Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Proteomic Analysis of the Response to Zinc, Magnesium, and Calcium Deficiency in Specific Cell Types of Arabidopsis Roots

The proteome profiles of specific cell types have recently been investigated using techniques such as fluorescence activated cell sorting and laser capture microdissection. However, quantitative proteomic analysis of specific cell types has not yet been performed. In this study, to investigate the response of the proteome to zinc, magnesium, and calcium deficiency in specific cell types of Arabidopsis thaliana roots, we performed isobaric tags for relative and absolute quantification (iTRAQ)-based quantitative proteomics using GFP-expressing protoplasts collected by fluorescence-activated cell sorting. Protoplasts were collected from the pGL2-GFPer and pMGP-GFPer marker lines for epidermis or inner cell lines (pericycle, endodermis, and cortex), respectively. To increase the number of proteins identified, iTRAQ-labeled peptides were separated into 24 fractions by OFFGFEL electrophoresis prior to high-performance liquid chromatography coupled with mass spectrometry analysis. Overall, 1039 and 737 proteins were identified and quantified in the epidermal and inner cell lines, respectively. Interestingly, the expression of many proteins was decreased in the epidermis by mineral deficiency, although a weaker effect was observed in inner cell lines such as the pericycle, endodermis, and cortex. Here, we report for the first time the quantitative proteomics of specific cell types in Arabidopsis roots.
Multiple-objective backtrace for solving test generation constraints

Current paper presents a new method for solving hierarchical test generation constraints. Unlike most of the previous solvers, the proposed approach relies on the low-level model description of the constraints. The low-level model used is structurally synthesized BDDs, which are generated directly from the gate-level descriptions of the hierarchical modules. The method has been implemented and verified on realistic test generation constraints. Preliminary experiments show that both, the proposed constraint solving engine and the decision diagram based hierarchical test generator achieve a very fast performance in comparison to well-known test tools.
Image Quality Assessment and Outliers Filtering in an Image-Based Animal Supervision System

This paper presents a probabilistic framework for the image quality assessment (QA), and filtering of outliers, in an image-based animal supervision system (asup). The proposed framework recognizes asup's imperfect frames in two stages. The first stage deals with the similarity analysis of the same-class distributions. The objective of this stage is to maximize the separability measures by defining a set of similarity indicators (SI) under the condition that the number of permissible values for them is restricted to be relatively low. The second stage, namely faulty frame recognition (FFR), deals with asup's QA training and real-time quality assessment (RTQS). In RTQS, decisions are made based on a real-time quality assessment mechanism such that the majority of the defected frames are removed from the consecutive sub routines that calculate the movements. The underlying approach consists of a set of SI indexes employed in a simple Bayesian inference model. The results confirm that a significant amount of defected frames can be efficiently classified by this approach. The performance of the proposed technique is demonstrated by the classification on a cross-validation set of mixed high and low quality frames. The classification shows a true positive rate of 88.6% while the false negative rate is only about 2.5%.
Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling.
User Selection Methods for Multi-User Downlinks with Multiple-Antenna Terminals

The need for high downlink throughput has led to the consideration of multiple-input multiple-output (MIMO) systems with multi-antenna user terminals. Spatial multiplexing via orthogonal space division multiplexing (OSDM) may be achieved using block diagonalization (BD) techniques. User subset selection is required when the potential user pool exceeds the available transmission resources. Judicious user subset selection will help ensure high system throughput. However, optimum selection requires exhaustive search. We demonstrate how existing antenna selection algorithms may be modified to operate on blocks of the overall composite channel matrix to serve as user selection algorithms for BD-OSDM. Four algorithms are derived. The approach is efficient because no BD pre-coding related computations are needed. Next, BD may employ additional user selection or receive antenna selection on the chosen user subset to help increase the sum rate or minimize the transmission power. We will show how three of the proposed algorithms lend themselves for this purpose with low additional complexity. Numerical results show good sum rate performance for the proposed algorithms especially when receive antenna selection is done on the chosen user subset
ReWAP: Reducing Redundant Transfers for Mobile Web Applications via App-Specific Resource Packaging

