Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust Aware Resilient Geographic Routing in Wireless Ad Hoc and Sensor Networks

The objective of the paper is to propose trust aware routing method for cooperative and resilient geographic routing in Wireless Ad-hoc and Sensor Networks (WASNs). The proposed method calculates the trust value on the basis of node behavior in routing the packets. The proposed method is designed to have the features such as self-adaptability, low overhead, and dependability which are missing in the existing trust models. With the trust values, the proposed method detects and isolates the malicious nodes dynamically during the routing process. The simulation results obtained using the network simulator ns-2 shows the efficiency of the proposed trust model.
Test Scheduling in an IEEE P1687 Environment with Resource and Power Constraints

In contrast to IEEE 1149.1, IEEE P1687 allows, through segment insertion bits, flexible scan paths for accessing on-chip instruments, such as test, debug, monitoring, measurement and configuration features. Flexible access to embedded instruments allows test time reduction, which is important at production test. However, the test access scheme should be carefully selected such that resource constraints are not violated and power constraints are met. For IEEE P1687, we detail in this paper session-based and session-less test scheduling, and propose resource and power-aware test scheduling algorithms for the detailed scheduling types. Results using the implementation of our algorithms shows on ITC'02-based benchmarks significant test time reductions when compared to non-optimized test schedules.
GluN2B-containing NMDA receptors and AMPA receptors in medial prefrontal cortex are necessary for odor span in rats

Working memory is a type of short-term memory involved in the maintenance and manipulation of information essential for complex cognition. While memory span capacity has been extensively studied in humans as a measure of working memory, it has received considerably less attention in rodents. Our aim was to examine the role of the N-methyl-D-aspartate (NMDA) and α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptors in odor span capacity using systemic injections or infusions of receptor antagonists into the medial prefrontal cortex (mPFC). Long Evans rats were trained on a well-characterized odor span task (OST). Initially, rats were trained to dig for a food reward in sand followed by training on a non-match to sample discrimination using sand scented with household spices. The rats were then required to perform a serial delayed non-match to sample procedure which was their odor span. Systemic injection of the broad spectrum NMDA receptor antagonist 3-(2-Carboxypiperazin-4-yl)propyl-1-phosphonic acid (CPP) (10 mg/kg) or the GluN2B-selective antagonist Ro 25-6981 (10 mg/kg but not 6 mg/kg) significantly reduced odor span capacity. Infusions of the GluN2B- selective antagonist Ro 25-6981 (2.5 μg/hemisphere) into mPFC reduced span capacity, an effect that was nearly significant (p = 0.069). Infusions of the AMPA receptor antagonist 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) (1.25 μg/hemisphere) into mPFC reduced span capacity and latency for the rats to make a choice in the task. These results demonstrate span capacity in rats depends on ionotropic glutamate receptor activation in the mPFC. Further understanding of the circuitry underlying span capacity may aid in the novel therapeutic drug development for persons with working memory impairments as a result of disorders such as schizophrenia and Alzheimer’s disease.
PROPANE: A Progressive Panorama Streaming Protocol to Support Interactive 3D Virtual Environment Exploration on Graphics-Constrained Devices

Image-Based Rendering (IBR) has become widely known by its relatively low requirements for generating new scenes based on a sequence of reference images. This characteristic of IBR shows a remarkable potential impact in rendering complex 3D virtual environments on graphics-constrained devices, such as head-mounted displays, set-top boxes, media streaming devices, and so on. If well exploited, IBR coupled with remote rendering would enable the exploration of complex virtual environments on these devices. However, remote rendering requires the transmission of a large volume of images. In addition, existing solutions consider limited and/or deterministic navigation schemes as a means of decreasing the volume of streamed data. This article proposes the PROgressive PANorama StrEaming protocol (PROPANE) to offer users a smoother virtual navigation experience by prestreaming the imagery data required to generate new views as the user wanders within a 3D environment. PROPANE is based on a very simple yet effective trigonometry model and uses a strafe (lateral movement) technique to minimize the delay between image updates at the client end. This article introduces the concept of key partial panoramas, namely panorama segments that cover movements in any direction by simply strafing from an appropriate key partial panorama and streaming the amount of lost pixels. Therefore, PROPANE can provide a constrained device with sufficient imagery data to cover a future user's viewpoints, thereby minimizing the impact of transmission delay and jitter. PROPANE has been implemented and compared to two baseline remote rendering schemes. The evaluation results show that the proposed technique outperforms the selected and closely related existing schemes by minimizing the response time while not limiting the user to predefined paths as opposed to previous protocols.
Modeling Vocal Fold Motion with a Continuum Fluid Dynamic Model, I. Derivation and Analysis

