Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using microscopy and DNA metabarcoding

Moths are globally relevant as pollinators but nocturnal pollination remains poorly understood. Plant-pollinator interaction networks are traditionally constructed using either flower-visitor observations or pollen-transport detection using microscopy. Recent studies have shown the potential of DNA metabarcoding for detecting and identifying pollen-transport interactions. However, no study has directly compared the realised observations of pollen-transport networks between DNA metabarcoding and conventional light microscopy. Using matched samples of nocturnal moths, we construct pollen-transport networks using two methods: light microscopy and DNA metabarcoding. Focussing on the feeding mouthparts of moths, we develop and provide reproducible methods for merging DNA metabarcoding and ecological network analysis to better understand species-interactions. DNA metabarcoding detected pollen on more individual moths, and detected multiple pollen types on more individuals than microscopy, but the average number of pollen types per individual was unchanged. However, after aggregating individuals of each species, metabarcoding detected more interactions per moth species. Pollen-transport network metrics differed between methods, because of variation in the ability of each to detect multiple pollen types per moth and to separate morphologically-similar or related pollen. We detected unexpected but plausible moth-plant interactions with metabarcoding, revealing new detail about nocturnal pollination systems. The nocturnal pollination networks observed using metabarcoding and microscopy were similar, yet distinct, with implications for network ecologists. Comparisons between networks constructed using metabarcoding and traditional methods should therefore be treated with caution. Nevertheless, the potential applications of metabarcoding for studying plant-pollinator interaction networks are encouraging, especially when investigating understudied pollinators such as moths.
Development of a Computer-Aided-Design-Based Geometry and Mesh Movement Algorithm for 3D Aerodynamic Shape Optimization

Development of a Computer-Aided-Design-Based Geometry and Mesh Movement Algorithm for 3D Aerodynamic Shape Optimization Anh Hoang Truong Doctor of Philosophy Graduate Department of Aerospace Science and Engineering University of Toronto 2014 This thesis focuses on the development of a Computer-Aided-Design (CAD)-based geometry parameterization method and a corresponding surface mesh movement algorithm suitable for three-dimensional aerodynamic shape optimization. The geometry parameterization method includes a geometry control tool to aid in the construction and manipulation of a CAD geometry through a vendor-neutral application interface, CAPRI. It automates the tedious part of the construction phase involving data entry and provides intuitive and effective design variables that allow for both the flexibility and the precision required to control the movement of the geometry. The surface mesh movement algorithm, on the other hand, transforms an initial structured surface mesh to fit the new geometry using a discrete representation of the new CAD surface provided by CAPRI. Using a unique mapping procedure, the algorithm not only preserves the characteristics of the original surface mesh, but also guarantees that the new mesh points are on the CAD geometry. The new surface mesh is then smoothed in the parametric space before it is transformed back into three-dimensional space. The procedure is efficient in that all the processing is done in the parametric space, incurring minimal computational cost. The geometry parameterization and mesh movement tools are integrated into a three-dimensional shape optimization framework, with a linear-elasticity volumegrid movement algorithm, a Newton-Krylov flow solver for the Euler equations, and a gradient-based optimizer. The validity and accuracy of the CAD-based optimization algorithm are demonstrated through a number of verification and optimization cases.
Functional synapse types via characterization of short-term synaptic plasticity

The strengths of synaptic connections dynamically change depending on the history of synaptic events, which is referred to as short-term plasticity (STP). While STP’s underlying mechanisms are well researched, its exact functions remain poorly understood. This is in part due to the diverse patterns of STP experimentally reported. Recently, the Allen Institute for Brain Science has launched the synaptic physiology pipeline to characterize the diverse properties of synapses. Since this pipeline generates a large-scale survey of synapses in mouse primary visual cortex using highly standardized experimental protocols, it provides a unique opportunity to study diverse patterns of STP. Here, we develop an end-to-end workflow that can characterize STP from the Allen Institute for Brain Science pipeline data and conduct network simulations to infer STP’s functions. Employing this workflow, we find 1) that diverse patterns of STP exist even in the same synapse classes and 2) that postsynaptic neurons’ responses have distinct characteristics depending on STP.
Long Hours' Effects on Work-Life Balance and Satisfaction

Purpose In this study, we examined whether the associations between working hours, job satisfaction, and work-life balance are mediated by occupational stress. In addition, we tested whether perceived time control helps moderate the effects of working hours and occupational stress. Methodology Questionnaires were administered to 369 respondents working in the high-tech and banking industries. Analyses were then conducted on the data. Findings The analysis revealed significant correlations between long working hours and both occupational stress and work-life balance, as well as between occupational stress and both work-life balance and job satisfaction. In addition, the relationship between working hours and occupational stress exhibited a significantly positive interaction with perceived time control. Value The results indicate the importance of giving workers greater control over working hours. We therefore recommend that labor laws should be revised as necessary to prevent excessive working hours and enhance work-time flexibility.
Simple and Practical Multigram Synthesis of d-Xylonate Using a Recombinant Xylose Dehydrogenase

