Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant Growth Retardation and Conserved miRNAs Are Correlated to Hibiscus Chlorotic Ringspot Virus Infection

Virus infection may cause a multiplicity of symptoms in their host including discoloration, distortion and growth retardation. Hibiscus chlorotic ringspot virus (HCRSV) infection was studied using kenaf (Hibiscus cannabinus L.), a non-wood fiber-producing crop in this study. Infection by HCRSV reduced the fiber yield and concomitant economic value of kenaf. We investigated kenaf growth retardation and fluctuations of four selected miRNAs after HCRSV infection. Vegetative growth (including plant height, leaf size and root development) was severely retarded. From the transverse and radial sections of the mock and HCRSV-infected kenaf stem, the vascular bundles of HCRSV-infected plants were severely disrupted. In addition, four conserved plant developmental and defence related microRNAs (miRNAs) (miR165, miR167, miR168 and miR171) and their respective target genes phabulosa (PHB), auxin response factor 8 (ARF8), argonaute 1 (AGO1) and scarecrow-like protein 1 (SCL1) displayed variation in expression levels after HCRSV infection. Compared with the mock inoculated kenaf plants, miR171 and miR168 and their targets SCL1 and AGO1 showed greater fluctuations after HCRSV infection. As HCRSV upregulates plant SO transcript in kenaf and upregulated AGO1 in HCRSV-infected plants, the expression level of AGO1 transcript was further investigated under sulfite oxidase (SO) overexpression or silencing condition. Interestingly, the four selected miRNAs were also up- or down-regulated upon overexpression or silencing of SO. Plant growth retardation and fluctuation of four conserved miRNAs are correlated to HCRSV infection.
Detection of Intermodal Proprioceptive-Visual Contingency as a , Potential Basis of Self-Perception in Infancy

Five-month-old infants can detect the invariant relationship between their own leg motion and a video display of that motion. In three experiments they discriminated between a perfectly contingent live display of their own leg motion and a noncon- tingent display of self or a peer. They showed this discrimination by preferential fixation of the noncontingent display. This effect was evident even when the infant's direct view of his or her own body was occluded, eliminating video image discrim- ination on the basis of an intramodal visual comparison between the sight of self- motion and the video display of that motion. These findings suggest that the con- tingency provided by a live display of one's body motion is perceived by detecting the invariant intermodal relationship between proprioceptive information for motion and the visual display of that motion. The detection of these relations may be fun- damental to the development of self-perception in infancy. In addition, though 3- month-olds did not show significant discrimination of the contingent and noncon- tingent displays, they did show significantly more extreme looking proportions to the two displays than did the 5-month-olds. This may reflect the infant's progression from self to social orientation. Lewis and Brooks-Gunn (1979) found that by the end of the first year of life, infants are able to discriminate a "live" video image of the self from a recorded image of the self or a peer. The authors propose that this self-rec- ognition is primarily based on the detection of contingent visual stimulation from the live video image. That is, movement of the infant's hand, for example, results in comparable movement of the hand in the video image. Furthermore, they propose that the earliest stages of self-perception are probably based on the infant's detection of some form of response
Design and simulation of a discrete time controller for regulating temperature in a scale greenhouse

This paper describes the process of designing a temperature controller working in discrete time, using as manipulated variables: thermal power applied from a heat flow supply, in combination with the variation of outdoor air volume flow. As a preliminary step, a dynamic model was analytically derived to describe the behavior of the temperature as a function of the variables: thermal power and air volume flow. An experimental procedure was performed to determine the particular parameters of the real system. Among others specific thermal power, surface thermal conductivity between the greenhouse cover and the environment, heat dissipation coefficient of the incoming airflow. With the values obtained proceeded to make a simulation of the greenhouse on scale as a representative of a physical system. The proposed controller was designed based on the limitations and operating ranges of the real system variables for manipulating: up to 20 watts for the heater in a volume of 5750 cm3, from 0°C of external temperature up to 12°C. By including the air flow as an input variable the system became nonlinear but designed controller was able to maintain the inner temperature between acceptable range for tested potato plants. At a simulation work, it was added a warm air supply at a higher temperature than the outside one. In addition to heating, warm air was also used to increase temperature. This work is the basis to build a mechanism that will be implemented for temperature control which shall carry out, in a full-scale greenhouse in which the efficiency of the control system will be evaluated to protect a crop against the frost weather phenomenon.
A unified approach of factor models and neighbor based methods for large recommender systems

Matrix factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this paper, we propose a hybrid approach that alloys an improved MF and the so-called NSVD1 approach, resulting in a very accurate factor model. After that, we propose a unification of factor models and neighbor based approaches, which further improves the performance. The approaches are evaluated on the Netflix Prize dataset, and they provide very low RMSE, and favorable running time. Our best solution presented here with Quiz RMSE 0.8851 outperforms all published single methods in the literature.
Secure Routing using Clustering Algorithm