Vocal fold (VF) motion is fundamental to voice production and diagnosis in speech and health sciences. The motion is a consequence of air flow interacting with elastic vocal fold structures. Motivated by existing lumped mass models and known flow properties, we propose to model the continuous shape of vocal fold in motion by the two dimensional compressible Navier-Stokes equations coupled with an elastic damped driven wave equation on the fold cover. In this paper, instead of pursuing a direct two dimensional numerical simulation, we derive reduced quasi-one-dimensional model equations by averaging two dimensional solutions along the flow cross sections. We then analyze the oscillation modes of the linearized system about a flat fold, and found that the fold motion goes through a Hopf bifurcation into temporal oscillation if the flow energy is sufficient to overcome the damping in the fold consistent with the early models. We also analyze the further reduced system under the quasi-steady approximation and compare the resulting vocal fold equation in the small vibration regime with that of the Titze model. Our model shares several qualitative features with the Titze model yet differs in the specific form of energy input from the air flow to the fold. Numerical issues and results of the quasi-one-dimensional model system will be presented in part II (view resulting web VF animation at this http URL).
Gesture-based robot's long-range navigation

In this paper, we deal with the problem of longrange navigating the robot in unknown environment. The robot captures the environment video in remote field, and the video is transmitted over the Internet in real-time and displayed on the control terminal. On the control side, according to the received video, the operator sends control instructions to guide the robot by using predetermined gestures. The gestures are recognized by the sensor, and convert to instructions such as forward, backward, turning left, turning right and so on, and then the instructions are transmitted to the robot over the internet. Therefore, we complete a close-loop feedback control of robot's long-range navigation. In gesture recognition, we propose a novel way to capture the tracks of users' arms by utilizing the Kinect - a product of Microsoft. With the skeleton tracing ability of Kinect, we can obtain the coordinates sequence of arms. Then we establish the library of gestures and recognize some given gestures by using DTW (Dynamic Time Warping) algorithm. In communications, we choose H.264 video codec standard for video encoding and decoding, and combine with the network communication technology, to ensure the real-time requirement of robot teleoperation.
Systemic Sustainability in RtI Using Intervention-Based Scheduling Methodologies

This study evaluated a scheduling methodology referred to as intervention-based scheduling to address the problem of practice regarding the fidelity of implementing Response to Intervention (RtI) in an existing school schedule design. Employing panel data, this study used fixed-effects regressions and first differences ordinary least squares (OLS) regression models to analyze the impact of intervention-based scheduling on student reading achievement and growth. Findings suggest that an intervention-based scheduling design holds promise for addressing the commonly reported concern of implementing interventions with fidelity. Results indicate that students obtained higher rates of achievement and growth in the area of reading while receiving instruction through an intervention-based schedule design. Students accessing Tier 2 interventions demonstrated higher growth rates in reading than those not accessing Tier 2 interventions. However, additional research is required to determine the extent to which intervention-based scheduling may influence other educational settings.
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization

Iterative Hard Thresholding (IHT) is a class of projected gradient descent methods for optimizing sparsity-constrained minimization models, with the best known efficiency and scalability in practice. As far as we know, the existing IHT-style methods are designed for sparse minimization in primal form. It remains open to explore duality theory and algorithms in such a non-convex and NP-hard problem setting. In this paper, we bridge this gap by establishing a duality theory for sparsity-constrained minimization with $\ell_2$-regularized loss function and proposing an IHT-style algorithm for dual maximization. Our sparse duality theory provides a set of sufficient and necessary conditions under which the original NP-hard/non-convex problem can be equivalently solved in a dual formulation. The proposed dual IHT algorithm is a super-gradient method for maximizing the non-smooth dual objective. An interesting finding is that the sparse recovery performance of dual IHT is invariant to the Restricted Isometry Property (RIP), which is required by virtually all the existing primal IHT algorithms without sparsity relaxation. Moreover, a stochastic variant of dual IHT is proposed for large-scale stochastic optimization. Numerical results demonstrate the superiority of dual IHT algorithms to the state-of-the-art primal IHT-style algorithms in model estimation accuracy and computational efficiency.
Neural Network Underlying Recovery from Disowned Bodily States Induced by the Rubber Hand Illusion

We used functional magnetic resonance imaging to investigate how causal influences between brain regions during the rubber hand illusion (RHI) are modulated by tactile and visual stimuli. We applied needle rotations during the RHI in two different ways: one was with the real hand (reinstantiation by tactile stimuli, R-TS) and the other was with the rubber hand (reinstantiation by visual stimuli, R-VS). We used dynamic causal modeling to investigate interactions among four relevant brain regions: the ventral premotor cortex (PMv), the intraparietal sulcus (IPS), the secondary somatosensory cortex (SII), and the lateral occipitotemporal cortex (LOC). The tactile aspects of needle rotations changed the effective connectivity by directly influencing activity in the SII, whereas visual aspects of needle rotation changed the effective connectivity by influencing both the SII and the LOC. The endogenous connectivity parameters between the IPS and the PMv were reduced significantly in the R-TS condition. The modulatory parameters between the IPS and the PMv were enhanced significantly in the R-TS condition. The connectivity patterns driven by disowned bodily states could be differentially modulated by tactile and visual afferent inputs. Effective connectivity between the parietal and frontal multimodal areas may play important roles in the reinstantiation of body ownership.
Editing support vector machines