An efficient multienzyme system for the preparative synthesis of d-xylonate, a chemical with versatile industrial applications, is described. The multienzyme system is based on d-xylose oxidation catalyzed by the xylose dehydrogenase from Calulobacter crescentus and the use of catalytic amounts of NAD+. The cofactor is regenerated in situ by coupling the reduction of acetaldehyde into ethanol catalyzed by alcohol dehydrogenase from Clostridium kluyveri. Excellent conversions (>95%) were obtained in a process that allows easy product isolation by simple evaporation of the volatile buffer and byproducts.
A nearest neighbour approach by genic distance to the assignment of individuals to geographic origin

During the past decade, the use of DNA for forensic applications has been extensively implemented for plant and animal species, as well as in humans. Tracing back the geographical origin of an individual usually requires genetic assignment analysis. These approaches are based on reference samples that are grouped into populations or other aggregates and intend to identify the most likely group of origin. Often this grouping does not have a biological but rather a historical or political justification, such as “country of origin”. In this paper, we present a new nearest neighbour approach to individual assignment or classification within a given but potentially imperfect grouping of reference samples. This method, which is based on the genic distance between individuals, functions better in many cases than commonly used methods. We demonstrate the operation of our assignment method using two data sets. One set is simulated for a large number of trees distributed in a 120 km by 120 km landscape with individual genotypes at 150 SNPs, and the other set comprises experimental data of 1221 individuals of the African tropical tree species Entandrophragma cylindricum (Sapelli) genotyped at 61 SNPs. Judging by the level of correct self-assignment, our approach outperformed the commonly used frequency and Bayesian approaches by 15% for the simulated data set and by 5 to 7% for the Sapelli data set. Our new approach is less sensitive to overlapping sources of genetic differentiation, such as genic differences among closely-related species, phylogeographic lineages and isolation by distance, and thus operates better even for suboptimal grouping of individuals.
Impact of g-Load Shift on Temporal Expression Pattern of Apoptosis-linked Proteins in the Rat Mammary Gland

Abstract Alteration in gravitational load impacts homeorhetic response in rat dams which affects neonatal pup survival. However, the effects of hypergravity (HG) exposure on the abundance of apoptosis-associated proteins in mammary epithelial cells (MECs) have not been characterized. Therefore, we examined whether chronic exposure to HG from midpregnancy alters the abundance of proapoptotic proteins in MECs during the late pregnancy and early lactation. A group of pregnant Sprague Dawley rats were exposed to either HG (2g) or normo-gravity (1g: stationary control [SC]) from days 11 to 20 of gestation (G20). Another set of animals were investigated from day 11 of pregnancy through days 1 and 3 (P1 and P3, respectively) postpartum. Quantitative (pixels [px]/lobule) immunohistochemistry at G20 of Cleaved Caspase-3 (CC-3), Tumor Protein p53 (P53), and vitamin D receptor (VDR) revealed that all the three proteins were increased (p<0.01) in HG rats compared to SC animals. At P1, the HG group had twofold higher (p<0.001) expression of CC-3 relative to the SC group. Approximately, 50% (p<0.001) more VDR was detected in the HG cohorts than SC at P3. These results suggest that a shift in g-load upregulates the expression of key proapoptotic proteins during the pregnancy-to-lactation transition in the rat MECs.
The N-cadherin interactome in primary cardiomyocytes as defined by quantitative proximity proteomics

The junctional complexes that couple cardiomyocytes must transmit the mechanical forces of contraction while maintaining adhesive homeostasis. The adherens junction (AJ) connects the actomyosin networks of neighboring cardiomyocytes and is required for proper heart function. Yet little is known about the molecular composition of the cardiomyocyte AJ or how it is organized to function under mechanical load. Here we define the architecture, dynamics and proteome of the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble stable AJs along intercellular contacts with organizational and structural hallmarks similar to mature contacts. We combine quantitative mass spectrometry with proximity labeling to identify the N-cadherin (CDH2) interactome. We define over 350 proteins in this interactome, nearly 200 of which are unique to CDH2 and not part of the E-cadherin (CDH1) interactome. CDH2-specific interactors are comprised primarily of adaptor and adhesion proteins that promote junction specialization. Finally, we find evidence of dynamic interplay between AJ and Z-disc proteins. Together, our results provide novel insight into the cardiomyocyte AJ and provide a proteomic atlas for defining the molecular complexes that regulate cardiomyocyte intercellular adhesion. Summary Statement Proximity proteomics reveals a specific and specialized N-cadherin (CDH2) interactome along the cell-cell contacts of primary cardiomyocytes.
Molecular Docking of Bawang Dayak (Eleutherine bulbosa) Secondary Metabolites as Bacterial Cell Wall Synthesis Inhibitor

