Quantitative behavior of unipotent flows and an effective avoidance principle

We give an effective bound on how much time orbits of a unipotent group $U$ on an arithmetic quotient $G/\Gamma$ can stay near homogeneous subvarieties of $G /\Gamma$ corresponding to $\mathbb Q$-subgroups of $G$. In particular, we show that if such a $U$-orbit is moderately near a proper homogeneous subvariety of $G/\Gamma$ for a long time it is very near a different homogeneous subvariety. Our work builds upon the linearization method of Dani and Margulis. Our motivation in developing these bounds is in order to prove quantitative density statements about unipotent orbits, which we plan to pursue in a subsequent paper. New qualitative implications of our effective bounds are also given.Comment: 52 page

Managing bacterial wilt, caused by Erwinia tracheiphila, on muskmelon with early control of striped cucumber beetle ( Acalymma vittatum (F)), and through varietal selection

Muskmelon (Cucumis melo L), is an important vegetable crop in the United States. It is grown throughout the US, and Indiana ranked 4th in production after California, Arizona and Georgia with 12.4 thousand metric tons and market value of $7.6 million in 2015. Bacterial wilt of cucurbits, which is caused by Erwinia tracheiphila (E. F. Smith), and vectored by striped cucumber beetle (Acalymma vittatum (F)), is one of the most serious diseases of muskmelon that influences muskmelon quality and yield. Many cultivars of muskmelon are grown around the United States, especially in the Midwest. Muskmelon cultivars differ in attractiveness to the striped cucumber beetle (SCB) and susceptibility to BW, but no known cultivar resistant to BW has been introduced. The primary method for managing BW is controlling the striped cucumber beetle before it can infect the plant. However, it is not known whether there is a critical stage during early plant growth when muskmelon plants are more susceptible to infection and therefore control of striped cucumber beetle is especially important. We conducted three field experiments at two locations (Lafayette and Vincennes, IN) in 2013 and 2014 to investigate whether there is a critical period for striped cucumber beetle control sometime during the first three weeks after muskmelons are transplanted to the field. We found that using row covers that exclude beetles, seed treatment or soil drenches with insecticide thiamethoxam significantly reduces the beetle numbers and wilt and increases the number of marketable fruits yield compared to not controlling striped cucumber beetle. However, the length of time row covers were left on the plants (for 7, 14, or 21 days after transplanting, DAT), or the period beetles were permitted to feed on plants (0-7, 7-14, or 14-21 DAT), or the time when beetles began to feed on plants (0, 7, or 14 DAT) did not significantly influence disease influence or yield in a consistent manner. This suggests that there is no clear ‘critical period’ during early muskmelon growth when controlling striped cucumber beetles is especially important. The data show that maximum severity of bacterial wilt occurred in June and July, which corresponds to development of disease transmitted by feeding of overwintered beetles plus additional transmission by the first generation of adults to emerge in the summer. We also conducted field studies in 2015 and 2016 with 10 to 12 cultivars at three locations (Lafayette, Wanatah and Vincennes, Indiana) to identify those most and least attractive to SCB and susceptible to BW. Replicated plots of each cultivar were grown and natural populations of SCB allowed to feed. At one location, additional plots of each cultivar were populated with 5 SCB per plant, and row covers applied to keep the SCB near the plants for 3 weeks. Results differed among locations. Without row covers, cultivars ‘Diplomat’, ‘Dream Dew’ and ‘RML 9818’ attracted higher numbers of SCBs than most other cultivars at one location each. ‘Dream Dew’ (at all locations) and ‘RML 9818’ (at two locations) had significantly higher percentages of BW than the least susceptible cultivars. Without row covers, ‘Superstar’, ‘Aphrodite’ and ‘Wrangler’ produced significantly greater yield than the lowest yielding cultivars at all locations. With row covers, early season beetle populations did not differ among cultivars and BW was greatest in ‘Dream Dew’ and least in ‘Superstar’ with other cultivars intermediate. With row covers, ‘Athena’ and ‘Superstar’ produced greater yield than many other cultivars. Over all ‘Diplomat’ and ‘Dream Dew’ were the most attractive to beetles and susceptible to BW. ‘Aphrodite’, ‘Athena’ and especially ‘Superstar’ were less attractive to beetles and showed more tolerance to BW in both 2015 and 2016. We found cucurbitacin A in leaves of ‘Athena’ and ‘RML9818’, and cucurbitacin B only in leaves and stems of ‘Dream Dew’ and ‘RML9818’. All cultivars had cucurbitacin I in both leaves and stems. In leaves the highest level of cucurbitacin I was found in ‘Hales Best’ followed by ‘Afg1’ and ‘Superstar’, and the highest level of cucurbitacin A was found in ‘RML9818’. Stems of ‘Diplomat’ had the most cucurbitacin I, followed ‘Superstar’, ‘Dream Dew’ and ‘Hales Best’. Cucurbitacin B was the highest in stems of both ‘Dream Dew’ and ‘RML9818’. Cucurbitacin E was present at similar levels in the stems of ‘Diplomat’, ‘Hales Best’ and ‘Afg2’

