Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of The ADC Resolution Based on FPGA Implementation of Interpolating Algorithm

This paper exposes a method that gives us the possibility to use a low accuracy Analog-to-Digital Converter (ADC) in high-resolution measurements. We increase the resolution of a 12-bits ADC to 16-bits by adding samples which are calculated using Shannon interpolate algorithm. Thus, the digital signal has high resolution compared to measurements. Specific hardware architecture was developed to implement the algorithm in FPGA. The great advantages of the proposed design are an enhancement of ADC resolution and the continuous time is modeled as a white noise which is generated by the FPGA itself, obviating the need of an external noise source. Results were presented in order to confirm the method
Joint Antenna Selection and Frequency-Domain Scheduling in OFDMA Systems with Imperfect Estimates from Dual Pilot Training Scheme

Transmit antenna selection (AS) has been adopted in contemporary wideband wireless standards such as Long Term Evolution (LTE). We analyze a comprehensive new model for AS that captures several key features about its operation in wideband orthogonal frequency division multiple access (OFDMA) systems. These include the use of channel-aware frequency-domain scheduling (FDS) in conjunction with AS, the hardware constraint that a user must transmit using the same antenna over all its assigned subcarriers, and the scheduling constraint that the subcarriers assigned to a user must be contiguous. The model also captures the novel dual pilot training scheme that is used in LTE, in which a coarse system bandwidth-wide sounding reference signal is used to acquire relatively noisy channel state information (CSI) for AS and FDS, and a dense narrow-band demodulation reference signal is used to acquire accurate CSI for data demodulation. We analyze the symbol error probability when AS is done in conjunction with the channel-unaware, but fair, round-robin scheduling and with channel-aware greedy FDS. Our results quantify how effective joint AS-FDS is in dispersive environments, the interactions between the above features, and the ability of the user to lower SRS power with minimal performance degradation.
Mapping of Service Level Objectives to Performance Queries

The concept of service level agreements (SLAs) defines the idea of a reliable contract between service providers and their users. SLAs provide information on the scope, the quality and the responsibilities of a service and its provider. Service level objectives (SLOs) define the detailed, measurable conditions of the SLAs. After service deployment, SLAs are monitored for situations, that lead to SLA violations. However, the SLA monitoring infrastructure is usually specific to the underlying system infrastructure, lacks generalization, and is often limited to measurement-based approaches. This makes it hard to apply the results from SLA monitoring in other stages of the software life-cycle. In this paper we propose the mapping of concerns defined in SLAs to the performance metrics queries using the Descartes Query Language (DQL). The benefit of our approach is that the same performance query can then be reused for evaluation of performance concerns throughout the entire life-cycle, and regardless of which approach is used for evaluation.
Mixed Membership Stochastic Block Models for Relational Data with Application to Protein-Protein Interactions

Modeling relational data is an important problem for modern data analysis and machine learning. In this paper we propose a Bayesian model that uses a hierarchy of probabilistic assumptions about the way objects interact with one another in order to learn latent groups, their typical interaction patterns, and the degree of membership of objects to groups. Our model explains the data using a small set of parameters that can be reliably estimated with an efficient inference algorithm. In our approach, the set of probabilistic assumptions may be tailored to a specific application domain in order to incorporate intuitions and/or semantics of interest. We demonstrate our methods on simulated data, where they outperform spectral clustering techniques, and we apply our model to a data set of protein-to-protein interactions, to reveal proteins’ diverse functional roles.
Place and Personality

An individual’s personality according to the Five-Factors (‘Big Five’) model of personality can be described in terms of openness, conscientiousness, extraversion, agreeableness and neuroticism. This work adapts human personality traits research to places, using keywords extracted from reviews as indicative of personality dimensions.
Mathematical modelling of internal heat recovery in flash tank heat exchanger cascades

Flash tank evaporation combined with a condensing heat exchanger can be used when heat exchange is required between two streams, where at least one of these streams is difficult to handle (tends severely to scale, foul, causing blockages). To increase the efficiency of heat exchange, a cascade of these units in series can be used. Heat transfer relationships in such a cascade are very complex due to their interconnectivity; thus the impact of any changes proposed is difficult to predict. Moreover, the distribution of loads and driving forces at different stages and the number of designed stages faces tradeoffs which require fundamental understanding and balances. This paper addresses these problems, offering a mathematical model of a single unit composed of a flash tank evaporator combined with a condensing heat exchanger. This model is then extended for a chain of such units. The purpose of this model is an accurate study of the factors influencing efficiency of the system (maximizing heat recovery) and evaluation of the impact of an alteration of the system, thus allowing for guided design of new or redesign of existing systems.
An Explanatory Design Theory for a Controlling System for IT Investments Performance Evaluation

