Miracle-dz/UniFAR-FTUs huggingface dataset:
Storm Surge Modeling in Large Estuaries: Sensitivity Analyses to Parameters and Physical Processes in the Chesapeake Bay

Large estuaries are especially vulnerable to coastal flooding due to the potential of combined storm surges and riverine flows. Numerical models can support flood prevention and planning for coastal communities. However, while recent advancements in the development of numerical models for storm surge prediction have led to robust and accurate models; an increasing number of parameters and physical processes’ representations are available to modelers and engineers. This study investigates uncertainties associated with the selection of physical parameters or processes involved in storm surge modeling in large estuaries. Specifically, we explored the sensitivity of a hydrodynamic model (ADCIRC) and a coupled wind-wave and circulation model system (ADCIRC + SWAN) to Manning’s n coefficient, wind waves and circulation interaction (wave setup), minimum depth (H0) in the wetting and drying algorithm, and spatially constant horizontal eddy viscosity (ESLM) forced by tides and hurricane winds. Furthermore, sensitivity analysis to Manning’s n coefficient and the interaction of waves and circulation were analyzed by using three different numerical meshes. Manning’s coefficient analysis was divided into waterway (rivers, bay and shore, and open ocean) and overland. Overall, the rivers exhibited a larger sensitivity, and M2 amplitude and maximum water elevations were reduced by 0.20 m and 0.56 m, respectively, by using a high friction value; similarly, high friction reduced maximum water levels up to 0.30 m in overland areas; the wave setup depended on the offshore wave height, angle of breaking, the profile morphology, and the mesh resolution, accounting for up to 0.19 m setup inside the bay; minimum depth analysis showed that H0 = 0.01 added an artificial mass of water in marshes and channels, meanwhile H = 0.1 partially solved this problem; and the eddy viscosity study demonstrated that the ESLM = 40 values reduced up to 0.40 m the peak of the maximum water levels in the upper side of narrow rivers.
Mixed Fantasy : An Integrated System for Delivering MR Experiences

This paper describes the underlying science and technologies employed in a system we have developed for creating and delivering multimodal Mixed Realities. We also present several aspects of a number of experiences that we have developed and delivered, when such aspects help understanding of algorithmic requirements and design decisions. The technical contributions include a unique application of retro-reflective material that results in nearly perfect chroma-key, even in the presence of changing illumination, and a component-based approach to scenario delivery. The user interface contribution is the integration of 3-D audio, hypersonic sound and special effects with the visuals typical of an MR experience.
Lactation-Related MicroRNA Expression Profiles of Porcine Breast Milk Exosomes

Breast milk is the primary source of nutrition for newborns, and is rich in immunological components. MicroRNAs (miRNAs) are present in various body fluids and are selectively packaged inside the exosomes, a type of membrane vesicles, secreted by most cell types. These exosomal miRNAs could be actively delivered into recipient cells, and could regulate target gene expression and recipient cell function. Here, we analyzed the lactation-related miRNA expression profiles in porcine milk exosomes across the entire lactation period (newborn to 28 days after birth) by a deep sequencing. We found that immune-related miRNAs are present and enriched in breast milk exosomes (p<10−16, χ 2 test) and are generally resistant to relatively harsh conditions. Notably, these exosomal miRNAs are present in higher numbers in the colostrums than in mature milk. It was higher in the serum of colostrum-only fed piglets compared with the mature milk-only fed piglets. These immune-related miRNA-loaded exosomes in breast milk may be transferred into the infant body via the digestive tract. These observations are a prelude to in-depth investigations of the essential roles of breast milk in the development of the infant’s immune system.
A NOVEL FORMULATION OF UPPER BOUND LIMIT ANALYSIS AS A SECOND-ORDER CONE PROGRAMMING PROBLEM

In this paper we describe an efficient approach to upper bound limit analysis of cohesivefrictional continua, using a finite element discretization in conjunction with second-order cone programming (SOCP). We also introduce the use of linear strain elements, focusing here on 6-node triangles in plane strain, though a directly analogous extension to 10-node tetrahedra in 3D is straightforward. If the vertices of such elements are taken as the flow rule points, it can be proved that the solutions obtained are strict upper bounds on the exact collapse load. Two numerical examples using unstructured meshes show that the linear strain elements give better results than constant strain elements combined with kinematically admissible discontinuities (until now considered to be the only practical choice for a rigorous upper bound analysis using finite elements). The examples also demonstrate that, as in shakedown analysis, the use of SOCP is highly advantageous, allowing very large problems to be solved in 1-2 minutes on a desktop PC. The obvious limitation of this approach is that it can only be applied to quadratic cone-shaped yield functions (e.g. Mohr-Coulomb in plane strain, and Drucker-Prager).
International Journal of Farming and Allied Sciences Efficiency Assessment of Fuzzy Logic Membership Models for Evaluation Scs Rainfall-runoff (acase Study: Kameh River Watershed)