Optimisation de la Conception du Moteur Synchrone à Excitation Hybride pour Véhicules Électriques à Haut Performance

Since 1970, the ever-growing concerns of human community for the life-threatening environmental changes have pushed the policy makers to decarbonize those sectors with high energy demands, including the transportation industry. Optimal designs of Electric Vehicles (EVs) can contribute to today’s exigent car market, and take the leading role for future sustainable transportation of human and goods. At the heart of electromechanical energy conversion lays the electrical machines, which have attracted lots of interests and efforts for efficiency increase and cost reduction. In this thesis, a methodology is proposed and implemented to design and optimize the cost and efficiency of a Hybrid Excitation Synchronous Machine (HESM) for a given vehicle and a desired driving cycle. Hybridization in the excitation system can combine the favorable qualities of high-torque at low-speed with superior overloading capability, exceptional flux weakening and extended Constant Power Speed Range (CPSR), high efficiency, and flexible controllability in motoring and generation modes. With HESM technology, we can also shift from the rare-earth magnets towards the cheap ferrite magnets and guaranty the supply for motor industry. The designed HESM in this work responds to three requirements of the vehicle, namely, the maximum cruising speed, acceleration time, and gradeability, with the least or null overdesign in the drivetrain. At the same time, it will have the maximum global efficiency over the driving cycle, and the minimum cost for the material. The optimization is conducted at either of the component and system levels. The optimization at component-level is developed based on the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). A new formulation for the objective functions is proposed, which deals with the design optimization and cost minimization, simultaneously. To maximize the efficiency, a system-level search is conducted to find the optimum HESM with the highest global efficiency over a given driving cycle. Due to the 3D direction of magnetic flux in the selected HESM topology, the Finite Element Analysis (FEA) was very time- and process-consuming. To be able to evaluate the objective functions during the optimization, a new model has been developed based on a 3D Magnetic Equivalent Circuit (MEC) network. This model predicts well the non-linearity of magnetic materials, as compared with the FEA simulations. At last, the final optimized HESM is evaluated by the virtue of FEA technique.Depuis 1970, les préoccupations de l’humanité envers les changements climatiques ont poussé les chercheurs à faire des études approfondies pour optimiser les machines électriques pour avoir des véhicules électriques plus performants et moins énergivores. La conception optimale de véhicules électriques (EV) peut contribuer pour un marché automobile plus exigeant et jouer un rôle principal pour le futur du transport durable des biens et des personnes. Les machines électriques se trouvent au cœur de la conversion d'énergie électromécanique, qui ont suscité beaucoup d'intérêts et d’efforts pour augmenter leur rendement et réduire leur coût. Cette thèse propose une méthodologie et une mise en œuvre pour minimiser le coût et maximiser l’efficacité d’une machine synchrone à excitation hybride (HESM) pour un véhicule donné et un cycle de conduite sélectionné. L'hybridation du système d’excitation peut combiner les qualités favorables comme un couple élevé à basse vitesse avec une capacité de surcharge supérieure, un défluxage exceptionnelle et une plage de vitesse prolongée de puissance constante (CPSR), une efficacité élevée et une contrôlabilité flexible dans les modes de traction et de freinage régénératif. Avec la technologie HESM, nous pouvons également passer des aimants de terres rares aux aimants en ferrite bon marché, et garantir l’approvisionnement pour l’industrie automobile. Le HESM conçu dans ce travail répond à trois exigences du véhicule : la vitesse de croisière maximale, le temps d’accélération et la capacité de monter une pente, avec un surdimensionnement minimal ou nulle de la chaîne de traction. Une optimisation multiniveau avec une interaction entre la vision composant et la vision système est proposée et validée. L’optimisation au niveau du composant est développée sur la base de l’algorithme génétique de tri non dominé (NSGA-II). Une nouvelle formulation pour les fonctions objectives est proposée pour l’optimisation simultanée de la conception de la machine et de la minimisation de son coût. Après avoir optimisés onze HESM au niveau du composant, pour maximiser l’efficacité, une optimisation au niveau du système est réalisée pour trouver le HESM optimal avec le plus haut rendement global sur le cycle de conduite donné. Une validation de la conception finale de la HESM présente un meilleur rendement global sur le cycle de conduite de 18,65% en relation à une machine synchrone à excitation séparée équivalente et 15,8% en relation à une à aiment permanent. En raison de la direction 3D du flux magnétique dans la topologie HESM sélectionnée, l’analyse par éléments finis (FEA) prenait beaucoup de temps et de ressources computationnelles. Afin d’évaluer les fonctions objectives lors de l’optimisation, un nouveau modèle a été développé basé sur un réseau de circuits magnétiques équivalents 3D (MEC). Ce modèle prédit bien la non-linéarité des matériaux magnétiques, par rapport aux simulations FEA. Enfin, le HESM optimisé final est évalué grâce à la technique FEA