ABSTRCAT Wireless sensor network are build up of various autonomous sensors which are responsible for monitoring environmental or physical conditions, such as temperature, sound and pressure. And pass their data through the network to the sink node.There are various applications for wireless sensor network, and security is very important for many of them. Wireless sensor network has some key constraints such as limited energy resources, lack of infrastructure. All these constraints impose some security challenges. Wireless sensor network’s development is originally motivated by military applications such as battlefield surveillance. Due to broadcast nature of transmission medium, also resource limitation on sensor nodes and their uncontrolled environments where they are left unattended, due to which these networks are susceptible to many attacks. Hence there is need of security mechanism in WSN. In this paper, secure DRINA algorithm is implemented for secure data transmission. Data routing in Network Aggregation (DRINA) is routing protocol which is designed for data aggregation in wireless sensor network. The main feature of DRINA is it provides best aggregation than the INFRA and SPT algorithms[1].
The Kinetics of Early T and B Cell Immune Recovery after Bone Marrow Transplantation in RAG-2-Deficient SCID Patients

The kinetics of T and B cell immune recovery after bone marrow transplantation (BMT) is affected by many pre- and post-transplant factors. Because of the profoundly depleted baseline T and B cell immunity in recombination activating gene 2 (RAG-2)-deficient severe combined immunodeficiency (SCID) patients, some of these factors are eliminated, and the immune recovery after BMT can then be clearly assessed. This process was followed in ten SCID patients in parallel to their associated transplant-related complications. Early peripheral presence of T and B cells was observed in 8 and 4 patients, respectively. The latter correlated with pre-transplant conditioning therapy. Cells from these patients carried mainly signal joint DNA episomes, indicative of newly derived B and T cells. They were present before the normalization of the T cell receptor (TCR) and the B cell receptor (BCR) repertoire. Early presentation of the ordered TCR gene rearrangements after BMT occurred simultaneously, but this pattern was heterogeneous over time, suggesting different and individual thymic recovery processes. Our findings early after transplant could suggest the long-term patients' clinical outcome. Early peripheral presence of newly produced B and T lymphocytes from their production and maturation sites after BMT suggests donor stem cell origin rather than peripheral expansion, and is indicative of successful outcome. Peripheral detection of TCR excision circles and kappa-deleting recombination excision circles in RAG-2-deficient SCID post-BMT are early markers of T and B cell reconstitution, and can be used to monitor outcome and tailor specific therapy for patients undergoing BMT.
Boundary Element Model Coupled with Finite Element Model for Dynamic Soil-Pile Interaction

The Boundary Element Method coupled with the Finite Element Method is used to model the dynamic interaction of soil – pile. The system considered is a single pile embedded in a viscoelastic half space. The system is subjected to upward propagating harmonic shear wave. The displacement of the pile has to be found. The pile is modelled using the finite elements and the soil is modelled with boundary element. A computer program using FORTRAN is developed for the purpose of this study. A parametric study is made in this study . The parameters are the ratio of modulus of elasticity of the pile to the modulus of elasticity of the soil, length of pile, diameter of pile and frequency of the shear waves. The result of the analysis yields conclusions that give an insight into the dynamic interaction behavior of the soil-pile-structure system.
Attributed-Based Access Control for Multi-authority Systems in Cloud Storage

Cipher text-Policy Attribute-base Encryption (CP-ABE) is regarded as one of the most suitable technologies for data access control in cloud storage. In almost all existing CP-ABE schemes, it is assumed that there is only one authority in the system responsible for issuing attributes to the users. However, in many applications, there are multiple authorities co-exist in a system and each authority is able to issue attributes independently. In this paper, we design an access control framework for multi-authority systems and propose an efficient and secure multi-authority access control scheme for cloud storage. We first design an efficient multi-authority CP-ABE scheme that does not require a global authority and can support any LSSS access structure. Then, we prove its security in the random oracle model. We also propose a new technique to solve the attribute revocation problem in multi-authority CP-ABE systems. The analysis and simulation results show that our multi-authority access control scheme is scalable and efficient.
Evaluation of Routing Protocols for Vehicular Ad Hoc Networks in Typical Road Traffic Scenarios

Vehicular multi-hop ad hoc networks (VANETs) enable the exchange of information between vehicles without any fixed infrastructure. The application range of such networks may cover safety related applications like the warning of drivers about accidents or congestions as well as Internet access e.g. via gateways along the road. The varying conditions in VANETs introduce high requirements on the routing protocols being used. Thus, we developed a realistic freeway mobility model and evaluated the performance of AODV, DSR, FSR and TORA in typical freeway traffic scenarios on the basis network simulations. The results show that AODV performs best in most of the simulated traffic situations, followed by FSR and DSR, while TORA is inapplicable for VANETs.
Airborne sensor and perception management: A conceptual approach for surveillance UAS