This paper introduces a fuzzy rule-based model to estimate runoff in semi-arid regions(Kameh river watershed) using the Soil Conservation Service Curve Number model. In this study factors such as: Land used and hydrologic soil group are considered, to determine direct runoff or excess precipitation in the in Kameh river watershed the North East part of Iran. Thematic layers for the above parameters were prepared, in a RS environment by the means of Fuzzy logic (bell-shaped and linear membership function) and Boolean Methods. The evaluation of runoff derived from fuzzy and Boolean methods show that the calculated runoff closer to the measured runoff in the watershed but bell-shaped membership function is the best linear membership function and boolean method for application purposes.
Intraspecific kleptoparasitism and counter-tactics in the archerfish (Toxotes chatareus)

The mechanics of the archerfish’s remarkable ability to spit down aerial prey is well studied. Relatively unknown, however, are the social consequences of this hunting method. To explore how physical factors and behavioural choices affect the use and success of intraspecific kleptoparasitism in socially foraging archerfish, 10 tagged, juvenile archerfish (Toxotes chatareus) were presented in groups of 3, 5, and 7 with single crickets of 3 sizes overhanging the water by either 15 or 30 cm. Video review revealed all spits, jumps, attempted thefts, and consumptions. Kleptoparasitism attempts were common, resulting in a 43.6% loss rate to the fish that successfully brought down the prey. Group size affected the probability of kleptoparasitism asymptotically: loss rate increased as group size increased from 3 to 5 members, but with no further increase at 7 members. As observed with other kleptoparasitic species, the rate and success of kleptoparasitism increased with both prey size and prey height (analogous to handling time). Several counter-kleptoparasitism behaviours were observed, including jumping to grab prey directly, aggression, spitting technique, and positioning.
Existential witness extraction in classical realizability and via a negative translation

We show how to extract existential witnesses from classical proofs using Krivine's classical realizability--where classical proofs are interpreted as lambda_c-terms with the call/cc control operator. We first recall the basic framework of classical realizability (in classical second-order arithmetic) and show how to extend it with primitive numerals for faster computations. Then we show how to perform witness extraction in this framework, by discussing several techniques depending on the shape of the existential formula. In particular, we show that in the Sigma^0_1-case, Krivine's witness extraction method reduces to Friedman's through a well-suited negative translation to intuitionistic second-order arithmetic. Finally we discuss the advantages of using call/cc rather than a negative translation, especially from the point of view of an implementation.
Segmented compressive sensing

This paper presents an alternative way of random sampling of signals/images in the framework of compressed sensing. In spite of usual random samplers which take p measurements from the input signal, the proposed method uses M different samplers each taking pi′(i = 1, 2, 3 … M) samples. Therefore, the overall number of samples will be q = M p′. Using this method a variable sampling criterion based on the content of the segments is achievable. Following this idea, the calculated measurement (or sensing) matrix is also more incoherent in columns comparing to other conventional methods which is a desired feature. Our experiments show that the reconstructed signal using this method has a better SNR and is more robust compared to the systems using one sampler.
A Review of Bird-Inspired Flapping Wing Miniature Air Vehicle Designs

Physical and aerodynamic characteristics of the bird in flight may offer benefits over typical propeller or rotor driven miniature air vehicle (MAV) locomotion designs in certain types of scenarios. A number of research groups and companies have developed flapping wing vehicles that attempt to harness these benefits. The purpose of this paper is to report different types of flapping wing designs and compare their salient characteristics. For each category, advantages and disadvantages will be discussed. The discussion presented will be limited to miniature-sized flapping wing air vehicles, defined as 10–100 grams total weight. The discussion will be focused primarily on ornithopters which have performed at least one successful test flight. Additionally, this paper is intended to provide a representation of the field of current technology, rather than providing a comprehensive listing of all possible designs. This paper will familiarize a newcomer to the field with existing designs and their distinguishing features. By studying existing designs, future designers will be able to adopt features from other successful designs. This paper also summarizes the design challenges associated with the further advancement of the field and deploying flapping wing vehicles in practice. © 2010 ASME
The transcriptional regulatory network in the drought response and its crosstalk in abiotic stress responses including drought, cold, and heat