Machine Learning-Enabled Resource Allocation for Underlay Cognitive Radio Networks

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources and the way they are regulated. Considering that the radio spectrum is a natural limited resource, supporting the ever increasing demands for higher capacity and higher data rates for diverse sets of users, services and applications is a challenging task which requires innovative technologies capable of providing new ways of efficiently exploiting the available radio spectrum. Consequently, dynamic spectrum access (DSA) has been proposed as a replacement for static spectrum allocation policies. The DSA is implemented in three modes including interweave, overlay and underlay mode [1]. The key enabling technology for DSA is cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems. Unlike conventional radio which is restricted to only operate in designated spectrum bands, a CR has the capability to operate in different spectrum bands owing to its ability in sensing, understanding its wireless environment, learning from past experiences and proactively changing the transmission parameters as needed. These features for CR are provided by an intelligent software package called the cognitive engine (CE). In general, the CE manages radio resources to accomplish cognitive functionalities and allocates and adapts the radio resources to optimize the performance of the network. Cognitive functionality of the CE can be achieved by leveraging machine learning techniques. Therefore, this thesis explores the application of two machine learning techniques in enabling the cognition capability of CE. The two considered machine learning techniques are neural network-based supervised learning and reinforcement learning. Specifically, this thesis develops resource allocation algorithms that leverage the use of machine learning techniques to find the solution to the resource allocation problem for heterogeneous underlay cognitive radio networks (CRNs). The proposed algorithms are evaluated under extensive simulation runs. The first resource allocation algorithm uses a neural network-based learning paradigm to present a fully autonomous and distributed underlay DSA scheme where each CR operates based on predicting its transmission effect on a primary network (PN). The scheme is based on a CE with an artificial neural network that predicts the adaptive modulation and coding configuration for the primary link nearest to a transmitting CR, without exchanging information between primary and secondary networks. By managing the effect of the secondary network (SN) on the primary network, the presented technique maintains the relative average throughput change in the primary network within a prescribed maximum value, while also finding transmit settings for the CRs that result in throughput as large as allowed by the primary network interference limit. The second resource allocation algorithm uses reinforcement learning and aims at distributively maximizing the average quality of experience (QoE) across transmission of CRs with different types of traffic while satisfying a primary network interference constraint. To best satisfy the QoE requirements of the delay-sensitive type of traffics, a cross-layer resource allocation algorithm is derived and its performance is compared against a physical-layer algorithm in terms of meeting end-to-end traffic delay constraints. Moreover, to accelerate the learning performance of the presented algorithms, the idea of transfer learning is integrated. The philosophy behind transfer learning is to allow well-established and expert cognitive agents (i.e. base stations or mobile stations in the context of wireless communications) to teach newly activated and naive agents. Exchange of learned information is used to improve the learning performance of a distributed CR network. This thesis further identifies the best practices to transfer knowledge between CRs so as to reduce the communication overhead. The investigations in this thesis propose a novel technique which is able to accurately predict the modulation scheme and channel coding rate used in a primary link without the need to exchange information between the two networks (e.g. access to feedback channels), while succeeding in the main goal of determining the transmit power of the CRs such that the interference they create remains below the maximum threshold that the primary network can sustain with minimal effect on the average throughput. The investigations in this thesis also provide a physical-layer as well as a cross-layer machine learning-based algorithms to address the challenge of resource allocation in underlay cognitive radio networks, resulting in better learning performance and reduced communication overhead