The business investments in IT show a stable growth even tough the international financial crisis stopped them for quite a small period of time. Still, the evaluation of IT investments impact onto business performance remains a low-structured problem and very often represents an expert, qualitative and not formalized procedure. From this point of view this research in progress paper presents the approach to the design and the development of an IT investments controlling and performance measurement instrument. It adopts a design research perspective and, at the current stage of research, discusses only a descriptive design theory of such instrument.
A Novel Compressive Sensing based Enhanced Multiplexing Scheme for MIMO System

A novel compressive-sensing based signal multiplexing scheme is proposed in this paper to further improve the multiplexing gain for multiple input multiple output (MIMO) system. At the transmitter side, a Gaussian random measurement matrix in compressive sensing is employed before the traditional spatial multiplexing in order to carry more data streams on the available spatial multiplexing streams of the underlying MIMO system. At the receiver side, it is proposed to reformulate the detection of the multiplexing signal into two steps. In the first step, the traditional MIMO equalization can be used to restore the transmitted spatial multiplexing signal of the MIMO system. While in the second step, the standard optimization based detection algorithm assumed in the compressive sensing framework is utilized to restore the CS multiplexing data streams, wherein the exhaustive over-complete dictionary is used to guarantee the sparse representation of the CS multiplexing signal. In order to avoid the excessive complexity, the sub-block based dictionary and the sub-block based CS restoration is proposed. Finally, simulation results are presented to show the feasibility of the proposed CS based enhanced MIMO multiplexing scheme. And our efforts in this paper shed some lights on the great potential in further improving the spatial multiplexing gain for the MIMO system.
Effects of Particle Size on Melt Viscoelastic Properties During Capillary Extrusion of Glass Bead-filled LDPE Composites

ABSTRACT: In this study, the viscoelastic properties of a low-density polyethylene (LDPE) filled with glass beads (GBs) are measured at 150 C by means of a capillary rheometer to identify the effect of the particle size on the melt viscoelasticity. The volume fraction of the GB was 8.4%. The surface of the particles has been treated with a silane-coupling agent and the diameter range was from 4 to 180 mm. The results showed that either the entry pressure drop (Pen) or the entry elongation stress (e) is a linear function of shear stress (w) at the channel wall. The values of both Pen and e of these composite melts are close to each other. This illustrates that the influence of the bead size and its distribution on them is insignificant at low filler concentration. The die-swell ratio (B) increases nonlinearly with an addition of w. When the diameter (d) of the beads is less than 50 mm, B decreases dramatically with an increase of d, especially at low shear stress level, and then it decreases slightly under the given shear stress level.
Explicit model-predictiv e control of hybrid dynamical systems: Application to a two-tank system

In this paper, we consider the solution of explicit model predictive control problem for piecewise affine systems in order to compare the results for the quadratic criterion and the linear one. Two issues are addressed: First, we start by computing the solution of the considered problem and determine the structure of the control law. Thereafter, we aim to reduce the complexity of the obtained control law to improve system performance in terms of number of polyhedral regions and computation time.
Consensus strategies of multiple agents system

In this paper, we consider the consensus problem of the multiple agents control for a discrete-time case under fixed information topology. First, we design the control laws based on the neighbor to solve the consensus problem of multi-agent systems. Second, we prove that each follower can track the active leader, and consensus analysis is performed based on Lyapunov approach. Furthermore, we study the effect of disturbances on the system. Numerical simulations illustrate the theoretical results.
Results of a phase I pilot clinical trial examining the effect of plant-derived resveratrol and grape powder on Wnt pathway target gene expression in colonic mucosa and colon cancer

Context: Resveratrol exhibits colon cancer prevention activity in animal models; it is purported to have this activity in humans and inhibit a key signaling pathway involved in colon cancer initiation, the Wnt pathway, in vitro. Design: A phase I pilot study in patients with colon cancer was performed to evaluate the effects of a low dose of plant-derived resveratrol formulation and resveratrol-containing freeze-dried grape powder (GP) on Wnt signaling in the colon. Eight patients were enrolled and normal colonic mucosa and colon cancer tissue were evaluated by Wnt pathway-specific microarray and quantitative real-time polymerase chain reaction (qRT-PCR) pre- and post-exposure to resveratrol/GP. Results: Based on the expression of a panel of Wnt target genes, resveratrol/GP did not inhibit the Wnt pathway in colon cancer but had significant (p < 0.03) activity in inhibiting Wnt target gene expression in normal colonic mucosa. The greatest effect on Wnt target gene expression was seen following ingestion of 80 g of GP per day (p < 0.001). These results were confirmed with qRT-PCR of cyclinD1 and axinII. The inhibitory effect of GP on Wnt signal throughput was confirmed in vitro with a normal colonic mucosa-derived cell line. Conclusions: These data suggest that GP, which contains low dosages of resveratrol in combination with other bioactive components, can inhibit the Wnt pathway in vivo and that this effect is confined to the normal colonic mucosa. Further study of dietary supplementation with resveratrol-containing foods such as whole grapes or GP as a potential colon cancer preventive strategy is warranted. Trial registration: NCT00256334.
Incubation temperature and parental identity determine sex in the Australian agamid lizard Ctenophorus pictus