Redundant transfer of resources is a critical issue for compromising the performance of mobile Web applications (a.k.a., apps) in terms of data traffic, load time, and even energy consumption. Evidence shows that the current cache mechanisms are far from satisfactory. With lessons learned from how native apps manage their resources, in this paper, we propose the ReWAP approach to fundamentally reducing redundant transfers by restructuring the resource loading of mobile Web apps. ReWAP is based on an efficient mechanism of resource packaging where stable resources are encapsulated and maintained into a package, and such a package shall be loaded always from the local storage and updated by explicitly refreshing. By retrieving and analyzing the update of resources, ReWAP maintains resource packages that can accurately identify which resources can be loaded from the local storage for a considerably long period. ReWAP also provides a wrapper for mobile Web apps to enable loading and updating resource packages in the local storage as well as loading resources from resource packages. ReWAP can be easily and seamlessly deployed into existing mobile Web architectures with minimal modifications, and is transparent to end-users. We evaluate ReWAP based on continuous 15-day access traces of 50 mobile Web apps that suffer heavily from the problem of redundant transfers. Compared to the original mobile Web apps with cache enabled, ReWAP can significantly reduce the data traffic, with the median saving up to 51%. In addition, ReWAP can incur only very minor runtime overhead of the client-side browsers.
Very fast pipelined RSA architecture based on Montgomery's algorithm

This paper present a design of RSA-Encryption using Pipelined radix-2 Montgomery's architecture. The architecture design exploits the algorithm to achieve high speed and efficient computation. The design separates the computation of Montgomery modular multiplication into different clock cycles to achieve high frequency clock. This design supports input from 1 to 14 block data and efficient in the number of total logic element and register. The design has been successfully verified whether functional Verilog RTL simulation, FPGA timing simulation and run in Signal Tap FPGA simulation. The design occupies logic elements 1157, 1030 registers, and able to run up to 261.85 MHz on Altera Cyclone II EP2C35 F672C6. The proposed design has been successfully synthesized using Synopsys with CMOS 0. 18µ technology. The area is 63567.5 µm2 and the delay is 3.35 ns.
Learning optimal striking points for a ping-pong playing robot

In this paper, an approach for learning optimal striking points is proposed. Based on a ball-flight model and a rebound model, a set of reachable striking points within the robot's workspace can be obtained. However, while these striking points are geometrically reachable, their success probability differs substantially due to the robot's nonlinear dynamics, the distance to the ball, the need to reach sufficient velocity as well as the right angle at interception and non-uniform sensitivity to errors. Thus, it is crucial for a ping-pong robotic system to select striking points well. As a successful ball interception is the result of various factors that cannot be modeled straightforwardly, we suggest determining optimal striking points based on a reward function that measures how well the ping-pong ball's trajectory and the racket's movement coincidence. In this approach, we propose to learn a stochastic policy over the reward given the prospective striking point in order to facilitate exploration of a wide range of prospective striking points. The resulting learning method takes both the amount of experience data and its confidence into account to reach optimal solutions reliably. Evaluation with a real robotic system demonstrates the applicability of the proposed method.
Towards Model Based Autonomy for AUV Mission Planning

References R. N. Smith, A. A. Pereira, Y. Chao, P. P. Li, D. A. Caron, B. H. Jones, and G. S. Sukhatme, "Autonomous underwater vehicle trajectory design coupled with predictive ocean models: A case study," in Proceedings of The IEEE International Conference on Robotics and Automation J. Bresina, A. Jonsson, P. Morris, and K. Rajan, "Activity planning for the Mars exploration rovers," in ICAPS, (Monterey, California), 2005. C. R. Anderson, D. A. Siegel, R. M. Kudela, and M. A. Brzezinskic, "Empirical models of toxigenic pseudo-nitzschia blooms: Potential use as a remote detection tool in the Santa Barbara channel," Harmful Algae, vol. 8, pp. 478{492, 2009. J. Das, K. Rajan, S. Frolov, J. Ryan, F. Py, D. Caron, and G. Sukhatme, "Towards marine bloom trajectory prediction for auv mission planning," in Proceedings of the IEEE International Conference on Robotics and Automation, 2010. J. Q. Lane, P. T. Raimondi, and R. M. Kudela, "Development of a logistic regression model for the prediction of toxigenic pseudo-nitzschia blooms in monterey bay, california," Marine Ecology Progress Series, vol. 383, pp. 37{51, 2009. B. Zhang and G. S. Sukhatme, "Adaptive sampling for estimating a scalar field using a robotic boat and a sensor network" in IEEE International Conference on Robotics and Automation, 2007. This work was supported in part by the NOAA MERHAB program under grant NA05NOS4781228 and by NSF as part of the Center for Embedded Network Sensing (CENS) under grant CCR-0120778, by NSF grants CNS-0520305 and CNS-0540420, by the ONR MURI program (grants N00014-09-1-1031 and N00014-08-1-0693) by the ONR SoA program and a gift from the Okawa Foundation, and the David and Lucile Packard Foundation at MBARI Develop shoreside technologies to track and direct sampling of blooms with robotic assets
Opposing Effects of Zac1 and Curcumin on AP-1-Regulated Expressions of S100A7

