ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection

The safety and resilience of fully autonomous vehicles (AVs) are of significant concern, as exemplified by several headline-making accidents. While AV development today involves verification, validation, and testing, end-to-end assessment of AV systems under accidental faults in realistic driving scenarios has been largely unexplored. This paper presents DriveFI, a machine learning-based fault injection engine, which can mine situations and faults that maximally impact AV safety, as demonstrated on two industry-grade AV technology stacks (from NVIDIA and Baidu). For example, DriveFI found 561 safety-critical faults in less than 4 hours. In comparison, random injection experiments executed over several weeks could not find any safety-critical faultsComment: Accepted at 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Network

Impacts of biomedical hashtag-based Twitter campaign: #DHPSP utilization for promotion of open innovation in digital health, patient safety, and personalized medicine

The open innovation hub Digital Health and Patient Safety Platform (DHPSP) was recently established with the purpose to invigorate collaborative scientific research and the development of new digital products and personalized solutions aiming to improve human health and patient safety. In this study, we evaluated the effectiveness of a Twitter-based campaign centered on using the hashtag #DHPSP to promote the visibility of the DHPSP initiative. Thus, tweets containing #DHPSP were monitored for five weeks for the period 20.10.2020–24.11.2020 and were analyzed with Symplur Signals (social media analytics tool). In the study period, a total of 11,005 tweets containing #DHPSP were posted by 3020 Twitter users, generating 151,984,378 impressions. Analysis of the healthcare stakeholder-identity of the Twitter users who used #DHPSP revealed that the most of participating user accounts belonged to individuals or doctors, with the top three user locations being the United States (501 users), the United Kingdom (155 users), and India (121 users). Analysis of co-occurring hashtags and the full text of the posted tweets further revealed that the major themes of attention in the #DHPSP Twitter-community were related to the coronavirus disease 2019 (COVID-19), medicine and health, digital health technologies, and science communication in general. Overall, these results indicate that the #DHPSP initiative achieved high visibility and engaged a large body of Twitter users interested in the DHPSP focus area. Moreover, the conducted campaign resulted in an increase of DHPSP member enrollments and website visitors, and new scientific collaborations were formed. Thus, Twitter campaigns centered on a dedicated hashtag prove to be a highly efficient tool for visibility-promotion, which could be successfully utilized by healthcare-related open innovation platforms or initiatives

Advances in genetics and molecular breeding of three legume crops of semi-arid tropics using next-generation sequencing and high-throughput genotyping technologies

Molecular markers are the most powerful genomic tools to increase the efficiency and precision of breeding practices for crop improvement. Progress in the development of genomic resources in the leading legume crops of the semi-arid tropics (SAT), namely, chickpea (Cicer arietinum), pigeonpea (Cajanus cajan) and groundnut (Arachis hypogaea), as compared to other crop species like cereals, has been very slow. With the advances in next-generation sequencing (NGS) and high-throughput (HTP) genotyping methods, there is a shift in development of genomic resources including molecular markers in these crops. For instance, 2,000 to 3,000 novel simple sequence repeats (SSR) markers have been developed each for chickpea, pigeonpea and groundnut. Based on Sanger, 454/FLX and Illumina transcript reads, transcriptome assemblies have been developed for chickpea (44,845 transcript assembly contigs, or TACs) and pigeonpea (21,434 TACs). Illumina sequencing of some parental genotypes of mapping populations has resulted in the development of 120 million reads for chickpea and 128.9 million reads for pigeonpea. Alignment of these Illumina reads with respective transcriptome assemblies have provided >10,000 SNPs each in chickpea and pigeonpea. A variety of SNP genotyping platforms including GoldenGate, VeraCode and Competitive Allele Specific PCR (KASPar) assays have been developed in chickpea and pigeonpea. By using above resources, the first-generation or comprehensive genetic maps have been developed in the three legume speciesmentioned above. Analysis of phenotyping data together with genotyping data has provided candidate markers for drought-tolerance-related root traits in chickpea, resistance to foliar diseases in groundnut and sterility mosaic disease (SMD) and fertility restoration in pigeonpea. Together with these traitassociated markers along with those already available, molecular breeding programmes have been initiated for enhancing drought tolerance, resistance to fusarium wilt and ascochyta blight in chickpea and resistance to foliar diseases in groundnut. These trait-associated robust markers along with other genomic resources including genetic maps and genomic resources will certainly accelerate crop improvement programmes in the SAT legum

Antixenosis and antibiosis mechanisms of resistance to pod borer, Helicoverpa armigera in wild relatives of chickpea, Cicer arietinum

The noctuid pod borer, Helicoverpa armigera is one of the most damaging pests of chickpea, Cicer arietinum. The levels of resistance to H. armigera in the cultivated chickpea are low to moderate, but the wild relatives of chickpea have exhibited high levels of resistance to this pest. To develop insect-resistant cultivars with durable resistance, it is important to understand the contribution of different components of resistance, and therefore, we studied antixenosis and antibiosis mechanisms of resistance to H. armigera in a diverse array of wild relatives of chickpea. The genotypes IG 70012, PI 599046, IG 70022, PI 599066, IG 70006, IG 70018 (C. bijugum), ICC 506EB, ICCL 86111 (cultivated chickpea), IG 72933, IG 72953 (C. reticulatum), IG 69979 (C. cuneatum) and IG 599076 (C. chrossanicum) exhibited non preference for oviposition by the females of H. armigera under multi-choice, dual-choice and no-choice cage conditions. Based on detached leaf assay, the genotypes IG 70012, IG 70022, IG 70018, IG 70006, PI 599046, PI 599066 (C. bijugum), IG 69979 (C. cuneatum), PI 568217, PI 599077 (C. judaicum) and ICCW 17148 (C. microphyllum) suffered significantly lower leaf damage, and lower larval weights indicating high levels of antibiosis than on the cultivated chickpea. Glandular and non-glandular trichomes showed negative correlation with oviposition, while the glandular trichomes showed a significant and negative correlation with leaf damage rating. Density of non-glandular trichomes was negatively correlated with larval survival. High performance liquid chromatography (HPLC) fingerprints of leaf surface exudates showed a negative correlation of oxalic acid with oviposition, but positive correlation with malic acid. Both oxalic acid and malic acid showed a significant negative correlation with larval survival. The wild relatives exhibiting low preference for oviposition and high levels of antibiosis can be used as sources of resistance to increase the levels and diversify the basis of resistance to H. armigera in cultivated chickpea

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Overload Induced Heat Shock Proteins (HSPs), MAPK and miRNA (miR-1 and miR133a) Response in Insulin-Resistant Skeletal Muscle

Background: Insulin resistance (IR) may decrease muscle adaptability. Heat shock proteins (HSPs), mitogen-activated protein kinases (MAPKs), and miRNA are thought to play a role in muscle hypertrophy but it is unclear if IR may affect their regulation. Methods: Soleus muscles of lean Zucker (LZ) and insulin resistant obese Zucker (OZ) rats were overloaded for 7 or 21 days and subjected to immunoblotting and RT-PCR. Results: IR was associated with decreased muscle hypertrophy. Overload increased HSP27 phosphorylation in both the LZ and OZ rats at day 7 but only in the LZ at day 21. IR was associated with diminished overload induced MAPK phosphorylation and decreased expression of miR-1 and miR133. Overload decreased mir-1 levels in both the LZ and OZ but to a greater extent in the LZ animals. Conclusion: These results suggest that alterations in the regulation of HSPs, MAPKs and miRNA may be associated with the diminished hypertrophy of IR muscle