This study aims to determine the type of secondary metabolite from bawang dayak with the highest inhibition activity of cell wall synthesis. This research was carried out in silico by docking method using Autodock Vina 1.1. 2 on several bawang dayak metabolites on the active site of cell wall synthesis receptors. The main parameter used was the free energy of binding as affinity marker. The docking results showed that among the 24 metabolites used, the highest affinity was shown by eleutherol A, a naphthalene derivative with a ΔG value of -9.4 kcal/mol. The affinity shown is even higher than the natural ligand of the receptor, which shows that eleutherol A has the potential to be developed as an inhibitor of microbial cell wall synthesis. In other words, the isolation of eleutherol A from bawang dayak can be done to increase its potential as an antimicrobial through inhibition of cell wall synthesis.
Iterative multiuser detection for TD-CDMA exploiting data estimate refinement techniques

An iterative multiuser detection scheme with data estimate refinement is presented and analyzed. Iterative multiuser detection with data estimate refinement can be looked at as an application of the general turbo principle. FEC coding with modulation and CDMA spreading can be considered as a serially concatenated code. Turbo decoding is based on alternately decoding the two codes by the multiuser detector and the data estimate refiner. It is shown by simulations that iterative multiuser detection with data estimate refinement achieves a performance close to the matched filter bound in typical mobile radio systems like TD-CDMA. Thus, iterative multiuser detection with data estimate refinement helps to overcome the problems of low asymptotic efficiencies of linear multiuser detection like e.g. zero forcing estimation in TD-CDMA mobile radio systems with high system loads. Simultaneously the complexity of iterative multiuser detection with data estimate refinement is much smaller than that of optimum nonlinear multiuser detection.
Estimation of neural field models from spatiotemporal electrophysiological data

The human brain is one of the most complex systems faced in research and science. Different methods and theories from various categories of science and engineering have contributed to understanding the functionality of the brain and its underlying structure. However, development of a complete theory remains a huge challenge. Among many different aspects of this field of research, one of the main branches is focused on brain disorders, causes and possible improvements to treatments and patients life quality. To tackle this challenge, experimental and clinical measurements have been used with computational models to analyse and contribute to treatments of brain disorders. Signal processing is playing a key role on detecting key features out of brain electrical recordings and developing frameworks that can give insight into underlying structure of recorded observations. As part of the scope of this thesis, previous work have been extended by relaxing some of the assumptions in earlier work and checking the performance of developed framework under new conditions. The main focus of this thesis is based on application of Unscented Kalman Filter with Amari type model for human brain electrical activities. It is assumed that Amari type models can present the underlying dynamics of the brain activity. The Amari type model is presented in state space form and by use of a decomposition method, the estimation framework has been used to estimate the states and connectivity kernel gains. Heterogeneous connectivity is considered as long range connection in a neural network. The novelty introduced in this thesis is the introduction of a heterogeneous connectivity kernel in Amari type model and estimating the connectivity strength. Applications of the developed methods on the synthetic data are applied on epilepsy data and results are presented. By monitoring the parameters, it is
Principles of self-organization and load adaptation by the actin cytoskeleton during clathrin-mediated endocytosis

Force generation due to actin assembly is a fundamental aspect of membrane sculpting for many essential processes. In this work, we use a multiscale computational model constrained by experimental measurements to show that a minimal branched actin network is sufficient to internalize endocytic pits against physiological membrane tension. A parameter sweep identified the number of Arp2/3 complexes as particularly important for robust internalization, which prompted the development of a molecule-counting method in live mammalian cells. Using this method, we found that ~200 Arp2/3 complexes assemble at sites of clathrin-mediated endocytosis in human cells. Our simulations also revealed that actin networks self-organize in a radial branched array with barbed filament ends oriented to grow toward the base of the pit, and that the distribution of linker proteins around the endocytic pit is critical for this organization. Surprisingly, our model predicted that long actin filaments bend from their attachment sites in the coat to the base of the pit and store elastic energy that can be harnessed to drive endocytosis. This prediction was validated using cryo-electron tomography on cells, which revealed the presence of bent actin filaments along the endocytic site. Furthermore, we predict that under elevated membrane tension, the self-organized actin network directs more growing filaments toward the base of the pit, increasing actin nucleation and bending for increased force production. Thus, our study reveals that spatially constrained actin filament assembly utilizes an adaptive mechanism that enables endocytosis under varying physical constraints.
Avaliação de funções de afilamento de expoente-variável para árvores de Eucalyptus spp.

