FuseFPS: Accelerating Farthest Point Sampling with Fusing KD-tree Construction for Point Clouds

Point cloud analytics has become a critical workload for embedded and mobile platforms across various applications. Farthest point sampling (FPS) is a fundamental and widely used kernel in point cloud processing. However, the heavy external memory access makes FPS a performance bottleneck for real-time point cloud processing. Although bucket-based farthest point sampling can significantly reduce unnecessary memory accesses during the point sampling stage, the KD-tree construction stage becomes the predominant contributor to execution time. In this paper, we present FuseFPS, an architecture and algorithm co-design for bucket-based farthest point sampling. We first propose a hardware-friendly sampling-driven KD-tree construction algorithm. The algorithm fuses the KD-tree construction stage into the point sampling stage, further reducing memory accesses. Then, we design an efficient accelerator for bucket-based point sampling. The accelerator can offload the entire bucket-based FPS kernel at a low hardware cost. Finally, we evaluate our approach on various point cloud datasets. The detailed experiments show that compared to the state-of-the-art accelerator QuickFPS, FuseFPS achieves about 4.3$\times$ and about 6.1$\times$ improvements on speed and power efficiency, respectively.Comment: conference for ASP-DAC 202

Molecular characterization and genetic diversity of different genotypes of Oryza sativa and Oryza glaberrima

Background: Availability of related rice species is critical for rice breeding and improvement. Two distinct species of domesticated rice exist in the genus Oryza: Oryza sativa (Asian rice) and Oryza glaberrima (African rice). New rice for Africa (NERICA) is derived from interspecific crosses between these two species. Molecular profiling of these germplasms is important for both genetics and breeding studies. We used 30 polymorphic SSR markers to assess the genetic diversity and molecular fingerprints of 53 rice genotypes of O. sativa, O. glaberrima, and NERICA. Results: In total, 180 alleles were detected. Average polymorphism information content and Shannon's information index were 0.638 and 1.390, respectively. Population structure and neighbor-joining phylogenetic tree revealed that 53 genotypes grouped into three distinct subpopulations conforming to the original three groups, except three varieties (IR66417, WAB450-4, MZCD74), and that NERICA showed a smaller genetic distance from O. sativa genotypes (0.774) than from O. glaberrima genotypes (0.889). A molecular fingerprint map of the 53 accessions was constructed with a novel encoding method based on the SSR polymorphic alleles. Ten specific SSR markers displayed different allelic profiles between the O. glaberrima and O. sativa genotypes. Conclusions: Genetic diversity studies revealed that 50 rice types were clustered into different subpopulations whereas three genotypes were admixtures. Molecular fingerprinting and 10 specific markers were obtained to identify the 53 rice genotypes. These results can facilitate the potential utilization of sibling species in rice breeding and molecular classification of O. sativa and O. glaberrima germplasms

Role of Cytokinin, Strigolactone, and Auxin Export on Outgrowth of Axillary Buds in Apple

Shoot branching is regulated by phytohormones, including cytokinin (CK), strigolactone (SL), and auxin in axillary buds. The correlative importance of these phytohormones in the outgrowth of apple axillary buds remains unclear. In this study, the outgrowth dynamics of axillary buds of a more-branching mutant (MB) and its wild-type (WT) of Malus spectabilis were assessed using exogenous chemical treatments, transcriptome analysis, paraffin section, and reverse transcription-quantitative PCR analysis (RT-qPCR). High contents of CK and abscisic acid coincided in MB axillary buds. Exogenous CK promoted axillary bud outgrowth in the WT but not in MB, whereas exogenous gibberellic had no significant effect on bud outgrowth in the WT. Functional analysis of transcriptome data and RT-qPCR analysis of gene transcripts revealed that MB branching were associated with CK signaling, auxin transport, and SL signaling. Transcription of the SL-related genes MsMAX1, MsD14, and MsMAX2 in the axillary buds of MB was generally upregulated during bud outgrowth, whereas MsBRC1/2 were generally downregulated both in WT and MB. Exogenous SL inhibited outgrowth of axillary buds in the WT and the apple varieties T337, M26, and Nagafu 2, whereas axillary buds of the MB were insensitive to SL treatment. Treatment with N-1-naphthylphalamic acid (NPA; an auxin transport inhibitor) inhibited bud outgrowth in plants of the WT and MB. The transcript abundance of MsPIN1 was generally decreased in response to NPA and SL treatments, and increased in CK and decapitation treatments, whereas no consistent pattern was observed for MsD14 and MsMAX2. Collectively, the present results suggest that in apple auxin transport from the axillary bud to the stem may be essential for the outgrowth of axillary buds, and at least, is involved in the process of bud outgrowth

Contributions of leaf distribution and leaf functions to photosynthesis and water-use efficiency from leaf to canopy in apple: A comparison of interstocks and cultivars

