Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal and mechanical controls on the evolution of archean crustal deformation: Examples from Western Australia

Dome-and-keel formation in Archean granite-greenstone terrains was uniquely favored by high abundances of heat-producing elements (HPEs) in the crust, and the ubiquity of pre-doming "greenstone-over-granite" stratification, which constituted large-scale density inversions and facilitated long-term steepening of the geotherm via burial of felsic basement-hosted HPEs. This contribution investigates the influence of these factors on the thermo-mechanical stability of the crust, with reference to two contrasting Archean granite-greenstone terrains in Western Australia. In the Neoarchean Eastern Goldfields Province, the rapid (2715-2665 Ma) accumulation of a thin (8-km) greenstone succession atop HPE-poor felsic crust (radiogenic heat flow contribution q c = 45 mW m -2 ) raised mid-crustal temperatures from 230 °C to 370 °C prior to 2650 Ma dome-and-keel formation. In such cold, strong crust, the development of broad, granite-cored antiforms and narrow, greenstone-cored synforms with little strike variation is likely to directly reflect far-field, horizontal tectonic forces, oriented perpendicular to the regional structural grain. In contrast, the Mesoarchean East Pilbara Granite-Greenstone Terrane underwent slow (3515-3325 Ma) accumulation of thick (14-km) greenstones atop HPE-rich (q c = 70 mW m -2 ) basement, which raised mid-lower crustal temperatures from 400 °C to 750-800 °C, prior to 3300 Ma dome-and-keel formation. The effective viscosity of this hot, weak crust was further reduced by partial melting of the felsic basement; the resulting "classical" architecture (featuring granite domes flanked by greenstone keels with a variety of strike orientations) may therefore reflect partial convective overturn and vertical reorganization of the crust during thermo-mechanical stabilization.
Ekman layers and two‐dimensional frontogenesis in the upper ocean

A two-dimensional modified semi geostrophic model is used to study the evolution of oceanic fronts in the presence of vertical mixing. The parameterization used for mixing is an elevated constant value of vertical viscosity and friction; hence the Ekman layer acts as a surrogate mixed layer, with, however, vertical shear allowed everywhere. An initial condition representative of the observed fields in Frontal Air-Sea Interaction Experiment (FASINEX) is used, and its modification in the presence of vertical mixing alone is investigated. Without external forcing an Ekman layer results because of the presence of vertical geostrophic shear at the surface. The maximum density gradient moves toward the dense side of the front driven by this flow. Convergence of Ekman flow results in downward bowing of the isopycnals beneath the surface expression of the front, a feature reminiscent of density sections taken during FASINEX. This feature is not evident when a barotropic convergence field is applied in the absence of mixing or in fully nonlinear simulations of the evolution of fronts with baroclinic instability. An analytic theory suggests that the maximum density gradient will increase over time when vertical mixing alone is present. In the presence of negative uniform wind stress in the direction opposite to the surface geostrophic flow the front moves toward the denser water, and the jet uniformly decreases in strength. In the presence of a positive uniform wind in the direction of the surface geostrophic flow the surface jet initially weakens but then strengthens again as the wind-driven Ekman flow opposes the frictionally driven Ekman flow and the cross-front density gradient increases.
Nitrogen use efficiency in intensive cropping systems: From crop to cropping system level

The heuristic value of the term nitrogen use efficiency (NUE) may generally be questioned. This term is used to describe a couple of input/output ratios which are very differently defined, depending on which level one looks at the ratio of nitrogen input and the yield output of the system (Novoa and Loomis, 1981) (Moll et al., 1982) (Huggins and Pan, 1993). These scales are ranging from the primary processes of plant productivity, photosynthesis and respiration, to farm and regional levels. Another problem arises from the fact that for some definitions NUE is steadily decreasing with increasing input level of nitrogen. It should therefore be predefined at which yield level and intensity level of other input resources one evaluates NUE. Using the term NUE often to veils the view on the underlying key processes of efficient nitrogen use in agriculture rather than to sharpen the discussion about it. However, despite of all these shortcomings, NUE has become a standard terminus, which can’t be ignored.
EVALUATION OF MULTIPLE KERNEL LEARNING ALGORITHMS FOR CROPMAPPING USING SATELLITE IMAGE TIME-SERIES DATA

Abstract. Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.
Face Recognition Using Line Edge Mapping Approach

The research is based on development of an authentication system. Similar to these is the facial features authentication method which is a very new and unpopular method of authentication. The method is very unique with its operation as it doesn’t require contact between the individual and the authentication device. The palm and retinal scanners have motivated the invention of the authentication system. Retinal scanners are contactless authentication methods which scans the venation in the retinal of the individual which is of course unique to human beings. The technology employed in this work uses picture frames from videos, detects facial features, and or matches the face to the respective individual’s face features in the database. Authentication systems are used to identify or verify an individual as well as to distinguish the individual so far identified. This work develops an authentication system that operates with similar accuracy and speed of the human identification.
A Study on Super Threshold FinFET Current Mode Logic Circuits