A support vector machine constructs an optimal hyperplane from a small set of samples near the boundary. This makes it sensitive to these specific samples and tends to result in machines either too complex with poor generalization ability or too imprecise with high training error, depending on the kernel parameters. In this paper, we present an improved version of the method, called editing support vector machine (ESVM), which removes some samples near the boundary from the training set. Experiments show that for cases that the two classes are overlapped, ESVM can get better generalizing ability, and ESVM is also more robust with noises.
Assessing the Value of Contributions in Tagging Systems

Assessing the value of individual users' contributions in peer-production systems is paramount to the design of mechanisms that support collaboration and improve users' experience. For instance, to incentivize contributions, file-sharing systems based on the BitTorrent protocol equate value with volume of contributed content and use a prioritization mechanism to reward users who contribute more. This approach and similar techniques used in resource-sharing systems rely on the fact that the physical resources shared among users are easily quantifiable. In contrast, information-sharing systems, like social tagging systems, lack the notion of a physical resource unit (e.g., content size, bandwidth) that facilitates the task of evaluating user contributions. For this reason, the issue of estimating the value of user contributions in information sharing systems remains largely unexplored. This paper introduces this problem and takes the first steps towards a solution. More precisely, it presents a framework to design algorithms that estimate the value of user contributions in tagging systems, proposes three complementary success criteria for potential solutions, and outlines the methodological evaluation challenges.
Deriving Mesoscale Surface Current Fields from Multi-Sensor Satellite Data

Sequential multi-sensor satellite images from Envisat ASAR and WiFS are used for the computation of mesoscale surface currents in the southestern Baltic Sea (Southern Baltic Proper). Marine surface films of different origin and accumulated algae at the water surface are imaged by the sensors working in the optical, infrared, and microwave part of the electromagnetic spectrum and can thus be used as tracers for the local motion of the sea surface. Taking advantage of the sufficiently short time lags between the multiple image acquisitions (from less than one hour to one day) and of the high spatial coverage we calculated surface motion fields by enhancing and combining image-processing techniques. Our computed two-dimensional surface current fields are compared with, and they complement, existing data from numerical models.
The design of RFID dual frequency integrated technology based on prison application

With the Internet of Things system rapidly development, it has being used in more and more various industries. As one of the important sensor technology, radio frequency identification (RFID) sensor becomes indispensable technology to a lot of applications. This paper analyzes the frequency characteristic in RFID and the principle of classification, focuses on design the dual frequency integrated technique, puts forward an edge positioning solution for complicated environment. This innovative design extends for most other mobile tracking, location positioning, and real time monitoring and so on fields.
Interactome analysis of the six cotton 14-3-3s that are preferentially expressed in fibres and involved in cell elongation

Proteins of the 14-3-3 family regulate a divergent set of signalling pathways in all eukaryotic organisms. In this study, several cDNAs encoding 14-3-3 proteins were isolated from a cotton fibre cDNA library. The Gh14-3-3 genes share high sequence homology at the nucleotide level in the coding region and at the amino acid level. Real-time quantitative RT-PCR analysis indicated that the expression of these Gh14-3-3 genes is developmentally regulated in fibres, and reached their peak at the stage of rapid cell elongation of fibre development. Furthermore, overexpression of Gh14-3-3a, Gh14-3-3e, and Gh14-3-3L in fission yeast promoted atypical longitudinal growth of the host cells. Yeast two-hybrid analysis revealed that the interaction between cotton 14-3-3 proteins is isoform selective. Through yeast two-hybrid screening, 38 novel interaction partners of the six 14-3-3 proteins (Gh14-3-3a, Gh14-3-3e, Gh14-3-3f, Gh14-3-3g, Gh14-3-3h, and Gh14-3-3L), which are involved in plant development, metabolism, signalling transduction, and other cellular processes, were identified in cotton fibres. Taking these data together, it is proposed that the Gh14-3-3 proteins may participate in regulation of fibre cell elongation. Thus, the results of this study provide novel insights into the 14-3-3 signalling related to fibre development of cotton.
Pegylated liposomal-encapsulated doxorubicin in cutaneous composite lymphoma

