Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Performance Evaluation of TCP in Mobile Ad-Hoc Networks

Wireless mobile ad-hoc networks offer challenges and opportunities to network. Distinguishing characteristics in some proposals are proposed. The performance study of a terminal system based mechanism that performs precise detection of network states by measuring appropriate metrics is also proposed. The performance under variety of network conditions running different class of routing protocols dynamic source routing and destination-sequenced distance vector is evaluated. The results show the effect of different factors in isolation and in combination with each other on the TCP performance, and the impact of routing protocol design approaches in the TCP stability.
Sliced voxel representations with LSTM and CNN for 3D shape recognition

We propose a sliced voxel representation, which we call Sliced Square Voxels (SSV), based on LSTM (Long Short-Term Memory) and CNN (Convolutional Neural Network) for three-dimensional shape recognition. Given an arbitrary 3D model, we first convert it into binary voxel of size 32×32×32. Then, after a view position is fixed, we slice the binary voxel data vertically in the depth direction. To utilize the 2D projected shape information of the sliced voxels, CNN has been applied. The output of CNN is fed into LSTM, which is our main idea, where the spatial topology is supposed to be favored with LSTM. From our experiments, our proposed method turns out to be superior to the baseline method which we prepared using 3DCNN. We further compared with related previous methods, using large-scale 3D model dataset (ModelNet10 and ModelNet40), and our proposed methods outperformed them.
DNA directed binding of photosynthetic light-harvesting proteins * *

Figure S1. Schematic illustration of puhA-zif268 DNA construct S2 Figure S2. Agarose gels showing amplification and assembly of the puhA-zif268 construct. S3 Figure S3 Sequence confirmation of puhA-zif268 construct by MWG Eurofins S3 Figure S4 SDS-PAGE and absorption spectra of purified WT and zfRC-LH1 S4 Figure S5 MALDI-TOF for the WT and zfRC-LH1 S5 Figure S6 MALDI-TOF mass spectra of DNA-cyclooctyne conjugates S6 Figure S7 Denaturing PAGE of DNA sequences 1 – 6 S7 Scheme S1 Synthesis of DNA cyclooctynes 3-4 and their conjugation with 4-((3-azidopropyl)carbamoyl)-3,6-dichloro-2-(2,4,5,7-tetrachloro6-hydroxy-3-oxo-3H-xanthen-9-yl)benzoic acid S8
Explorer Recognising emotions in spoken dialogue with hierarchically fused acoustic and lexical features

Automatic emotion recognition is vital for building natural and engaging human-computer interaction systems. Combining information from multiple modalities typically improves emotion recognition performance. In previous work, features from different modalities have generally been fused at the same level with two types of fusion strategies: Feature-Level fusion, which concatenates feature sets before recognition; and Decision-Level fusion, which makes the final decision based on outputs of the unimodal models. However, different features may describe data at different time scales or have different levels of abstraction. Cognitive Science research also indicates that when perceiving emotions, humans use information from different modalities at different cognitive levels and time steps. Therefore, we propose a Hierarchical fusion strategy for multimodal emotion recognition, which incorporates global or more abstract features at higher levels of its knowledge-inspired structure. We build multimodal emotion recognition models combining state-of-the-art acoustic and lexical features to study the performance of the proposed Hierarchical fusion. Experiments on two emotion databases of spoken dialogue show that this fusion strategy consistently outperforms both Feature-Level and Decision-Level fusion. The multimodal emotion recognition models using the Hierarchical fusion strategy achieved state-of-the-art performance on recognizing emotions in both spontaneous and acted dialogue.
ISAR Imaging by Two-Dimensional Convex Optimization-Based Compressive Sensing

A novel 2D convex optimization-based compressive sensing (CS) method is presented for inverse synthetic aperture radar (ISAR) imaging. The method deals directly with the 2D signal model for the image reconstruction based on solving a convex optimization problem. The superiority of this method is that the memory usage and the computational complexity are much lower than those of the 1D CS-based ISAR imaging method. Especially, the method belongs to a convex optimization problem. Convex functions do not suffer from local minima assuring that the achieved solution always happens to be the optimal. Simulation and experimental results are provided to demonstrate the performance of the proposed method with comparisons to the traditional Fourier-based method and to the smoothed L0-norm-based method, which proves that the proposed method is an effective way to solve the ISAR imaging problem.
Self-reported health and socio-economic inequalities in England , 1996 e 2009 : Repeated national cross-sectional study