Molecular and physiological investigation of trace metal stress in seagrass, Zostera muelleri

University of Technology Sydney. Faculty of Science.Despite the vast research on the negative effects of anthropogenic pollution on marine organisms, little is known about the toxicity responses of seagrasses to such perturbations. Understanding seagrass responses at the molecular level will ensure adequate conservation strategies to mitigate the increasing decline rate of seagrasses as a result of climate change and anthropogenic driven disturbances. The meadows of the Southern hemisphere seagrass species, , encounter similar threats, which led to a significant loss along the Australia and New Zealand coasts. Trace metal pollution and most specifically copper (Cu), have been previously reported in industrial, agricultural and domestic run-off waste which often finds their way to the ocean and jeopardise the health of the seagrass meadows. Although we have a firm undersetting of the deleterious effect of Cu stress at the physiological and ecological level, no current knowledge exists on how . responds to elevated levels of Cu at the molecular level. Upon our investigation of the physiological responses of . to 250 μg Cu L⁻¹ and 500 μg Cu L⁻¹ over a 7 day period of exposure, the Cu accumulation in the leaves, the continual production of ROS and the decline of photosynthetic efficiency were observed in . at both above mentioned Cu concentrations. However, the responses were concentration-dependent illustrating 250 μg Cu L⁻¹ and 500 μg Cu L⁻¹ as a tolerable and a toxic level for . , respectively. The results of our molecular investigations indicated regulation shifts in the expression of genes and the abundance of proteins mainly at 500 μg Cu L⁻¹ were associated with energy metabolism, carbon fixation, photosynthesis and defence mechanism. While the expression of genes (and the abundance of proteins) involved in energy metabolism (mainly glycolysis) and defence mechanism have been shown to be mainly increased, the opposite was observed in the photosynthetic process and carbon fixation. As a result, whilst these results offers a new level of understanding into the seagrass toxicity responses at transcriptomic and proteomic levels, it also provides candidate molecular markers for future toxicology studies and seagrass monitoring. This PhD thesis also evaluates a protein-centric and four peptide-centric proteomic methods and proposed an optimised peptide desalting protocol. Additionally, major alterations in photosynthesis process as a result of Cu stress has led us to report on an optimised intact chloroplast isolation method that can be used for future proteomic-based studies

Comparison of Attractiveness and Reaction of Melon Cultivars to the Striped Cucumber Beetle and Bacterial Wilt, 2015

This is a compilation of 21 research trial reports from four land-grant universities in the Midwestern United States. Crops include cantaloupe, pickling cucumber, pepper, potato, pumpkin, summer squash and zucchini, sweet corn, tomato, and watermelon. Somecrops were evaluated in high tunnels or hoophouses. Most trials evaluated different cultivars or varieties. One report addressed plant spacing for sweet corn and one addressed soil block for production of tomato seedlings. A list of vegetable seed sources and a list of other online sources of vegetable trial reports are also included