Background: Cutaneous composite lymphomas are very rare. Their treatment depends upon the different contributing lymphoma entities. Peripheral T-cell lymphoma, not otherwise specified, (PTCL-NOS) represents an aggressive lymphoma subtype. Follicular cutaneous B-cell lymphoma (FCBCL) runs an indolent course. Treatment with pegylated liposomal encapsulated doxorubicin (PLE-DOXO) has yet not been reported in this entity. Case presentation: A 73-year-old male patient presented with 3 rapidly growing, painful nodules on his left leg. He was diagnosed as composite cutaneous lymphoma consisting of PTCL-NOS and FCBCL. All lesions had been surgically removed. Staging was unremarkable. After 4 months a relapse occurred with involvement of inguinal lymph nodes and systemic treatment with PEL-DOXO 20 mg/ m2 every 3 weeks was initiated. After 6 cycles PLE-DOXO, which were well tolerated without grade 3 or 4 toxicities, a mixed response was obtained with complete remission of cutaneous lesions. Lymph nodes were treated by radiotherapy. A second relapse occurred after 8 months and various polychemotherapy regimens were applied without remission. The overall survival was 28 months. Conclusion: PEL-DOXO is a possible initial systemic treatment in case of PCTL-NOS. Whether polychemotherapy offers an advantage for survival remains questionable but further investigations are needed.
Vision-based Raising Hand Detection in Classroom

Raising hand is one of the most important types of interaction between students and lecturers in classroom. When an automatic system can be installed in classroom to figure out which students raise their hands, it is possible to design more advanced applications for education goals. This paper proposes a system that employs computer vision technologies to automatically detect the student action of raising hand. We first design a foreground extraction method to segment student bodies in consecutive video frames. Next, a shape-like appearance signature that represents human gestures is designed based on the scale-invariant feature transform (SIFT) descriptor. A gesture classifier for raising hands is also designed using the support vector machine (SVM) approach. This paper designs several experiments to demonstrate the performance of our proposed system in a real classroom.
ASIStint: an interactive ASIS interpreter

ASIStint is an interactive ASIS interpreter with scripting facilities. It may be usedfor learning ASIS, i.e. the user may inieractively try out the eflects of the various ASIS queries It might also be used as an assistant (sic. , when experimenting with ASIS queries, e.g. in order to discover a way of implementing a part of an ASIS application, or to correct itYet another use is debugging and testing an ASIS implementation. Input-output of a session may be recorded, and then be reprayed.
A Fluorescent Bioreporter for Acetophenone and 1-Phenylethanol derived from a Specifically Induced Catabolic Operon

The β-proteobacterium Aromatoleum aromaticum degrades the aromatic ketone acetophenone, a key intermediate of anaerobic ethylbenzene metabolism, either aerobically or anaerobically via a complex ATP-dependent acetophenone carboxylase and a benzoylacetate-CoA ligase. The genes coding for these enzymes (apcABCDE and bal) are organized in an apparent operon and are expressed in the presence of the substrate acetophenone. To study the conditions under which this operon is expressed in more detail, we constructed a reporter strain by inserting a gene fusion of apcA, the first gene of the apc-bal operon, with the gene for the fluorescent protein mCherry into the chromosome of A. aromaticum. The fusion protein indeed accumulated consistently with the expression pattern of the acetophenone-metabolic enzymes under various growth conditions. After evaluating and quantifying the data by fluorescence microscopy, fluorescence-based flow cytometry and immunoblot analysis, mCherry production was found to be proportional to the applied acetophenone concentrations. The reporter strain allowed quantification of acetophenone within a concentration range of 50 μM (detection limit) to 250 μM after 12 and 24 h. Moreover, production of the Apc-mCherry fusion protein in the reporter strain was highly specific and responded to acetophenone and both enantiomers of 1-phenylethanol, which are easily converted to acetophenone. Other analogous substrates showed either a significantly weaker response or none at all. Therefore, the reporter strain provides a basis for the development of a specific bioreporter system for acetophenone with an application potential reaching from environmental monitoring to petroleum prospecting.
Mixed Precision Comparison in Reconfigurable Systems

Customisable data formats provide an opportunity for exploring trade-offs in accuracy and performance of reconfigurable systems. This paper introduces a novel methodology for mixed-precision comparison, which improves comparison performance by using reduced-precision datapaths while maintaining accuracy by using high-precision datapaths. Our methodology adopts reduced-precision data-paths for preliminary comparison, and high-precision data-paths when the accuracy for preliminary comparison is insufficient. We develop an analytical model for performance estimation of the proposed mixed-precision methodology. Optimisation based on integer linear programming is employed for determining the optimal precision and resource allocation for each of the datapaths. The effectiveness of our approach is evaluated using a common collision detection problem. Performance gains of 4 to 7.3 times are obtained over baseline fixed-precision designs for the same FPGAs. With the help of the proposed mixedprecision methodology, our FPGA designs are 15.4 to 16.7 times faster than software running on multi-core CPUs with the same technology. Keywords-mixed precision, reconfigurable system.