Abstract Sex determination in Australian agamid lizards shows a complex framework of different mechanisms, varying even among closely related taxa. It is clear that discrete classification of these species as either having genetic (GSD) or environmental sex determination (ESD) does not agree with empirical data. Although many species in this group show temperature‐dependent sex determination (TSD), recent evidence suggests additional genetic or epigenetic effects. A proposed model explaining the adaptive significance and evolution of TSD in short‐lived agamids predicts that selection will favor temperature‐biased sex ratios in species with intense male‐male competition. Here, we use experimental incubation at (near) constant temperatures to test whether the sex of Australian painted dragons (Ctenophorus pictus) is influenced by temperature, building on previous research yet to have reached an agreement regarding the role of temperature in this species. In this study, incubation temperature and parental identity affected hatchling sex suggesting that environment and genetics may work in concert to determine sex in this species. Although our results are consistent with TSD, our data cannot rule out a temperature‐by‐sex effect on egg or hatchling mortality. However, our findings together with the observed differences of sex determination systems in closely related species within this genus may provide novel opportunities to address fundamental questions in the evolution of sex determination systems.
Steady state controller design for aero-engine based on reinforcement learning NNs

An aero-engine optimal steady state controller based on reinforcement learning neural networks (NNs) was proposed in this paper. The presented reinforcement learning NNs can achieve the optimal control objective by constructing two interconnected modules (i.e. action module and critic module). For the state variable models of small perturbation on steady operating points, the double-variable control of an aero-engine is accomplished by two similar backing propagation (BP) NNs. The simulation results show that the presented controller has the perfect performance with the smooth transition process. It not only has strong anti-interference ability and adaptability, but also has excellent robustness to the change of aero-engine model parameters.
Flexible Pavement Response Evaluation using the Semi-analytical Finite Element Method

ABSTRACT The Semi-Analytical Finite Element method is an effective method for modeling the load response of structures in which the material properties and problem geometry do not change in one coordinate direction. The method offers considerable savings in computational requirements compared to a full three-dimensional finite element analysis, yet allows the modeling of complex pavement design situations such as those involving cracks or non-homogeneous layers. In this paper, the background to, and theoretical basis of the semi-analytical finite element method is presented. The application of the method to a pavement response evaluation is illustrated. Results obtained with the semi-analytical finite element method are compared with the corresponding theoretical (closed-form) solution. It is shown that there is a good agreement between results obtained with the theoretical solution and those obtained with the semi-analytical finite element method.
HybIdx: Indexes for Processing Hybrid Graph Patterns Over Text-Rich Data Graphs

Many databases today are text-rich in that they not only capture structured but also unstructured data. In this work, we propose a full-text extension to SPARQL capable of expressing different types of hybrid search queries over text-rich RDF graphs. We study existing indexing solutions to arrive at the conclusions that database extensions are less efficient than native solutions, and the most efficient indexes are limited w.r. t. the types of hybrid search queries they can support, i.e. entity queries. We propose an indexing solution call HybIdx, which is both efficient and versatile in terms of query type support, i.e. it supports full SPARQL graph patterns where keywords can appear in any position (relational queries). Experiments suggest that it can outperform the second best approach by up to three orders of magnitude for complex queries.
Evisceration of Mouse Vitreous and Retina for Proteomic Analyses

While the mouse retina has emerged as an important genetic model for inherited retinal disease, the mouse vitreous remains to be explored. The vitreous is a highly aqueous extracellular matrix overlying the retina where intraocular as well as extraocular proteins accumulate during disease.1-3 Abnormal interactions between vitreous and retina underlie several diseases such as retinal detachment, proliferative diabetic retinopathy, uveitis, and proliferative vitreoretinopathy.1,4 The relative mouse vitreous volume is significantly smaller than the human vitreous (Figure 1), since the mouse lens occupies nearly 75% of its eye.5 This has made biochemical studies of mouse vitreous challenging. In this video article, we present a technique to dissect and isolate the mouse vitreous from the retina, which will allow use of transgenic mouse models to more clearly define the role of this extracellular matrix in the development of vitreoretinal diseases.
The Prediction Method Research of Wavelet and Fuzzy Combined with Statistical Correlation