The energy dissipation of a circuit is concerned problem for battery-operated mobile platforms. The super-threshold computing scheme based on FinFET CML (Current Mode Logic) circuits is addressed in this paper to attain low power dissipations. In near-threshold circuits, the power supply voltage is slightly above the threshold voltage of MOS devices, so that their PDN transistors operate on medium inversion regions. In the super-threshold circuit, much larger supply voltage is used, so that the larger biasing current can been used, and thus the super-threshold FinFET CML circuits can realize faster operation than near-threshold one. The basic logic gates such as AND/NAND and XOR/XNOR, and 1-bit full-adder based on FinFET CML are used to verify power efficiencies. All circuits are simulated with HSPICE at a PTM (Predictive Technology Model) 32nm BSIMCMG FinFET technology. The results show that the power consumption of FinFET CML circuits can be reduced by scaling the supply voltage into super-threshold regions without performance degrading. KeywordsSuper-threshold computing, FinFET current mode logic, energy-efficient design
Effects of Late Fall Foliar Boron Sprays on the Fruit Set of Sweet Cherry Trees cv. 0900 Ziraat

In this study the effect of boron (B) sprays in late fall to the consistently low yielding 0900 Ziraat sweet cherry trees on the percentage of fruit set was investigated. Four boron doses were applied (0-75-100-150 g / tree, from 20.8 % B source) four weeks before leaf fall. There was an increase in the amount of boron content of spur flower buds in sprayed trees which in turn improved the fruit set of this cultivar (over 30.0 %) compared to untreated control trees (15.7 %). Fall foliar B sprays can be considered a valuable tool for obtaining a better yield in sweet cherry trees when needed.
Improving the Accuracy of Face Annotation in Social Network

The across the board utilization of digital cameras and cell telephones, and the prevalence of online photograph sharing applications, for example, "Flickr" and "Facebook" has prompted the production of various accumulations of individual photographs. These accumulations of individual photographs should be overseen by clients. Accordingly, an in number interest exists for programmed substance annotation procedures that encourage proficient and viable pursuit in accumulations of individual photographs. Individual photographs are generally commented along the "who," "where," and "when" measurement in a specific order of significance. In reality, late client studies report that individuals want to arrange their photographs as indicated by who shows up in their photographs (e.g., relatives or companions). The fundamental pointof this paper is to maintain a strategic distance from the duplication ofnames by utilizing random walk (RW) with restarts based semi-directed learning procedure. Utilizing Random walk, this framework re-positions the competitor annotations, in which both the web data and certainty scores of unique annotations are fortified. RW understands the general substance based face annotationissue utilizing the inquiry based strategy. By evacuating the duplication of names, the marking quality will be expanded to more noteworthy degree by which the annotation method will get exact results.
Memory: Looking back and looking forward

This review brings together past and present achievements in memory research, ranging from molecular to psychological discoveries. Despite some false starts, major advances include our growing understanding of learning-related neural plasticity and the characterisation of different classes of memory. One striking example is the ability to reactivate targeted neuronal ensembles so that an animal will seemingly re-experience a particular memory, with the further potential to modify such memories. Meanwhile, human functional imaging studies can distinguish individual episodic memories based on voxel activation patterns. While the hippocampus continues to provide a rich source of information, future progress requires broadening our research to involve other sites. Related challenges include the need to understand better the role of glial–neuron interactions and to look beyond the synapse as the sole site of experience-dependent plasticity. Unmet goals include translating our neuroscientific knowledge in order to optimise learning and memory, especially among disadvantaged populations.
Formation and manipulation of ferrofluid droplets at a microfluidic T-junction

This paper reports the formation and manipulation of ferrofluid droplets at a microfluidic T-junction in the presence of a permanent magnetic field. A small circular permanent magnet with a diameter of 3 mm is used to control the size of the ferrofluid droplets within a microfluidic device. In the absence of a magnetic field, the size of the ferrofluid droplets decreases linearly with the increase of the flow rate of the continuous phase. In the presence of a magnetic field, the size of the droplets depends on the magnetic field strength, magnetic field gradient and the magnetization of the ferrofluid. The magnetic field strength is adjusted in our experiment by the location of the magnet. The induced attractive magnetic force affects the droplet formation process leading to the change in the size of the formed droplets. Experimental observation also shows that the relative change in the size of the droplet depends on the flow rate of the continuous phase. Furthermore, the paper compares the evolving shape of the ferrofluid droplet during the formation process with and without the magnetic field.
Hybrid atomistic-continuum simulation of nucleate boiling with a domain re-decomposition method

