimation and selection of underground mining methods for some copper deposits

Imperial Users onl

Topology Network Optimization of Facility Planning and Design Problems

The research attempts to provide a graphical theory-based approach to solve the facility layout problem. Which has generally been approached using Quadratic Assignment Problem (QAP) in the past, an algebraic method. It is a very complex problem and is part of the NP-Hard optimization class, because of the nonlinear quadratic objective function and (0,1) binary variables. The research is divided into three phases which together provide an optimal facility layout, block plan solution consisting of MHS (material handling solution) projected onto the block plan. In phase one, we solve for the position of departments in a facility based on flow and utility factor (weight for location). The position of all the departments is identified on the vertices of MPG (maximal planar graph), which maximizes the possibility of flow. We use named MPG produced in literature, throughout the research. The grouping of the department is achieved through GMAFLAD, a QSP (quadratic set packing) based optimizer. In Phase 2, the dual for the MPG’s is solved consisting of department location as per phase 1, to generate Voronoi graphs. These graphs are then, expanded by an ingenious parameter optimization formulation to achieve area fitting for individual cases. Optimization modeling software, Lingo17.0 is used for solving the parameter optimization for generating coordinates of the block plan. The plotting of coordinates for the block plan graphics is done via Autodesk inventor 2019. In phase 3, the solution for MHS is achieved using an RSMT (Rectilinear Steiner minimal tree) graph approach. The Voronoi seed coordinates produced through phase 2 results are computed by GeoSteiner package to generated the RSMT graph for projection onto the block plan (Also, done by Inventor 2019). The graphical method employed in this research, itself has complex and NP-hard problem segments in it, which have been relaxed to polynomial time complexity by fragmenting into groups and solving them in sections. Solving for MPG & RSMT are a class of NP-Hard problem, which have been restricted to N=32 here. Finally, to validate the research and its methodology a real-life case study of a shipyard building for the data set of PDVSA, Venezuela is performed and verified

Genetics in Osteoarthritis Knee

Osteoarthritis (OA) is a debilitating joint disorder with a complex pathogeny wherein diverse factors interact, causing a process of deterioration of the articular cartilage and the subchondral bone. It can be primary or secondary but has common clinical, radiological, and pathological manifestations. Unfortunately, there are no curative or preventive options available for this disease. The knee is the most common site to develop OA among all synovial joints. Both environmental and genetic factors play an essential role in the initiation of the disease. Identifying the genes underlying the genetic background could give new insights into the pathophysiology of knee osteoarthritis (KOA) and could potentially lead to new drug targets. Several genes involving developmental processes or maintenance of cartilage and bone are found to be associated with KOA susceptibility and progression. Understanding the gene functions has improved the knowledge towards the disease pathogenesis. So, it will be of interest to investigate the role of gene-gene interaction in the disease

Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi

In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection. The total size of the corpus currently stands at approximately 18 hours (approx. 4-5 hours each language) and it is transcribed and annotated with grammatical information such as part-of-speech tags, morphological features and Universal dependency relationships. We discuss our methodology for data collection in these languages, most of which was done in the middle of the COVID-19 pandemic, with one of the aims being to generate some additional income for low-income groups speaking these languages. In the paper, we also discuss the results of the baseline experiments for automatic speech recognition system in these languages.Comment: Speech for Social Good Workshop, 2022, Interspeech 202

Treatment Modalities of Ankylosing Spondylitis

Ankylosing spondylitis is a chronic inflammatory arthropathy of young adults which primarily affects the axial skeleton. The pathogenesis of AS is unclear, but it is thought to be caused by an early inflammatory phase followed by ossification that may induce local osteitis. It has also been linked to an increase in morbidity and mortality and is known to have a debilitating impact on QoL of the patients. Whereby, CRP and ESR are used for assessment of the disease activity and determination of treatment efficacy, HLA-B27 is considered the best biomarker for AS diagnosis. The conventional therapeutic regimen like NSAIDs and DMARDs alone are not effective in controlling symptoms and indicators of disease; however, when combined with the physical therapy, great improvement in the QoL of the patients has been observed. The outlook for AS has improved remarkably with the advent of biologics that blocks key inflammatory cytokines such as TNF inhibitors. Biologics aids in halting disease progression, and can be used concomitantly with other medications for pain management. In this chapter, barring surgical interventions, we will discuss about the non-pharmacological and pharmacological therapies routinely employed for the treatment of AS, as well as the novel therapeutics currently under study

Bacterial ACC deaminase: Insights into enzymology, biochemistry, genetics, and potential role in amelioration of environmental stress in crop plants

Growth and productivity of crop plants worldwide are often adversely affected by anthropogenic and natural stresses. Both biotic and abiotic stresses may impact future food security and sustainability; global climate change will only exacerbate the threat. Nearly all stresses induce ethylene production in plants, which is detrimental to their growth and survival when present at higher concentrations. Consequently, management of ethylene production in plants is becoming an attractive option for countering the stress hormone and its effect on crop yield and productivity. In plants, ACC (1-aminocyclopropane-1-carboxylate) serves as a precursor for ethylene production. Soil microorganisms and root-associated plant growth promoting rhizobacteria (PGPR) that possess ACC deaminase activity regulate growth and development of plants under harsh environmental conditions by limiting ethylene levels in plants; this enzyme is, therefore, often designated as a “stress modulator.” TheACC deaminase enzyme, encoded by the AcdS gene, is tightly controlled and regulated depending upon environmental conditions. Gene regulatory components of AcdS are made up of the LRP protein-coding regulatory gene and other regulatory components that are activated via distinct mechanisms under aerobic and anaerobic conditions. ACC deaminase-positive PGPR strains can intensively promote growth and development of crops being cultivated under abiotic stresses including salt stress, water deficit, waterlogging, temperature extremes, and presence of heavy metals, pesticides and other organic contaminants. Strategies for combating environmental stresses in plants, and improving growth by introducing the acdS gene into crop plants via bacteria, have been investigated. In the recent past, some rapid methods and cutting-edge technologies based on molecular biotechnology and omics approaches involving proteomics, transcriptomics, metagenomics, and next generation sequencing (NGS) have been proposed to reveal the variety and potential of ACC deaminase-producing PGPR that thrive under external stresses. Multiple stress-tolerant ACC deaminase-producing PGPR strains have demonstrated great promise in providing plant resistance/tolerance to various stressors and, therefore, it could be advantageous over other soil/plant microbiome that can flourish under stressed environments

SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages

This year's iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features. In terms of the task, we enrich UniMorph with new data for 32 languages from 13 language families, with most of them being under-resourced: Kunwinjku, Classical Syriac, Arabic (Modern Standard, Egyptian, Gulf), Hebrew, Amharic, Aymara, Magahi, Braj, Kurdish (Central, Northern, Southern), Polish, Karelian, Livvi, Ludic, Veps, Võro, Evenki, Xibe, Tuvan, Sakha, Turkish, Indonesian, Kodi, Seneca, Asháninka, Yanesha, Chukchi, Itelmen, Eibela. We evaluate six systems on the new data and conduct an extensive error analysis of the systems' predictions. Transformer-based models generally demonstrate superior performance on the majority of languages, achieving >90% accuracy on 65% of them. The languages on which systems yielded low accuracy are mainly under-resourced, with a limited amount of data. Most errors made by the systems are due to allomorphy, honorificity, and form variation. In addition, we observe that systems especially struggle to inflect multiword lemmas. The systems also produce misspelled forms or end up in repetitive loops (e.g., RNN-based models). Finally, we report a large drop in systems' performance on previously unseen lemmas.Peer reviewe