In this article, we present the concept of an integrated perception and sensor management function for airborne platforms with a focus on optimal resource allocation considering domain driven requirements. It is especially designed for small UAVs, where the shortage of weight, space and power has to be addressed. We propose a dynamic composition of algorithmic chains from individual perception modules in order to satisfy given perceptional tasks. A toy problem in the area of road vehicle tracking and detection is used to explain the resulting system in detail, consisting mainly of a Perception Solver, Processing Coordinator and Result Validator.
Approximate Calculation about Standard Normal Distribution with Genetic Programming

Normal distribution is a most widely used probability distribution in engineering calculation and analysis, which is commonly transformed into standard normal distribution to research. This paper presents a new hybrid method of genetic programming and least square method to calculate function values of standard normal distribution, based on determining the function value of standard normal distribution by checking table have many limits and bring huge inconvenience to the engineering application. The simulating results show that the algorithm has the advantages of high speed and precision, easy for using.
Secrecy rate optimization for a MIMO secrecy channel based on Stackelberg game

In this paper, we consider a multi-input-multi-output (MIMO) wiretap channel with a multi-antenna eavesdropper, where a private cooperative jammer is employed to improve the achievable secrecy rate. The legitimate user pays the legitimate transmitter for its secured communication based on the achieved secrecy rate. We first approximate the legitimate transmitter covariance matrix by employing Taylor series expansion, then this secrecy rate problem can be formulated into a Stackelberg game based on a fixed covariance matrix of the transmitter, where the transmitter and the jammer try to maximize their revenues. This secrecy rate maximization problem is formulated into a Stackelberg game where the jammer and the transmitter are the leader and follower of the game, respectively. For the proposed game, Stackelberg equilibrium is analytically derived. Simulation results are provided to show that the revenue functions of the legitimate user and the jammer are concave functions and the Stackelberg equilibrium solution has been validated.
MOSAIC - A Mobile Peer-to-Peer Networks-Based 3D Streaming Supplying Partner Protocol

The rapid spread of wireless mobile devices and the advances of wireless communication have fueled the interest about streaming 3D graphics on mobile devices to be used in augmented reality based classes of applications. In these types of applications, a real world is mapped into the virtual world and thin mobile devices are employed to navigate in the virtual simulated environment (VE). In evidence, one of the prime difficulties in 3D streaming over thin mobile devices consists of the limited mobile resources and capabilities, i.e., low processing power, limited storage capacity, limited graphics’ hardware and graphics’ accelerator making it very difficult for mobile devices to render and process large and complex 3D scenes. So far, a significant body of work has been dedicated to the challenges of mobile networks-based 3D streaming such as streaming performance, and bandwidth limitation. On the downside, very few studies have been committed to the mobile supplying partner strategies aiming at determining the peer that owns the correct information and that possesses enough bandwidth to send the required data quickly and efficiently to other peers in need. In this paper, we propose MOSAIC, our supplying partner strategy protocol for mobile networks-based 3D streaming. MOSAIC is based on the quick discovery of multiple supplying partners, by optimizing the time required by peers to acquire data, avoiding unnecessary messages propagation and network congestion, and decreasing the network bandwidth over utilization.
Automatic Runtime Customization for Variability Awareness on Multicore Platforms

Driven by increasingly aggressive CMOS technology scaling, sub-wavelength lithography is incurring more evident variability in the technology parameters of the semiconductors fabrication process. That variability results in otherwise identical designs displaying very different performances, power consumption levels and lifespans once fabricated. Hence, process variability may lead to execution uncertainties, impacting the expected quality of service and energy efficiency of the running software. As such uncertainties are intolerable in certain application domains such as automotive and avionic infotainment systems, it has become a persistent necessity to customize runtime engines to introduce measures for variability awareness in task allocation decisions. The purpose of compensating process variability is to avoid performance degradation and energy inefficiency. And customization is meant to take place automatically through exporting the variability-impacted platform characteristics - such as per-core manufactured clock frequency - for the runtime library to perform variability-aware workload sharing on the target cores of the hardware platform. Hence, we can eventually achieve noticeable optimization results, not only on the system performance and energy consumption levels, but also in increasing productivity in systems development, testing, integration, and marketing. This paper presents a holistic approach starting from a system model of the target multicore platform, to building and integrating the runtime library, and finally highlighting the optimization results achieved through the proposed runtime customization paradigm.
Performance comparison of Eulerian kinetic Vlasov code between flat-MPI parallelism and hybrid parallelism on Fujitsu FX100 supercomputer