Drought negatively impacts plant growth and the productivity of crops around the world. Understanding the molecular mechanisms in the drought response is important for improvement of drought tolerance using molecular techniques. In plants, abscisic acid (ABA) is accumulated under osmotic stress conditions caused by drought, and has a key role in stress responses and tolerance. Comprehensive molecular analyses have shown that ABA regulates the expression of many genes under osmotic stress conditions, and the ABA-responsive element (ABRE) is the major cis-element for ABA-responsive gene expression. Transcription factors (TFs) are master regulators of gene expression. ABRE-binding protein and ABRE-binding factor TFs control gene expression in an ABA-dependent manner. SNF1-related protein kinases 2, group A 2C-type protein phosphatases, and ABA receptors were shown to control the ABA signaling pathway. ABA-independent signaling pathways such as dehydration-responsive element-binding protein TFs and NAC TFs are also involved in stress responses including drought, heat, and cold. Recent studies have suggested that there are interactions between the major ABA signaling pathway and other signaling factors in stress responses. The important roles of these TFs in crosstalk among abiotic stress responses will be discussed. Control of ABA or stress signaling factor expression can improve tolerance to environmental stresses. Recent studies using crops have shown that stress-specific overexpression of TFs improves drought tolerance and grain yield compared with controls in the field.
A robust face detector under partial occlusion

This paper presents a robust face detector under partial occlusion. In recent years, the effectiveness of support vector machines (SVM) to object detection has been reported. However, conventional methods apply one kernel to global features. Therefore, those methods are not robust to occlusion because global features are influenced easily by noise or occlusion. To overcome this problem, SVM with local kernels is proposed. It is used to realize a robust face detector under partial occlusion. The robustness of the proposed method under partial occlusion is shown by using occluded face images. The proposed method can detect faces wearing sunglasses or a scarf. It is also confirmed that the proposed method is superior to the conventional SVM with global kernel.
An integrated source-to-sink model simulation sediment flux through a river system and fluvio-deltaic stratigraphy

The evolution of fluvio-deltaic and shallow marine sedimentary systems is primarily controlled by eustatic sea level, tectonics and sediment supply. The first two variables are generally well constrained, but it is very difficult to reconstruct the amount of sediment transported by rivers over time. Therefore, in order to reconstruct such sediment flux signal and its variability on geological time scales, a source-to-sink numerical model has been developed.
Near Optimal Mobile Advertisement User Selection with Interested Area Coverage

Mobile advertisement distribution effects are vitally important for advertisers as well as users. Status quo studies are lacking of efficient distribution especially when user traces and budgets are involved. In achieving efficient and effective mobile advertisement applications, this work advocates the concept of location-centric mobile crowdsourcing network instead of conventional user-centric and platform, where locations are vitally important for advertisement distribution. To this end, this work focuses on the mobile advertisement user selection problem when interested area coverage (IAC) is considered. Unfortunately, developing location-centric needs to deal with the spatio-temporal features in each user, and IAC coverage needs to be effectively counted. Even worse, budget constraint makes this problem intractable. In tackling aforementioned challenges, this work makes following efforts: First, a budget-constrained user selection problem is formulated when location sensitive mobile advertisement applications are considered, which is proved to be NP-hard. Second, the submodularity feature is explored, and a simple but efficient heuristic algorithm is presented with guaranteed approximation ratio (1–1/e). Finally, extensive simulation results show that, our scheme could effectively improve the propagation effects for mobile advertisement with 125%.
BATCH MODE MICROMANUFACTURING BASED ON MICRO ELECTRO-DISCHARGE MACHINING AND MICRO ULTRASONIC MACHINING FOR MICRO ELECTRO MECHANICAL SYSTEMS (MEMS)

Metal alloys have material properties that are very appealing for micro electro mechanical systems (MEMS), but present a challenge for process integration within a lithographic manufacturing sequence of the type used in the semiconductor industry. The batch-mode micro electro- discharge machining (µEDM) discussed here uses lithographically-fabricated electrode arrays with high density and high uniformity to achieve high-throughput and high-precision micromachining. It has been demonstrated for potential applications that range from micro-gears to smart stents. Similarly, batch-mode micro ultrasonic machining provides lithographic manufacturing compatibility to micromachining hard ceramics and other dielectric materials, such as glass-mica ceramic, lead zirconate titanate (PZT), single-crystal quartz, ruby, etc. In this process, batch-µEDM is used to define a cutting tool with desired pattern, typically in stainless steel. This has been demonstrated for the batch fabrication of piezoelectric transducers for smart biopsy tools and structurally complex microresonators.
Survey of Hardware Systems for Wireless Sensor Networks

Wireless sensor networks have been gaining interest as a platform that changes how we interact with the physical world. Applications in medicine, military, inventory management, structural and environmental monitoring, and the like can benefit from low-power wireless nodes that communicate data collected via a variety of sensors. Current deployments of wireless sensor networks (WSN) rely on off-the-shelf commodity-based microcontrollers, but the unoptimized energy consumption of these systems can limit the effective lifetimes. Ideally, researchers would like to deeply embed wireless sensor network nodes in the physical world, relying on energy scavenged from the ambient environment. This paper provides a survey of ultra low power processors specifically designed for WSNapplications that have begun to emerge from research labs, which require detailed understanding of tradeoffs between application space, architecture, and circuit techniques to implement these low-power systems.
On Non-Standard Problem Formulations in Structural Optimization

