Editorial: Crop response to density: Optimization of resource use to promote sustainability

This issue centered around plant population density and related topics; those were stem lodging and kernel abortion, decline and variability in solar radiation, leaf area index and the amount of intercepted photosynthetically active radiation, variability in optimum density and other topics for maize and other crops (sweet corn, wheat, grain sorghum, and barley)

Haematophagic Caenorhabditis elegans

Caenorhabditis elegans is a free-living nematode that resides in soil and typically feeds on bacteria. We postulate that haematophagic C. elegans could provide a model to evaluate vaccine responses to intestinal proteins from hematophagous nematode parasites, such as Necator americanus. Human erythrocytes, fluorescently labelled with tetramethylrhodamine succinimidyl ester, demonstrated a stable bright emission and facilitated visualization of feeding events with fluorescent microscopy. C. elegans were observed feeding on erythrocytes and were shown to rupture red blood cells upon capture to release and ingest their contents. In addition, C. elegans survived equally on a diet of erythrocytes. There was no statistically significant difference in survival when compared with a diet of Escherichia coli OP50. The enzymes responsible for the digestion and detoxification of haem and haemoglobin, which are key components of the hookworm vaccine, were found in the C. elegans intestine. These findings support our postulate that free-living nematodes could provide a model for the assessment of neutralizing antibodies to current and future hematophagous parasite vaccine candidates

How familiarity warps representation in the face space

Recognition of familiar as compared to unfamiliar faces is robust and resistant to marked image distortion or degradation. Here we tested the flexibility of familiar face recognition with a morphing paradigm where the appearance of a personally familiar face was mixed with the appearance of a stranger (Experiment 1) and the appearance of one's own face with the appearance of a familiar face and the appearance of a stranger (Experiment 2). The aim of the two experiments was to assess how categorical boundaries for recognition of identity are affected by familiarity. We found a narrower categorical boundary for the identity of personally familiar faces when they were mixed with unfamiliar identities as compared to the control condition, in which the appearance of two unfamiliar faces was mixed. Our results suggest that familiarity warps the representational geometry of face space, amplifying perceptual distances for small changes in the appearance of familiar faces that are inconsistent with the structural features that define their identities

NUCLEOTIDE SEQUENCE VARIATION IN LEPTIN GENE OF MURRAH BUFFALO (BUBALUS BUBALIS)

Leptin is a 16 kD protein, synthesized by adipose tissue and is involved in regulation of feed intake, energy balance, fertility and immune functions. Present study was undertaken with the objectives of sequence characterization and studying the nucleotide variation in leptin gene in Murrah buffalo. The leptin gene consists of three exons and two introns which spans about 18.9kb, of which the first exon is not transcribed into protein. In buffaloes, the leptin gene is located on chromosome eight and maps to BBU 8q32. The leptin gene was amplified by PCR using oligonucleotide primers to obtain 289 bp fragment comprising of exon 2 and 405 bp fragment containing exon 3 of leptin gene. The amplicons were sequenced to identify variation at nucleotide level. Sequence comparison of buffalo with cattle reveals variation at five nucleotide sequences at positions 983, 1083, 1147, 1152, 1221 and all the SNPs are synonymous resulting no in change in amino acids. Three of these eight nucleotide variations have been reported for the first time in buffalo. The results indicate conservation of DNA sequence between cattle and buffalo. Nucleotide sequence variations observed at leptin gene between Bubalus bubalis and Bos taurus species revealed 97% nucleotide identity

Initial sites of hepadnavirus integration into host genome in human hepatocytes and in the woodchuck model of hepatitis B-associated hepatocellular carcinoma

Hepatitis B virus (HBV) and the closely related woodchuck hepatitis virus (WHV) are potent carcinogens that trigger development of primary hepatocellular carcinoma (HCC). The initial sites of hepadnavirus–host genome integration, their diversity and kinetics of formation can be central to virus persistence and the initiation and progression of HCC. To recognize the nature of the very early virus–host interactions, we explored de novo infection of human hepatocyte-like HepaRG cells with authentic HBV and naive woodchucks with WHV. HepaRG were analyzed from several minutes post exposure to HBV onwards, whereas woodchuck liver biopsies at 1 or 3 h and 6 weeks post infection with WHV. Inverse PCR and clonal sequencing of the amplicons were applied to identify virus–host genomic junctions. HBV and WHV DNA and their replication intermediates became detectable in one hour after virus exposure. Concomitantly, HBV DNA integration into various host genes was detected. Notably, junctions of HBV X gene with retrotransposon sequences, such as LINE1 and LINE2, became prominent shortly after infection. In woodchucks, insertion of WHV X and preS sequences into host genome was evident at 1 and 3 h post infection (h.p.i.), confirming that hepadnavirus under natural conditions integrates into hepatocyte DNA soon after invasion. The HBV and WHV X gene enhancer II/core promotor sequence most often formed initial junctions with host DNA. Moreover, multiple virus–virus DNA fusions appeared from 1 h.p.i. onwards in both infected hepatocytes and woodchuck livers. In summary, HBV DNA integrates almost immediately after infection with a variety of host’s sequences, among which tandemly repeating non-coding DNAs are common. This study revealed that HBV can engage mobile genetic elements from the beginning of infection to induce pro-oncogenic perturbations throughout the host genome. Such swift virus insertion was also evident in natural hepadnaviral infection in woodchucks