Variable-expoent taper functions were fitted to Eucalyptus spp. data, using different approaches for estimating inflection point (p). The precision and the prediction abilities of the taper functions were evaluated for diameter along the stem and total volume (inside bark and outside bark). A new approach was presented for estimating the p value and a modified version of Kozak’s model was developed. The geometrical methods EDE (Extremum Distance Estimator), ESE (Extremum Surface Estimator), BEDE (Bisection EDE) e BESE (Bisection ESE) can be applied as an alternative to estimate p. The fitted equations performed well, with good precisions (Syx% de 6.35% a 7.20%) and good ability to predict diameter along the stem and total volume (outside and inside bark). It was found that the different approches tested to determine p had little influence on the precision of the equations. It was observed that the relative height at the inflection point (p) varies from tree to tree and the results indicated that DBH and H have little or no effect in this variation. The modified variable exponent was similar to Kozak’s equations, but it is advantagious because it is a simpler exponent.
Effect of Different Seed Treatment on Grain Yield of Maize (Zea mays l.) Under Drought Stress Conditions

A field experiment was conducted at College of Agricultural Technology, Kullapuram Theni during 2016-2017 on “Effect of different seed treatment on grain yield of maize under drought conditions”. The experiment was laid out in a randomized block design with seven treatments and replicated thrice. The result revealed that among the seed enhancement treatments, seed treated with ZnSO4 (2 %) recorded highest plant height (154.97 cm) at 90 DAS. The higher grain yield belonged to ZnSO4 (2%) (2880 kg ha -1) (8.5% yield increase over control). The seed quality parameters like seed germination (98.71 %), mean seedling length (34.64 cm), mean seedling dry weight (84.74 mg), SVI-I and II (3420 and 8420) were also highest, followed by seed treatment with spent wash (20%)that along with the application of recommended dose of fertilizer increased all growth and yield attributes. The study showed that zinc sulfate can reduce the negative effects of drought stress on grain yield and its components.
Reducing main memory access latency through SDRAM address mapping techniques and access reordering mechanisms

As the performance gap between microprocessors and memory continues to increase, main memory accesses result in long latencies which become a factor limiting system performance. Previous studies show that main memory access streams contain significant localities and SDRAM devices provide parallelism through multiple banks and channels. These locality and parallelism have not been exploited thoroughly by conventional memory controllers. In this thesis, SDRAM address mapping techniques and memory access reordering mechanisms are studied and applied to memory controller design with the goal of reducing observed main memory access latency. The proposed bit-reversal address mapping attempts to distribute main memory accesses evenly in the SDRAM address space to enable bank parallelism. As memory accesses to unique banks are interleaved, the access latencies are partially hidden and therefore reduced. With the consideration of cache conflict misses, bit-reversal address mapping is able to direct potential row conflicts to different banks, further improving the performance. The proposed burst scheduling is a novel access reordering mechanism, which creates bursts by clustering accesses directed to the same rows of the same banks. Subjected to a threshold, reads are allowed to preempt writes and qualified writes are piggybacked at the end of the bursts. A sophisticated access scheduler selects accesses based on priorities and interleaves accesses to maximize the SDRAM data bus utilization. Consequentially burst scheduling reduces row conflict rate, increasing and exploiting the available row locality. Using a revised SimpleScalar and M5 simulator, both techniques are evaluated and compared with existing academic and industrial solutions. With SPEC CPU2000 benchmarks, bit-reversal reduces the execution time by 14% on average over traditional page interleaving address mapping. Burst scheduling also achieves a 15% reduction in execution time over conventional bank in order scheduling. Working constructively together, bit-reversal and burst scheduling successfully achieve a 19% speedup across simulated benchmarks.
Model Based Study of Crop Evapotranspiration under Canopy Shading

California has some of the key agricultural regions in the United States. One of these key regions, San Joaquin Valley, frequently experiences severe droughts leading to shortage of irrigation water. This has a significant impact on the agricultural based economy of the region. It is imperative to develop new strategies to reduce overall water consumption in agriculture without affecting crop yield. A large fraction of irrigation water is lost due to the evapotranspiration (ET) process in the crops and the soil. The classical Penman-Monteith model has been used in the present work to analyze the effect of different environmental variables and water saving strategies on the ET. Some of the scenarios considered show potential for significant water savings without much reduction in the amount of sunlight available to facilitate crop growth. The central idea considered in this study is the use of canopy shading to cover the crop field resulting in reduction in the ET. Among the strategies considered, the most promising strategy is to partially cover the crop field for a certain part of the day by employing a partially covering retractable canopy. Based on numerical calculations, total reduction in ET is calculated to be 37% from June to August for the partially covering retractable canopy.