110 research outputs found
Vulnerability of public buildings subjected to earthquake by finite element modelling
Tremors in Peninsular Malaysia and East Malaysia due to Sumatra and Philippine earthquakes have been reported several times. Engineers are concerned of the seismic vulnerability of public buildings due to lack of earthquake consideration in Malaysia’s building design procedure. This study addresses the vulnerability of public buildings in Malaysia subjected to earthquakes from Sumatra and Philippines. A case study has been conducted on low rise to medium rise reinforced concrete buildings, which are mostly categorized as moment resisting frames. The buildings are analyzed using Finite Element Modeling (FEM) under different types of analyses including Free Vibration Analysis (FVA), and Time History Analysis (THA) considering low to medium earthquake intensities. The study indicates that more than 50% of the buildings produced dynamic amplification factors of slightly more than one indicating not much of a dynamic response to the buildings. The performances of the structure are shown by the yield point at beam-column connections where the internal forces at beam elements exceed the design capacity of the beams. In the non-linear analysis, the largest damage index is still under the intermediate level where no structural damage is indicated, but some non-structural damage are expected
Demonstration of Universal Parametric Entangling Gates on a Multi-Qubit Lattice
We show that parametric coupling techniques can be used to generate selective
entangling interactions for multi-qubit processors. By inducing coherent
population exchange between adjacent qubits under frequency modulation, we
implement a universal gateset for a linear array of four superconducting
qubits. An average process fidelity of is estimated for
three two-qubit gates via quantum process tomography. We establish the
suitability of these techniques for computation by preparing a four-qubit
maximally entangled state and comparing the estimated state fidelity against
the expected performance of the individual entangling gates. In addition, we
prepare an eight-qubit register in all possible bitstring permutations and
monitor the fidelity of a two-qubit gate across one pair of these qubits.
Across all such permutations, an average fidelity of
is observed. These results thus offer a path to a scalable architecture with
high selectivity and low crosstalk
Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources
Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum
and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed
in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a
genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the
sorghum race and for trait and SNP markers for assisting in plant breeding programs
Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain
Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production
ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart
crop to overcome the food and nutritional insecurity in the developing world. The
development and characterisation of the sorghum pan-genome will provide insight
into genome diversity and functionality, supporting sorghum improvement. We built
a sorghum pan-genome using reference genomes as well as 354 genetically diverse
sorghum accessions belonging to different races. We explored the structural and
functional characteristics of the pan-genome and explain its utility in supporting genetic
gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome
of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes
are enriched with environment responsive genes and classify the sorghum accessions
according to their race.We show that 53%of genes display presence-absence variation,
and some of these variable genes are predicted to be functionally associated with drought
adaptation traits. Using more than two million SNPs from the pan-genome, association
analysis identified 398 SNPs significantly associated with important agronomic traits, of
which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that
are functionally linked to different conditions, of which 79 were absent from the reference
genome assembly. This study provides comprehensive genomic diversity resources in
sorghum which can be used in genome assisted crop improvement
Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources
Due to evolutionary divergence, sorghum race populations exhibit significant
genetic and morphological variation. A k-mer-based sorghum race sequence
comparison identified the conserved k-mers of all 272 accessions from sorghum
and the race-specific genetic signatures identified the gene variability in 10,321
genes (PAVs). To understand sorghum race structure, diversity and
domestication, a deep learning-based variant calling approach was employed
in a set of genotypic data derived from a diverse panel of 272 sorghum
accessions. The data resulted in 1.7 million high-quality genome-wide SNPs
and identified selective signature (both positive and negative) regions through a
genome-wide scan with different (iHS and XP-EHH) statistical methods. We
discovered 2,370 genes associated with selection signatures including 179
selective sweep regions distributed over 10 chromosomes. Co-localization of
these regions undergoing selective pressure with previously reported QTLs and
genes revealed that the signatures of selection could be related to the
domestication of important agronomic traits such as biomass and plant height.