DATA MINING FOR CLASSIFICATION OF HIGH VOLUME DENSE LiDAR DATA IN AN URBAN AREA

3D LiDAR point cloud obtained from the laser scanner is too dense and contains millions of points with information. For such huge volume of data to be sorted, identified, validated and be used for prediction, data mining provides immense scope and has been used to achieve the same. Certain unique attributes were selected as an input for creating models through machine learning. Supervised models were thus built for prediction of classes through the available LiDAR data using random forest algorithm. The algorithm was chosen owing to its efficiency and accuracy over other data mining algorithms. The models created using random forest were then tested on an unclassified point cloud data of an urban area. The method shows promising results in terms of classification accuracy as overall accuracy of 91.71 % was achieved for pixel-based classification. The method also displays enhanced efficiency over common classification algorithms as the time taken to make predictions about the data is reduced considerably for a set of dense LiDAR data. This shows positive foresight of making use of data mining and machine learning to handle large volume of LiDAR data and can go a long way in augmenting efficient processing of LiDAR data

LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms

Continual Learning (CL) allows applications such as user personalization and household robots to learn on the fly and adapt to context. This is an important feature when context, actions, and users change. However, enabling CL on resource-constrained embedded systems is challenging due to the limited labeled data, memory, and computing capacity. In this paper, we propose LifeLearner, a hardware-aware meta continual learning system that drastically optimizes system resources (lower memory, latency, energy consumption) while ensuring high accuracy. Specifically, we (1) exploit meta-learning and rehearsal strategies to explicitly cope with data scarcity issues and ensure high accuracy, (2) effectively combine lossless and lossy compression to significantly reduce the resource requirements of CL and rehearsal samples, and (3) developed hardware-aware system on embedded and IoT platforms considering the hardware characteristics. As a result, LifeLearner achieves near-optimal CL performance, falling short by only 2.8% on accuracy compared to an Oracle baseline. With respect to the state-of-the-art (SOTA) Meta CL method, LifeLearner drastically reduces the memory footprint (by 178.7x), end-to-end latency by 80.8-94.2%, and energy consumption by 80.9-94.2%. In addition, we successfully deployed LifeLearner on two edge devices and a microcontroller unit, thereby enabling efficient CL on resource-constrained platforms where it would be impractical to run SOTA methods and the far-reaching deployment of adaptable CL in a ubiquitous manner. Code is available at https://github.com/theyoungkwon/LifeLearner.Comment: Accepted for publication at SenSys 202

Social Saliency of the Cue Slows Attention Shifts

Eye gaze is a powerful cue that indicates where another person\u27s attention is directed in the environment. Seeing another person\u27s eye gaze shift spontaneously and reflexively elicits a shift of one\u27s own attention to the same region in space. Here, we investigated whether reallocation of attention in the direction of eye gaze is modulated by personal familiarity with faces. On the one hand, the eye gaze of a close friend should be more effective in redirecting our attention as compared to the eye gaze of a stranger. On the other hand, the social relevance of a familiar face might itself hold attention and, thereby, slow lateral shifts of attention. To distinguish between these possibilities, we measured the efficacy of the eye gaze of personally familiar and unfamiliar faces as directional attention cues using adapted versions of the Posner paradigm with saccadic and manual responses. We found that attention shifts were slower when elicited by a perceived change in the eye gaze of a familiar individual as compared to attention shifts elicited by unfamiliar faces at short latencies (100 ms). We also measured simple detection of change in direction of gaze in personally familiar and unfamiliar faces to test whether slower attention shifts were due to slower detection. Participants detected changes in eye gaze faster for familiar faces than for unfamiliar faces. Our results suggest that personally familiar faces briefly hold attention due to their social relevance, thereby slowing shifts of attention, even though the direction of eye movements are detected faster in familiar faces