This article was submitted to Plant Biophysics and Modeling, a section of the journal Frontiers in Plant Science.International audienceGrafting has been widely used in horticulture to induce dwarfing and avoid stress-derived limitations on plant growth and yield by affecting plant architecture and leaf functions. However, the respective effects on plant photosynthesis and water use efficiency (WUE) of leaf distribution and functions that depend on both rootstock and scion have not been fully elucidated. This study aimed to (i) clarify the scion × interstock impacts on the variability of leaf photosynthetic traits and WUE, and (ii) decipher the respective effects of leaf distribution and functions on canopy photosynthesis and WUE (WUEc). Leaf gas exchange over light gradients and responses to light, CO2, temperature, and vapor pressure deficit were measured in two apple cultivars, ‘Liquan Fuji’ (‘Fuji’) and ‘Regal Gala’ (‘Gala’), grafted onto rootstocks combined with interstocks: a vigorous (VV, ‘Qinguan’), or a dwarf one (VD, M26). The 3D architecture-based RATP model was parameterized to estimate the canopy photosynthesis rate (Ac), transpiration rate (Ec), and WUEc. Then, virtual scenarios were used to compare the relative contributions of cultivar and interstock to canopy Ac, Ec, and WUEc. These scenarios changed the leaf distribution and functions of either cultivar or interstock. At the leaf scale, VD trees had significantly higher leaf nitrogen per area but a lower maximum carboxylation rate and dark respiration in both cultivars. In parallel with higher leaf stomatal conductance (gs) and transpiration in VD ‘Fuji’ and similar gs in VD ‘Gala’, VD trees showed significantly lower leaf photosynthesis rate and WUE than VV trees. However, lower leaf photosynthetic capacities in VD trees were compensated at the canopy scale, with Ac and WUEc for ‘Fuji’ significantly improved in VD trees under both sunny and cloudy conditions, and for ‘Gala’ significantly improved in VD trees under cloudy conditions compared with VV trees. Switching scenarios highlighted that ‘Gala’ leaf functions and distribution and VD leaf distributions enhanced Ac and WUEc simultaneously, irrespective of weather conditions. Up-scaling leaf gas exchange to the canopy scale by utilizing 3D architecture-based modeling and reliable measurements of tree architecture and leaf functional traits provides insights to explore the influence of genetic materials and tree management practices

Relationship between Rad51 G135C and G172T Variants and the Susceptibility to Cancer: A Meta-Analysis Involving 54 Case-Control Studies

<div><p>Background</p><p>The associations between Rad51 gene polymorphisms (G135C and G172T) and risk of cancer have been investigated, but the results were inconclusive. To get a comprehensive evaluation of the association above, we performed a meta-analysis of published studies.</p><p>Methods</p><p>A computerized search of PubMed, Embase and Web of Knowledge databases for all relevant studies was performed and the data were analyzed in a meta-analysis. The overall odds ratio (OR) with the 95% confidence interval (95% CI) was calculated to assess the strength of the association between Rad51 polymorphisms and cancer risk. Data were analyzed using fixed- or random-effects model when appropriate. Sensitivity analysis and publication bias test were also estimated.</p><p>Results</p><p>Overall, a total of 54 case-control studies were included in the current meta-analysis, among which 42 studies with 19,142 cases and 20,363 controls for RAD51 G135C polymorphism and 12 studies with 6,646 cases and 6,783 controls for G172T polymorphism. For G135C polymorphism, the pooled results indicated that significantly increased risk was found in overall cancers (homozygote model: OR = 1.776, 95% CI = 1.288–2.449; allelic genetic model: OR = 1.169, 95% CI = 1.016–1.345; recessive model: OR = 1.946, 95% CI = 1.336–2.835), especially in breast cancer (homozygote model: OR = 1.498, 95% CI = 1.026–2.189; recessive model: OR = 1.732, 95% CI  =  1.170–2.562). For G172T polymorphism, a decreased cancer risk was observed in head and neck cancer (homozygote model: OR  =  0.621, 95% CI  =  0.460–0.837; allelic genetic model: OR  =  0.824, 95% CI  =  0.716–0.948; recessive model: OR  =  0.639, 95% CI = 0.488–0.837).</p><p>Conclusions</p><p>Our results suggested that the Rad51 G135C polymorphism is a candidate for susceptibility to overall cancers, especially to breast cancer, and that the Rad51 G172T might play a protective role in the development of head and neck cancer.</p></div

Characteristics of the studies included on Rad51 G172T polymorphism.

<p>PB: population based; HB: hospital based; HWE: Hardy-Weinberg equilibrium (significant at the 0.05 level)</p><p>AML: acute myelocytic leukemia; HNC: head and neck cancer</p

Meta-analysis of the Rad51 G135C polymorphism on cancer risk.

<p>P-values for ORs; <i>Ph</i> values of Q-test for heterogeneity test; I² refers to the proportion of total variation owing to between-study heterogeneity</p><p>Bold data represent the positive results.</p><p>PB: population based; HB: hospital based; AML: acute myelocytic leukemia; HNC: head and neck cancer</p>*<p>Random-effects model was used when <i>Ph</i> value for heterogeneity test <0.05; otherwise, fix-effects model was used.</p