Tackling social inequalities in health has been a priority for recent UK governments. We used repeated national cross-sectional data for 155,311 participants (aged 16 years) in the Health Survey of England to examine trends in socio-economic inequalities in self-reported health over a recent period of sustained policy focus by successive UK governments aimed at tackling social inequalities in health. Socioeconomic related inequalities in self-reported health were estimated using the Registrar General's occupational classification (1996e2009), and for sensitivity analyses, the National Statistics SocioEconomic Classification (NS-SEC; 2001e2011). Multi-level regression was used to evaluate time trends in General Health Questionnaire (GHQ-12) scores and bad or very bad self-assessed health (SAH), as well as EQ-5D utility scores. The study found that the probability of reporting GHQ-12 scores 4 and 1 was higher in those from lower social classes, and decreased for all social classes between 1997 and 2009. For SAH, the probability of reporting bad or very bad health remained relatively constant for social class I (professional) [0.028 (95%CI: 0.026, 0.029) in 1996 compared to 0.028 (95%CI: 0.024, 0.032) in 2009], but increased in lower social classes, with the greatest increase observed amongst those in social class V (unskilled manual) [0.089 (95%CI: 0.085, 0.093) in 1996 compared to 0.155 (95%CI: 0.141, 0.168) in 2009]. EQ-5D utility scores were lower for those in lower social classes, but remained comparable across survey years. In sensitivity analyses using the NS-SEC, health outcomes improved from 2001 to 2011, with no evidence of widening socio-economic inequalities. Our findings suggest that socio-economic inequalities have persisted, with evidence of widening for some adverse self-reported health outcomes. Crown Copyright © 2015 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
C ONTEXTO : Leveraging Energy Awareness in the Development of Context-Aware Applications

We introduce a new context classification and recognition framework for the development and deployment of mobile, context-aware applications. The framework is complemented with an energy calculator that specifically assists mobile developers in estimating the energy footprint of context-aware applications during the development process with the framework. The framework abstracts from the raw context information gathering, allows for sensor fusion, enables the prediction of custom and higher-level contexts, and provides for context sharing.
Circuit Modeling in DLSim 3

DLSim 3, is a GUI-based digital logic simulation program developed by Richard Salter at Oberlin College, extends the capabilities of such programs through the use of Java plug-ins. DLSim 3 makes it it possible to use the software for digital design at higher levels of abstraction. With DLSim 3, we are able to present the many levels of circuit design in a single environment, from low level combinational and sequential circuits through models of complete CPUs. This paper shows how DLSim 3 has been used in the classroom to model several CPUs well known to educators, and to support creative efforts on the part of students of Computer Organization.
Enhancing video game performance through an individualized biocybernetic system

Biocybernetic systems are physiological software systems that explicitly utilize physiological signals to control or adapt software functionality (Pope et al., 1995.) These systems have tremendous potential for innovation in human computer interaction by using physiological signals to infer a user’s emotional and mental states (Allanson & Fairclough, 2004; Fairclough, 2008). Nevertheless, development of these systems has been ultimately hindered by two fundamental challenges. First, these systems make generalizations about physiological indicators of cognitive states across populations when, in fact, relationships between physiological responses and cognitive states are specific to each individual (Andreassi, 2006). Second, they often employ largely inconsistent retrospective techniques to subjectively infer user’s mental state (Fairclough, 2008). An individualized biocybernetic system was developed to address the fundamental challenges of biocybernetic research. This system was used to adapt video game difficulty through real-time classifications of physiological responses to subjective appraisals. A study was conducted to determine the system’s ability to improve player’s performance. The results provide evidence of significant task performance increase and higher attained task difficulty when players interacted with the game using the system than without. This work offers researchers with an alternative method for software adaptation by conforming to the individual characteristics of each user.
Optimizing PM coverage ratio in flux concentrating axial flux machine

A two-stator, one-rotor axial motor is considered for bike applications. It has a 24 slot 20 pole structure, and concentrated pole windings. Two stator cores are made with the laminated sheets instead of the soft magnetic composite (SMC). PMs are magnetized to the circumferential direction for concentrating the PM flux. The air-gap field is analyzed based on a simplified 2D model, and is solved for optimal permanent magnet (PM) ratio. The optimum PM coverage ratio is determined based on 3D FEM results. A prototype motor was built, and back EMF was tested.
CREATIVITY TRAINING FOR FUTURE ENGINEERS: PRELIMINARY RESULTS FROM AN EDUCATIVE EXPERIENCE