Differences in human perception

Spatial navigation involves dynamic and intricate brain functions, fundamentally required to locate oneself in space, which is vital for any human’s survival in their daily life. Sensorimotor abilities are quintessential for spatial navigation wherein subjects associate external sensory stimuli with sensori commands. Individuals for instance process external stimiuli such as buildings in the environment and pathways between the buildings and internally create spatial information in their brain and use this information to navigate in the environment (Brunsdon, Nickels, & Coltheart, 2007; Davis, 1999; Farah, 1989). Therefore, individuals create a mental image of the environment which they are navigating and with respect to their target, they manipulate their current position (Palermo, Iaria, & Guariglia, 2008). The Chapter identifies the difference in human perception of different spatial environments via analyzing activated parts of the brain [of the participants in the experiment], as they encounter three different types of environments: - Fully-designed environment - Semi-designed environments - Abstract-environment The aim of the experiment was to prove that human perception is different in abstract environments as comparison to fully designed and semi designed environments. Since an abstract environment, has multiple degrees of freedom as compared to the physical world and is thus unlike a fully-designed or a semi-designed environment, the difference in perception of these kinds of environments can be related to creativity and divergent thinking. The experiment was conducted at The Goldsmiths University, London in collaboration with the Faculty of Psychology, under the supervision of Professor Joydeep Bhattacharya. The findings have been published in the fifth journal paper “Navigating abstract virtual environment: an eeg study”. Cognitive Neurodynamics, 1-10, Springer publisher, New York, US

Fas and fas-ligand promoter polymorphisms in hepatitis b virus infection

Background: The FAS and FAS-Ligand (FASL) system is an important apoptosis pathway in the liver. The FAS-mediated pathway functions by binding the FASL on the activated cytotoxic T lymphocytes and Natural Killer (NK) cells to the FAS receptor on infected hepatocytes. FAS and FASL polymorphisms, which are related to apoptosis, might influence the outcome of Hepatitis B Virus (HBV) infection. Objectives: Thus, the present study aimed to determine if FAS and FASL promoter polymorphisms are associated with the clinical outcome of HBV infection. Patients and Methods: DNA samples were obtained from the infected individuals including chronic carrier (n = 50), chronic hepatitis (n = 50), cirrhosis (n = 25), naturally recovered (n = 26) and compared with those of their matched healthy controls (n = 100). Genotyping for polymorphisms of FAS-670 A/G and -1377 G/A, and FASL -844 C/T was performed using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) assays. Results: Multiple analyses for genetic association of FAS and FASL polymorphisms were not statistically different between HBV patients (n = 125) and healthy controls (n = 100). However, genotype and allele frequencies of FASL-844 C/T were significantly different between recovered individuals and patients with cirrhosis (P = 0.02 and P=0.01, respectively). Whereas, FAS-670A/G and -1377G/A polymorphisms were similarly distributed in these two groups (P = 0.8 and P = 0.47, respectively). Conclusions: The current study results showed that bearing -844T allele in FASL promoter region has a protective effect on cirrhosis and is involved in recovery from infection. In conclusion, it is proposed that HBV infection outcome might be influenced by FASL-844C/T polymorphism through alteration in apoptosis of hepatocytes. © 2015, Kowsar Corp

To evaluate the correlation between gingival crevicular blood glucose and capillary blood glucose to screen diabetes mellitus in the dental office

Background: Most of the Indian population goes undiagnosed for diabetes due to unawareness. This will lead to more serious and long-term complications of diabetes. Thus, there is a critical need to increase opportunities for diabetes screening and early diabetes detection. Research has explored the dental office as a strategic venue of opportunity for glucose testing, examining the possibility of using gingival crevicular fluid (GCF) for diabetes screening. Aim: The aim of this study is to evaluate the reliability of gingival crevicular blood (GCB) to screen the diabetes. Methodology: Thirty patients were randomly selected based on bleeding on probing and probing depth. GCB and capillary finger blood (CFB) glucose levels were calculated using glucometer from patients. Data for glucose levels were statistically analyzed. Results: The correlation between GCB and CFB was high. Conclusion: GCB can be used as the screening test for diabetes in the dental office. Clinical Significance: GCB blood glucose level detection can be used as chairside screening test for diabetes patients