1. Abstract The talk deals with optimization problems with vanishing constraints, i.e., with constraints that must not be considered at certain points of the feasible domain. Such formulations are typical in Topology Optimization where ”mechanical response” of vanishing structural members gets lost during optimization, and thus certain function values become undefined. As an example, consider topology problems with stress constraints. Problem formulations with vanishing constraints are not covered by the standard framework of Nonlinear Optimization. As a consequence, standard optimization theory cannot be applied, standard solution methods generally fail, convergence to non-optimal points is observed. Closely related is the effect of so-called singular optimizers. The paper deals with reformulations in standard form and with related optimality conditions. More closely we will focus on a new framework working with a reformulation in standard form given as a so-called Mathematical Program with Equilibrium Constraints (MPEC). This class of optimization problems has been very well studied by the math programming community in the recent past. In particular, several concepts of optimality conditions have been derived for MPECs. Surprisingly it turns out, that in our particular situation all these concepts are (practically) equivalent. By this, known numerical procedures for the solution of MPECs can be applied on the reformulated problem. 2.
Cognitive Estimation and Affective Judgments in Alcoholic Korsakoff Patients

Alcoholic Korsakoff patients have their most marked deficits in memory, but may exhibit problems in further cognitive and behavioral domains, particularly in so-called frontal lobe functions and on the emotional level. Cognitive estimation is among the frontal lobe-associated functions; nevertheless, the underlying processes of estimation and estimation deficits are still unknown. Additionally, though affective judgments were found to be disturbed in Korsakoff patients one can question whether this result is due to a deficiency in emotional processing itself, or whether deteriorated basic processes underlying all kinds of judgment tasks result in affective judgment errors. In this study, possible relations and underlying cognitive processes of affective and nonaffective judgments (cognitive estimates) were analyzed in a large sample of 39 Korsakoff patients. A neuropsychological test battery was administered together with a new test for cognitive estimation consisting of four dimensions (‘size,’ ‘weight,’ ‘quantity,’ and ‘time’) and an affective judgment task comprising negative, neutral, and positive words. The Korsakoff patients' results showed marked deficits concerning both, cognitive estimation and affective judgments. These deficits were highly intercorrelated and performance in both tasks was related to basic (e.g., information processing speed) and higher cognitive functions (executive functions and memory), suggesting a common basis in cognitive estimation and in affective judgments in Korsakoff syndrome.
A manic episode after bilateral subthalamic stimulation in a patient with advanced Parkinson's disease

Deep brain stimulation (DBS) has proven to be an effective treatment for patients with refractory symptoms in the advanced stages of Parkinson's disease. However, different psychiatric and cognitive problems may occur after DBS. We report a case of a manic episode after DBS of the subthalamic nucleus in a patient with advanced Parkinson's disease. After slow and gradually restart of the neurostimulation using the lowest effective intensity, the motor symptoms remained sufficiently under control without causing any psychiatric problems.
A Constraint-Based Tutor for Learning Object-Oriented Analysis and Design using UML

COLLECT-UML is an intelligent tutoring system that teaches Object-Oriented design using Unified Modelling Language (UML). UML is one of the most popular techniques used in the design and development of Object-Oriented systems nowadays. The Constraint-Based Modelling (CBM) has been used successfully in several systems and they have proved to be extremely effective in evaluations performed in real classrooms. In this paper, we present our experiences in implementing another constraint-based tutor, in the area of Object-Oriented design. We present the system's architecture and functionality and describe the results of a preliminary study with postgraduate students who interacted with the system as part of a think-aloud study. Participants felt that using the system helped them improve their UML knowledge. A full evaluation study is planned for May 2005, which aims to evaluate the interface and the effect of using the system on students' learning.
Experiments in Piecewise Linear Approximation of Nonlinear Class Boundaries using Support Vector Machines

This work is concerned with issues that arise in implementation of support vector machines (SVM) for detecting class boundaries. First, an exact solution for the convex optimization problem for Support Vector Machines(SVM) without any conventional heuristic optimization techniques is considered. Second, the application of this solution in an iterative SVM algorithm with linear kernels to data sets which are not linearly separable in order to obtain piecewise linear approximations of the class boundaries for such data. Finally, for nonlinearly separable data, the approach is applied in a space obtained by a suitable nonlinear transformation of the data, which does not increase the dimensionality of the feature space, in such a way so as to recover nonlinear class boundaries. The proposed approach is illustrated on several two-dimensional artificial datasets.