The present study deals with the Vlasov simulation code, which solves the first-principle kinetic equations called the Vlasov equation for space plasma. In the present study, a five-dimensional Vlasov code with two spatial dimension and three velocity dimensions is parallelized with two methods, the flat-MPI and the MPI-OpenMP hybrid parallelism. The two types of the parallel Vlasov code are benchmarked on massively-parallel supercomputer Fujitsu FX100, which has been developed with the second-generation post architecture of the K computer in Japan. In the present performance comparison, we vary the number of threads per nodes from 1 (the flat-MPI parallelism) to 32. The result shows that the OpenMP-MPI hybrid parallelism outperforms the flat-MPI for any number of compute nodes. There is an optimum number of threads per nodes depending on the number of compute nodes. It is shown that the optimum number of threads per node becomes larger on a larger number of compute nodes. This is because the communication time of an MPI collective communication subroutine, which is used for convergence check of iterative methods, can be reduced by decreasing the total number of processes with the OpenMP-MPI hybrid parallelism.
Dynamic Power Supply Design for High-Efficiency Wireless Transmitters

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Interaction style detection based on Fused Cross-Correlation Model in spoken conversation

In recent years, much attention has been given to dialogue strategy design to achieve intelligent speech-based human-computer interaction. Since speakers generally express their intents in different Interaction Styles (ISs), the responses of a spoken dialogue system should be versatile instead of invariable and planned. This paper presents an approach to automatic detection of a user's IS using a Fused Cross-Correlation Model (FCCM). As IS generally involves high level psychological meaning, cross-correlation among various psychological factors including emotion, personality trait, and IS is thus considered for IS detection modeling. The Bayes' theorem is then used to integrate the cross-correlation into the IS detector for enhancing the IS detection accuracy. Experiments show a promising result of the proposed approach.
Diagnostic immunophenotype of acute promyelocytic leukemia before and early during therapy with all-trans retinoic acid.

OBJECTIVES To study the immunophenotypic changes of acute promyelocytic leukemia (APL) in patients who recently received all-trans retinoic acid (ATRA) and to assess the diagnostic utility of flow cytometry in this setting. METHODS Flow cytometry was performed on 29 newly diagnosed APLs and 93 other acute myeloid leukemias, including 25 HLA-DR- or CD34- cases. Clinical notes from referring institutions were reviewed to assess for recent ATRA administration. RESULTS Recent ATRA therapy was documented in 17 (59%) of 29 patients with APL. The main features of untreated APL were preserved with ATRA therapy, including CD34- (83% vs 82%), HLA-DR- (83% vs 100%), and CD117+ (100% vs 77%). CD11b and CD11c were negative in all untreated APLs but positive in 76% and 88% of ATRA-treated APLs, respectively. Optimal diagnostic criteria for untreated APL (CD34- or HLA-DR- and CD11b- and CD11c-) showed 100% sensitivity and 98% specificity but were not useful after ATRA administration. The best interpretative approach to ATRA-treated APL (CD34- or HLA-DR-) showed 100% sensitivity but limited specificity (73%). CONCLUSIONS Information about recent ATRA administration is critical for adequate interpretation of the flow cytometric findings in patients with suspected APL.
Streaming of high-resolution progressive meshes over the internet

High-resolution 3D meshes are increasingly available in networked applications, such as digital museum, online game, and virtual reality. The amount of data constituting a high-resolution 3D mesh can be huge, leading to long downloading time. To reduce the waiting time of users, a common technique for remote viewing is progressive streaming, which allows a low-resolution version of the mesh to be transmitted and rendered with low latency. The quality of the transmitted mesh is incrementally improved by continuously transmitting the refinement information.
Speech recognition in the presence of highly non-stationary noise based on spatial, spectral and temporal speech/noise modeling combined with dynamic variance adaptation

In this paper, we introduce a system for recognizing speech in the presence of multiple rapidly time-varying noise sources. The main components of the proposed approach are a modelbased speech enhancement pre-processor and an adaptation technique to optimize the integration between the pre-processor and the recognizer. The speech enhancement pre-processor consists of two complementary elements, a multi-channel speechnoise separation method that exploits spatial and spectral information, followed by single channel enhancement that uses the long-term temporal characteristics of speech. To compensate for any mismatch that may remain between the enhanced features and the acoustic model, we employ an adaptation technique that combines conventional MLLR with the dynamic adaptive compensation of the variance of the Gaussians of the acoustic model. Our proposed system greatly improves the audible quality of speech and substantially improves of the keyword recognition accuracy. Index Terms: Robust ASR, Source separation, Model-based speech enhancement, Example-based enhancement, Model adaptation, Dynamic variance adaptation