Due in part to the increased pace of cultural and environmental change, as well as increased competition due to globalization, innovation is become one of the primary concerns of the 21st century. We will present an academic course designed to develop cognitive abilities related to creativity within an engineering education context, based on a conceptual framework rooted in cognitive sciences. The course was held at Ecole Polytechnique de Montreal (EPM), a world renowned engineering school and a pillar in Canada’s engineering community. The course was offered twice in the 2014-2015 academic year and more than 30 students from the graduate and undergraduate programs participated. The course incorporated ten pedagogical strategies, including serious games, an observation book, individual and group projects, etc., that were expected to facilitate the development of cognitive abilities related to creativity such as encoding, and associative/analytical thinking. The CEDA (Creative Engineering Design Assessment) test was used to measure the students’ creativity at the beginning and at the end of the course. Field notes were taken after each of the 15 three-hour sessions to qualitatively document the educative intervention along the semester and students gave anonymous written feedback after completing the last session. Quantitative and qualitative results suggest that an increase in creativity is possible to obtain with a course designed to development cognitive abilities related to creativity. Also, students appreciated the course, found it relevant, and made important, meaningful learnings regarding the creative process, its cognitive mechanism and the approaches available to increase it.
How to determine protein secondary structure in solution by Raman spectroscopy: practical guide and test case DNase I

For many proteins available in large (milligram) quantities, a three-dimensional structure determination by X-ray or NMR methods is very difficult, impossible, or too costly. In these cases, spectroscopic determination of secondary structure content can be a valuable source of partial information about protein structure in solution. In particular, Raman spectroscopy can be used to determine to fair accuracy the helix and sheet content of a globular protein. However, technical difficulties have hampered the routine application of the method: (1) The large background signal of aqueous solvent in the amide I region is difficult to subtract accurately. (2) The reference data set of Raman spectra of proteins with known crystal structure is incomplete, and the assignment of secondary structure in a known crystal structure is not unambiguous. (3) The mathematical problem of extracting structure information from the spectra is ill determined; i.e., there are many apparently satisfactory solutions for a given spectrum. We have now partly solved and partly sidestepped these problems by improving and simplifying existing methods. Here, we give a step-by-step outline of a procedure intended for routine determination of the percentage of a-helix and @-sheet from the amide I Raman spectra of proteins in solution. Its main features are (a) an uncom- plicated procedure for solvent subtraction, aided by use of a divided spinning cell technique, (b) a numerically stable data handling algorithm, and (c) a clear statement of expected accuracy. In our hands, using the reference spectra of Williams (1 983), helix content can be determined to an accuracy of 6 percentage points (largest error 12%) and @-sheet content to an accuracy of 5 percentage points (largest error 7%). However, the experimental distinction between parallel and antiparallel 0-sheet does not appear possible without a significant expansion of the set of reference proteins. As a test we have measured the Raman spectrum of DNase I, a known structure treated as unknown, and derive 14% a-helix and 22% 0-sheet content, compared to X-ray derived values of 20% helix and 25% sheet (hydrogen bonds per 100 residues). The error, -6% for helix and -3% for sheet content, is typical. The method can be a tool for checking the structural purity of genetically engineered proteins, detecting major structural alterations of mutant proteins, and providing a priori information as input to predictions of protein structure.
Electrowetting based actuation of droplets with PDMS dielectric

Both properties of the used dielectrics in electrowetting actuators - i.e. thickness and layer material - play an important role in their functionality. In this paper, in order to optimize dielectric layer thickness, equivalent circuit method has been used. Then, PDMS polymer was used instead of common materials for insulation. Common insulation materials, like SiO2, are deposited by methods like PECVD which are time-consuming and costly. Unlike such methods, PDMS deposition is done by spin coating which is considered to be a simple method indeed. Afterwards, the actuator was fabricated according to the optimized thickness. Finally, it was proved that the actuator functionality was fairly appropriate, regarding the dominating theoretical equations and the ability to manipulate droplets on the surface.
A Bayesian Estimator of the Intracluster Correlation Coefficient from Correlated Binary Responses

Clustered binary samples arise often in biomedical investigations. An important feature of such samples is that the binary responses within clusters tend to be correlated. The Beta-Binomial model is commonly ap- plied to account for the intra-cluster correlation - the correlation between responses within the clusters - among dichotomous outcomes in cluster sam- pling. The intracluster correlation coefficient (ICC) quantifies this correla- tion or level of similarity. In this paper, we propose Bayesian point and inter- val estimators for the ICC under the Beta-Binomial model. Using Laplace's method, the asymptotic posterior distribution of the ICC is approximated by a normal distribution. The posterior mean of this normal density is used as a central point estimator for the ICC, and 95% credible sets are calculated. A Monte Carlo simulation is used to evaluate the coverage probability and average length of the credible set of the proposed interval estimator. The simulations indicate that for the situation when the number of clusters is above 40, the underlying mean response probability falls in the range of (0.3;0.7), and the underlying ICC values are • 0.4, the proposed interval estimator performs quite well and attains the correct coverage level. Even for number of clusters as small as 20, the proposed interval estimator may still be useful in the case of small ICC (• 0.2).
Short- / Long-Term Deformation of Upper Crust: Integrated and Quantitative Approach for Neotectonics