ZAC, an encoding gene mapped at chromosome 6q24-q25 within PSORS1, was previously found over-expressed in the lower compartment of the hyperplastic epidermis in psoriatic lesions. Cytokines produced in the inflammatory dermatoses may drive AP-1 transcription factor to induce responsive gene expressions. We demonstrated that mZac1 can enhance AP-1-responsive S100A7 expression of which the encoding gene was located in PSORS4 with HaCaT keratinocytes. However, the mZac1-enhanced AP-1 transcriptional activity was suppressed by curcumin, indicating the anti-inflammatory property of this botanical agent and is exhibited by blocking the AP-1-mediated cross-talk between PSORS1 and PSORS4. Two putative AP-1-binding sites were found and demonstrated to be functionally important in the regulation of S100A7 promoter activity. Moreover, we found curcumin reduced the DNA-binding activity of AP-1 to the recognition element located in the S100A7 promoter. The S100A7 expression was found to be upregulated in the lesioned epidermis of atopic dermatitis and psoriasis, which is where this keratinocyte-derived chemoattractant engaged in the pro-inflammatory feedback loop. Understanding the regulatory mechanism of S100A7 expression will be helpful to develop therapeutic strategies for chronic inflammatory dermatoses via blocking the reciprocal stimuli between the inflammatory cells and keratinocytes.
Phong Splatting

Surface splatting has developed into a valuable alternative to triangle meshes when it comes to rendering of highly detailed massive datasets. However, even highly accurate splat approximations of the given geometry may sometimes not provide a sufficient rendering quality since surface lighting mostly depends on normal vectors whose deviation is not bounded by the Hausdorff approximation error. Moreover, current point-based rendering systems usually associate a constant normal vector with each splat, leading to rendering results which are comparable to flat or Gouraud shading for polygon meshes. In contrast, we propose to base the lighting of a splat on a linearly varying normal field associated with it, and we show that the resulting Phong Splats provide a visual quality which is far superior to existing approaches. We present a simple and effective way to construct a Phong splat representation for a given set of input samples. Our surface splatting system is implemented completely based on vertex and pixel shaders of current GPUs and achieves a splat rate of up to 4M Phong shaded, filtered, and blended splats per second. In contrast to previous work, our scan conversion is projectively correct per pixel, leading to more accurate visualization and clipping at sharp features.
Advanced Modeling of MISHFET Devices and their Performance in Current-Mode Class-D Power Amplifiers

GaN HFETs and MISHFETs are promising power devices for RF and microwave power applications. However, the performance of devices can be compromised under some operating conditions. From the device development point of view, device optimization is necessary to obtain the best possible performance. For device modeling and design purposes, the device needs to be characterized and modeled accurately in order to foresee how the device will behave under realistic operating conditions. In this paper, an improved EEHEMT1-based model for GaN MISHFETs, will be introduced. This model is capable of describing the knee region of the device's output characteristics, dispersion effects as well as gate diode behavior accurately. The models will be incorporated in a switched-mode amplifier topology and evaluations will be made to determine the suitability of MISHFETs in these amplifiers.
Localization in long-range ultra narrow band IoT networks using RSSI

Internet of things wireless networking with long-range, low power and low throughput is raising as a new paradigm enabling to connect trillions of devices efficiently. In such networks with low power and bandwidth devices, localization becomes more challenging. In this work we take a closer look at the underlying aspects of received signal strength indicator (RSSI) based localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI has been used for fingerprinting localization where RSSI measurements of GPS anchor nodes have been used as landmarks to classify other nodes into one of the GPS nodes classes. Through measurements we show that a location classification accuracy of 100% is achieved when the classes of nodes are isolated. When classes are approaching each other, our measurements show that we can still achieve an accuracy of 85%. Furthermore, when the density of the GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus improve the possibility of localizing nodes with an error less than 20m from 20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes is localized with an error of less than 50m in our experiment with non-optimized anchor node locations.
Highly Efficient 3 D Nanofocusing Plasmonic Waveguide

We have demonstrated experimentally a highly efficient on-chip three-dimensional (3D) linearly tapered metalinsulator-metal (MIM) nanoplasmonic photon compressor (3D NPC) with a final aperture size of 14 x 80 nm. An optimized and linearly tapered MIM gap plasmon waveguide could theoretically reduce the excessive losses that would occur during nanofocusing processes. In simulation study, this approach could enable nanofocusing into a 2 x 5 nm area with the coupling loss and maximum E enhancement of 2.5 dB and 3.0 × 10, respectively. We fabricated the 3D NPC on a chip employing electron beaminduced deposition and demonstrated its highly localized light confinement using a two-photon photoluminescence (TPPL) technique. From the TPPL measurements, we experimentally estimated an intensity enhancement of 400 within a 14 x 80 nm cross-sectional area and a coupling efficiency of -1.3 dB (or 74% transmittance).
In vivo evidences that insulin regulates human polymorphonuclear neutrophil functions