Based on prediction model of fuzzy classification and fuzzy recognition combined with statistical correlation, the theory of wavelet analysis was introduced and proposed the prediction model of wavelet and fuzzy combined with statistical correlation, there is a basic mentality: first, wavelet decomposes the prediction factors one by one, and then take the wavelet series that have decomposed into the prediction model of fuzzy classification and fuzzy recognition combined with statistical correlation, the prediction can progressed by getting the regression equation between category variable characteristic value and prediction object, in the annual runoff prediction of Yamadu station at Sinkiang province, the prediction accuracy of this model is satisfying.
MIX DESIGN SYSTEM FOR POLYMER- MODIFIED MORTARS

This paper deals with the mix design system for the polymer- modified mortars using various polymer dispersions (latexes or emulsions) for cement modifiers, which are popular construction materials in the world. The purpose of this study was to find out the useful mix design systems for the polymer- modified mortars. Based on the strength prediction equations empirically proposed using "void- binder ratio" by the author, an appropriate mix design system is developed for the polymer- modified mortars. Nomographs for estimating the quantities of the materials required for mix proportioning of the polymer--modified mortars are presented. (Author/TRRL)
Living on the edge: Monitoring network flows at the edge in cloud data centers

Scalable network wide flow monitoring has remained a distant dream because of the strain it puts on network router resources. Recent proposals have advocated the use of coordinated sampling or host based flow monitoring to enable a scalable network wide monitoring service. As most hosts in data centers get virtualized with the emergence of the cloud, the hypervisor on a virtualized host adds another network layer in the form of a vSwitch (virtual switch). The vSwitch now forms the new edge of the network. In this paper, we explore the implications of enabling network wide flow monitoring inside virtual switches in the hosts. Monitoring of network flows inside the server vSwitch can enable scalability due to its distributed nature. However, assumptions that held true for flow monitoring inside a physical switch need to be revisited since vSwitches are usually not limited by the same level of resource constraints that exist for physical switches and routers. On the other hand, vSwitches do not implement flow monitoring in hardware, as it is done in some physical switches. We present the design and implementation of EMC2 - a scalable network wide monitoring service for cloud data centers. We also conduct an extensive evaluation of various switch based flow monitoring techniques and share our findings. Our results indicate that while layer-3 flow monitoring protocols such as NetFlow can give a very good network coverage without using too many resources, protocols that sample packet headers (such as sFlow) need to be carefully configured. A badly configured sFlow vSwitch can degrade application network throughput by up to 17% and can also choke the management network by generating monitoring data at a very high rate.
A Nonlinear Filtering Approach for the Attitude and Dynamic Body Acceleration Estimation Based on Inertial and Magnetic Sensors: Bio-Logging Application

This paper addresses the problem of rigid body orientation and Dynamic Body Acceleration (DBA) estimation. This work is applied in bio-logging, an interdisciplinary research area at the intersection of animal behavior and bioengineering. The proposed approach combines a quaternion-based nonlinear filter with the Levenberg Marquardt Algorithm (LMA). The algorithm has a complementary structure design that exploits measurements from a three-axis accelerometer, a three-axis magnetometer, and a three-axis gyroscope. Attitude information is necessary to calculate the animal's DBA in order to evaluate its energy expenditure. Some numerical simulations illustrate the nonlinear filter performance. Some quantitative assessments prove this efficiency such as the time constant of the filter ( ) and the rms magnitude of the quaternion error ( ). Moreover, the effectiveness of the algorithm is experimentally demonstrated. In the experiments a domestic animal is equipped with an Inertial Measurement Unit (MTi-G), which provides a truth attitude for comparison with the complementary nonlinear filter. The rms difference between the filter and MTi-G outputs in the free movement experiments is within 0.392 rms on roll, 0.577 rms on pitch, and 2.521 rms on yaw.
Vacuum Deposition of Parylene Films: Influence of Process Factors and Baffling on Film-Thickness Distribution

Deposition in vacuum of poly(paraxylylene)-PPX or "Parylene"-and derivative polymers from dimer that have been ionized and vaporized is a process used for over 35 years to form protective and insulating coatings on electronic and other devices and to generate extremely thin, pinhole-free films. Coating thickness has been asserted to be highly uniform, but with scant data in the literature. We investigated thickness distribution in a series of coating runs in each of which 60 or 80 small aluminum disks were positioned throughout the coating chamber. The processing factors tested were rate of coating, disk location (radius and altitude), flow-distribution devices, and whether the rack holding the disks was stationary or rotated. In the initial sequence of five runs, 320 film thicknesses were determined. Some findings include: (1) film thickness was heaviest at chamber midheight, diminishing symmetrically toward top and bottom by as much as 25%, and, less strongly, inward from wall to axis. (2) Disk orientation-whether vertical, hoizontal, or at 45°-did not affect film thickness. (3) Rotation of the rack eliminated an inlet-to-outlet downslope of thickness. (4) Dividing the chamber with a midplane separator, together with special inlet and takeoff distributors, reduced the total range of thickness from 40% to 25% of the average. A thickness variation of less than± 10% is possible by positioning objects in a limited vertical range and while preventing shadowing.