The Japanese Islands are facing active convergent margin, and have suffered intense deformation. On 11 March 2011, accumulated stress on the Japan Trench was released as a catastrophic earthquake (Mw 9.0), and the number of casualties are still increasing during preparation of this manuscript. The authors offer our deepest condolences on the loss of human lives, and dedicate this paper to the deceased hoping that our research can contribute to the advancement of integrated evaluation of seismic hazards. The islands are divided into northeast and southwest Japan at the Itoigawa-Shizuoka Tectonic Line (ISTL; Figure 1), which is a remarkable geological break and a zone of highly active reverse faults. An area of extremely high strain rate is conventionally named as Central Japan, which is a mountainous province associated with a number of active faults/volcanoes. Based on geomorphological studies, distribution of active faults in Central Japan has been clarified in detail (Research Group for Active Faults, 1991). Countless Quaternary tephra are precisely correlated (Machida & Arai, 2003), and serve to monitor subtle neotectonic deformation as explained in the following sections. It is an example of a junction of arcs (northeast Japan, southwest Japan and Izu-Bonin arcs), and an intensive collision zone. Remarkable bent of geologic belts, caused by collision of the Izu-Bonin arc, has been studied from the viewpoint of paleomagnetism / structural geology. Itoh & Ito (1989) clarified process of ductile deformation of the crust since the Miocene on the basis of spatial distribution of vertical-axis rotation deduced from paleomagnetic data. Long-term deformation in Central Japan is accommodated by conjugate strike-slip fault system; the NE-SW Atotsugawa fault system and NW-SE Atera fault system (Figure 1). Huzita (1980) proposed that they have been activated under an E-W compressive stress regime provoked during the Quaternary. Recently, paleomagnetic studies (Kimura et al., 2004; Itoh et al., 2008) revealed that rotation pattern around the active faults is simulated as deformation of continuous medium. Although temporal fluctuation of geomagnetic field (secular variation) generally hinders us from precise determination of tectonic rotation
Micromachined Fabry-Perot cavity pressure transducer

A surface micromachined Fabry-Perot cavity used as a pressure sensor has been fabricated using standard IC technology. Dielectric film stacks consisting of layers of silicon dioxide and silicon nitride were used as mirrors. Polysilicon was used as a sacrificial layer that was then removed to form an air gap cavity. The Fabry-Perot sensor was optically interrogated using a multimode optical fiber. The measured response of the sensor agrees well with theoretical simulation, which takes into account the averaging effect caused by the shape of the deflected mirror in the cavity.
The Seven Properties of Highly Secure Devices

Industry largely underestimates the critical societal need to embody the highest levels of security in every network-connected device —every child’s toy, every household’s appliances, and every industry’s equipment. High development and maintenance costs have limited strong security to high-cost or high-margin devices. Our group has begun a research agenda to bring high-value security to low-cost devices. We are especially concerned with the tens of billions of devices powered by microcontrollers. This class of devices is particularly ill-prepared for the security challenges of internet connectivity. Insufficient investments in the security needs of these and other price-sensitive devices have left consumers and society critically exposed to device security and privacy failures. This paper makes two contributions to the field of device security. First, we identify seven properties we assert are required in all highly secure devices. Second, we describe our experiment working with a silicon partner to revise one of their microcontrollers to create a prototype, highly secure microcontroller. Our experimental results suggest that in the near future even the most price-sensitive devices should be redesigned to achieve the high levels of device security critical to society’s safety. While our first experimental results are promising, more ongoing research remains and we seek to enlist the broader security community in a dialog on device security
Disease Gene Prioritization and the Novel Un-normalized Graph ( p-) Laplacian Ranking Methods

Abstract—The biological motivated problem that we want to solve in this paper is to predict the new members of a partially known set of genes involved in specific disease (i.e. disease gene prioritization). In this problem, we are given a core set of genes (i.e. the queries) involved in the specific disease. However, the biologist experts do not know whether this core set is complete or not. Our objective is to find more potential members of this core set by ranking genes in gene-gene interaction network. One of the solutions to this problem is the random walk on graphs method. However, the random walk on graphs method is not the current state of the art network-based method solving bioinformatics problem. In this paper, the novel un-normalized graph (p-) Laplacian based ranking method will be developed based on the un-normalized graph p-Laplacian operator definitions such as the curvature operator of graph (i.e. the un-normalized graph 1-Laplacian operator) and will be used to solve the disease gene prioritization problem. The results from experiments shows that the un-normalized graph p-Laplacian ranking methods are at least as good as the current state of the art network-based ranking method (p=2).