The developed k-mer signatures will be useful in the future to identify the
sorghum race and for trait and SNP markers for assisting in plant
breeding programs
Development of a new AgriSeq 4K mid-density SNP genotyping panel and its utility in pearl millet breeding
Pearl millet is a crucial nutrient-rich staple food in Asia and Africa and adapted
to the climate of semi-arid topics. Since the genomic resources in pearl millet
are very limited, we have developed a brand-new mid-density 4K SNP panel
and demonstrated its utility in genetic studies. A set of 4K SNPs were mined
from 925 whole-genome sequences through a comprehensive in-silico
pipeline. Three hundred and seventy-three genetically diverse pearl millet
inbreds were genotyped using the newly-developed 4K SNPs through the
AgriSeq Targeted Genotyping by Sequencing technology. The 4K SNPs were
uniformly distributed across the pearl millet genome and showed considerable
polymorphism information content (0.23), genetic diversity (0.29), expected
heterozygosity (0.29), and observed heterozygosity (0.03). The SNP panel
successfully differentiated the accessions into two major groups, namely B
and R lines, through genetic diversity, PCA, and structure models as per their
pedigree. The linkage disequilibrium (LD) analysis showed Chr3 had higher LD
regions while Chr1 and Chr2 had more low LD regions. The genetic divergence
between the B- and R-line populations was 13%, and within the sub-population
variability was 87%. In this experiment, we have mined 4K SNPs and optimized
the genotyping protocol through AgriSeq technology for routine use, which is cost-effective, fast, and highly reproducible. The newly developed 4K middensity
SNP panel will be useful in genomics and molecular breeding
experiments such as assessing the genetic diversity, trait mapping, backcross
breeding, and genomic selection in pearl millet
Repeatability of Corticospinal and Spinal Measures during Lengthening and Shortening Contractions in the Human Tibialis Anterior Muscle
Elements of the human central nervous system (CNS) constantly oscillate. In addition, there are also methodological factors and changes in muscle mechanics during dynamic muscle contractions that threaten the stability and consistency of transcranial magnetic stimulation (TMS) and perpherial nerve stimulation (PNS) measures
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
Uncharted waters: rare and unclassified cardiomyopathies characterized on cardiac magnetic resonance imaging
Cardiac magnetic resonance imaging (CMR) has undergone considerable technology advances in recent years, so that it is now entering into mainstream cardiac imaging practice. In particular, CMR is proving to be a valuable imaging tool in the detection, morphological assessment and functional assessment of cardiomyopathies. Although our understanding of this broad group of heart disorders continues to expand, it is an evolving group of entities, with the rarer cardiomyopathies remaining poorly understood or even unclassified. In this review, we describe the clinical and pathophysiological aspects of several of the rare/unclassified cardiomyopathies and their appearance on CMR
Snake Bite in South Asia: A Review
Snake bite is one of the most neglected public health issues in poor rural communities living in the tropics. Because of serious misreporting, the true worldwide burden of snake bite is not known. South Asia is the world's most heavily affected region, due to its high population density, widespread agricultural activities, numerous venomous snake species and lack of functional snake bite control programs. Despite increasing knowledge of snake venoms' composition and mode of action, good understanding of clinical features of envenoming and sufficient production of antivenom by Indian manufacturers, snake bite management remains unsatisfactory in this region. Field diagnostic tests for snake species identification do not exist and treatment mainly relies on the administration of antivenoms that do not cover all of the important venomous snakes of the region. Care-givers need better training and supervision, and national guidelines should be fed by evidence-based data generated by well-designed research studies. Poorly informed rural populations often apply inappropriate first-aid measures and vital time is lost before the victim is transported to a treatment centre, where cost of treatment can constitute an additional hurdle. The deficiency of snake bite management in South Asia is multi-causal and requires joint collaborative efforts from researchers, antivenom manufacturers, policy makers, public health authorities and international funders
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