Polymorphonuclear neutrophils (PMN) are able to destroy invasive mircoorganisms by a wide variety of functions. Whereas insulin does not stimulate hexose transport in PMN, previous reports have clearly shown that this hormone regulates glucose metabolism inside this cell, raising the question of insulin action on PMN functions in humans. It is interesting that in vitro studies established a strong relationship between specific binding of insulin to its PMN membrane receptor and the activation of the main PMN functions. Therefore, investigation in healthy subjects under strict euglycemia and physiological insulinemia was performed to understand the in vivo‐specific action of insulin on PMN functions without hyperglycemia interferences. We determined numerous PMN functions before and after hyperinsulinemia (0.5 mU/kg/min) and euglycemia (0.9 g/l) clamp for 4 h in eight adult healthy volunteers (24±6 years). The total number of PMN and the number of PMN expressing CD11b, CD15, CD62L, and CD89 were significantly increased over baseline (P<0.001), whereas the density of these receptors was down‐regulated (P<0.01) by insulin. PMN chemotaxis (+117%, P<0.05), phagocytosis (+29%, P<0.001), and bactericidal (+17–25%, P<0.001) capacities were increased during the insulin clamp (P<0.05). Therefore, insulin treatment may modulate PMN functions not only by attainment of a better metabolic control, as suggested by in vivo studies in diabetic patients, but also through a direct effect of insulin.
Video shot boundary detection with local feature post refinement

Video shot boundary detection is a fundamental step for content base video analysis and has been widely studied in recent years. In this paper, a novel shot boundary detection algorithm is proposed. The algorithm uses feature space kernel smoothing to segment video into shots. The method is demonstrated to have high accuracy in both cuts and gradual transition detection. For flashlights and fast background change which cause the false detection, a post refinement strategy using local feature analysis is also studied in this paper. The effectiveness of the method is also verified by the experiments.
Understanding the Challenges of Introducing Self-driven Blended Learning in a Restrictive Ecosystem - Step 1 for Change Management: Understanding Student Motivation

This paper describes the implementation of a prototype for blended learning in a Software Engineering course at the Cooperative State University Baden-Wurttemberg in Karlsruhe. The University has certain particularities that distinguish it from other Universities because students alternate quarters between study and work. Thus, students receive a salary during their three years towards earning a Bachelor Degree and attendance is mandatory. In cohorts, around 30 students spend an average day with at least 5 hours of frontal lecture in the same classroom. Software Engineering takes up about 5 hours a week of in-class time in their second year of study and is the first course students have seen with a self-driven, blended learning format. The paper describes the set-up of the learning environment based on known research results of motivational factors. Based on an exploratory survey of 59 students, these motivation factors are compared to students’ motivations and their realizations in traditional and self-driven lecture format. Answers revealed that change presents a major challenge for most students and identifies the need for explicit habit building, change management and improved serving of students’ basic needs in a grade-based ecosystem.
Multi-dimension QoE model based optimization for resource allocation in HetNets over SDN

With the deployment of ultra-dense HetNets, the inter-cell resource allocation requires new network solutions to handle differentiated user demands, while software defined network (SDN) has emerged as a solution to it for imbalanced user needs, as well as enabling efficient resource utilization and QoE. Under such motivations, we employ a QoE assessment model over SDN to analyze the impact factors on user demands from various dimensions, including network conditions, equipment characteristics, ambient environment, and the user themselves. In this contexts, we propose a dynamic inter-cell wireless resource allocation scheme which expends and provides a more generalized architecture for heterogeneous radio access networks, especially in terms of resource allocation based on QoE requirements with support of SDN. Analytical and experimental results demonstrate that the proposed scheme has improved more than 10% of user QoE satisfaction due to the high efficiency and extra flexibility of optimization over more dimension of heterogeneity provided by radio resource allocation scheme among SDN in HetNets.
A New Model for Generating Multimodal Referring Expressions

We present a new algorithm for the generation of multimodal referring expressions (combining language and deictic gestures). 1 The approach differs from earlier work in that we allow for various gradations of preciseness in pointing, ranging from unambiguous to vague pointing gestures. The model predicts that linguistic properties realized in the generated expression are co-dependent on the kind of pointing gesture included. The decision to point is based on a tradeoff between the costs of pointing and the costs of linguistic properties, where both kinds of costs are computed in empirically motivated ways. The model has been implemented using a graph-based generation algorithm.