ABSTRACT In this study, a domain re-decomposition hybrid atomistic-continuum method is developed to conduct a multiscale/multiphase investigation on the bubble nucleation. In addition to the conventional coupling scheme, this method is capable of re-partitioning the molecular and continuum domains once it is necessary during the simulation. Giving the fact that the accurate modeling of interface tracking and phase change are still problematic for continuum mechanics on microscale, our coupling method directly avoids these issues since CFD domain takes care of a single-phase flow while the molecular domain simulates the bubble growth.
A Study on Surface, Thermal and Mechanical Properties of Absorbable PLGA Plate

In recent years, it has been become important to develop an effective material to be used as scaffolds for bone fixation in surgical field. PLA (Poly lactic acid), PGA (Poly glycolic acid), PLGA(Poly lactic-co-glycolic acid) and PLLA(Poly (L)-lactic acid) are well known to absorbable polymers that exhibit sufficiently low toxicity to useful for internal applications. So, we are study on the one of absorbable polymers as scaffolds (Plates and screws) consisting of PLGA (85/15). The aim of this study is to fabricate this plates and screws using an injection molding and to evaluate its surface, thermal and mechanical properties. The obtained plates and screws were observed with SEM, NMR, XRD, XPS, FTIR, DSC, TGA and mechanical moment (tensile and compressive strength). The glass temperature and molecular of PLGA were influenced by absorbed moisture. Therefore, obtained injection moldings were stored at 40°C and 20%, 50%, 80% relative humidity. Weight fraction absorbed free moisture was determined using a chemical balance.
Design Of Anti‐Slip Controller For An Electric Vehicle With An Adhesion Status Analyzer Based On The Ev Simulator

The In this paper, a simulator of a one‐wheel Electric Vehicle system is designed for testing an anti‐slip controller using the Motor‐Generator system. The drive motor of the M‐G system is used to simulate the drive wheel of the Electric Vehicle, and the load motor is used to simulate the load force of the chassis. In the driving process, the torque of the load motor is changed according to the drive force of the chassis that is calculated by the program. So it can simulate the dynamic process of the tire‐road system. Based on this simulator system, an anti‐slip controller based on an Adhesion Status Analyzer is proposed. Information about the wheel speed is acquired by using a Back EMF Observer. A load torque disturbance observer is designed to stabilize the acceleration of the wheels. The Adhesion Status Analyzer is used to generate safe acceleration commands for the anti‐slip controller. When a slip occurs, the anti‐slip controller will decrease the torque quickly, and at the same time, by estimating the dynamic status of adhesion, the Adhesion Status Analyzer will restrain the acceleration command within a safe area. The effectiveness of the proposed approach is verified by using the EV slip simulator.
Global Existence for Degenerate Quadratic Reaction-Diffusion Systems

We consider a class of degenerate reaction-diffusion systems with quadratic nonlinearity and diffusion only in the vertical direction. Such systems can appear in the modeling of photochemical generation and atmospheric dispersion of pollutants. The diffusion coefficients are different for all equations. We study global existence of solutions. Nous considérons une classe de systèmes dégénérés de réaction-diffusion avec une non-linarité quadratique et avec diffusion uniquement dans la direction verticale. De tels systèmes peuvent apparâıtre dans la modélisation de la synthèse de polluants par réactions photochimiques et de leur dispersion atmosphérique. Les coefficients de diffusion sont différents pour chaque équation. Nous étudions l’existence globale de solutions.
Analysis of Xenopus laevis claudin (Xcla) Tight Junction Genes in Development

XIE, JIANZHEN Analysis of Xenopus laevis claudin (Xcla) tight junction genes in development Under the direction of Dr. Brenda Judge Brizuela Eight Xenopus laevis claudin genes, Xcla1, Xcla4B, Xcla5, Xcla6, Xcla12, Xcla16, Xcla18 and Xcla19, were cloned and sequenced. Their normal mRNA expression was determined from cleavage stage to tadpole stage by whole mount in situ hybridization. The protein expression of Xcla5 was detected at the neural stage by whole mount immunostaining. Overexpression of Xcla5 by injection of synthetic mRNA into embryos caused morphological defects similar to those in embryos exposed to Bisphenol A (BPA). Altered patterns of claudin gene expression in the presence of BPA can be correlated with these developmental defects. The results suggest that claudins may play an important role in neural crest cell migration, epithelial-mesenchymal transition and ultimately organogenesis during embryonic development. ANALYSIS OF Xenopus laevis CLAUDIN (Xcla) TIGHT JUNCTION GENES IN DEVELOPMENT by
An eating disorder is more than just disordered eating Bio-psycho-social perspectives

Several reports show that stress and psychiatric ill health are increasing in adolescents. Eating disorders (ED) and related conditions such as depression, self-injurious behaviour and suicide attempts are becoming more common, especially among young women. Eating disorders include two main categories: anorexia nervosa (self-starvation) and bulimia nervosa (binge eating and compensatory actions). These disorders do not only involve deviations in eating behaviour, but also include several severe physiological and psychiatric symptoms. The aetiology of eating disorders remains largely unclear, and multifactorial models that integrate biological, psychological and social perspectives are necessary in the investigation of risk factors and the natural history of these conditions. The overall aim of the present thesis was to integrate bio-psycho-social aspects in the study of the aetiology and clinical course of eating disorders. The studies included are based on two different data sets. Study I is based on the Uppsala Birth Cohort Multigenerational Study (UBCoS Multigen), a longitudinal register-based study including information about families spanning over three generations. The sample includes all men and women born at the Uppsala University Hospital between the years 1915-1929 and their descendants born up to 2002. The database is unique in enabling researchers to study intergenerational associations. The second data set is a clinical sample of severely ill, eating disorder inpatients from a specialized clinic (Study II-IV). Our results indicate that social background can be of importance in the development of eating disorders; higher education in parents and maternal grandparents was associated with higher risk of hospitalization for ED. Further we found a higher risk of ED in women with the highest marks in school. The clinical studies showed that patients with eating disorders had higher scores on somatic stress and physiological tension, as well as on cognitive-social anxiety as compared to healthy controls. The co-morbidity with self-injurious behaviour and suicide attempts was high, especially in patients with bulimia nervosa. Among the bulimia nervosa patients low social adaptation, negative childhood environment and low childhood adjustment were more common. Biological markers as measured by cytokines showed higher levels of pro-inflammatory proteins in the patient group. Personality traits indicating anxiety and aggression were associated with increased levels of cytokines. Finally neuropsychological impairments and negative self-evaluations were common in both anorexia and bulimia nervosa. Eating disorders are to be considered an increasing public health problem. Studies on the interplay between social factors, interpersonal variations in behaviour, and biological aspects of eating pathology are essential for a better understanding of eating disorders.
ROBUST TWO‐DEGREE‐OF‐FREEDOM CONTROL OF AN ATOMIC FORCE MICROSCOPE

The performance of an atomic force microscope (AFM) is improved substantially by utilizing modern model‐based control methods in comparison to a standard proportional‐integral (PI) controlled AFM system. We present the design and implementation of a two‐degree‐of‐freedom (2DOF)‐controller to accomplish topography measurements at high scan‐rates with reduced measurement error. An H∞‐controller operates the AFM system in a closed loop while a model‐based feedforward controller tracks the scanner to the last recorded scan‐line. Experimental results compare the actual performance of the standard PI‐controlled AFM and the 2DOF controlled system. The new controller reduces the control error considerably and enables imaging at higher speeds and at weaker tip‐sample interaction forces.
Online Energy Management in Microgids Considering Reactive Power

The optimal power energy scheduling of a microgrid (MG) is not only related to the active power of distributed generators but also dependent on the reactive power and system operational constraints. It is essential to manage the active and reactive power simultaneously in optimal energy distribution. This paper is focused on developing an online algorithm to optimize the real-time power energy distribution in the MG, considering both reactive power and system operational constraints. The goal is to provide high quality electricity usage for users in the MG and maximize users’ utility. The output power of controllable generators are also optimized. The proposed online algorithm is asymptotically optimal, since its solution converges to the offline optimal solution. The effectiveness of the proposed algorithm is validated using data traces obtained from a real-world MG.
Online Sequential Extreme Learning Machine for Vibration-Based Damage Assessment Using Transmissibility Data

AbstractTraditional vibration-based damage assessment approaches include the use of feed-forward neural networks. However, the slow learning speed of these networks and the large number of parameters that need to be tuned have been a major bottleneck in their application. This paper proposes to use an emergent learning algorithm called the online sequential extreme learning machine (OS-ELM) algorithm. This algorithm provides good generalization at fast learning speeds, allows data to be learned one by one or block by block, and the only parameter that needs to be tuned is the number of hidden nodes. A single-hidden-layer network is trained to detect, locate, and quantify structural damage using data derived from transmissibility measurements. Two experimental cases are presented to illustrate the approach: an eight-degree-of-freedom (DOF) mass-spring system and a beam under multiple damage scenarios. To demonstrate the potential of the proposed algorithm over existing ones, the obtained results are compar.