Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards rational de novo design of peptides for inorganic interfaces

Protein adsorption at inorganic surfaces is highly relevant to nano- and bionanotechnology. Just two examples of great significance are the use of specific peptide sequences to control cell deposition on tissue scaffolds, and the tethering of bio-photosynthetic reaction centers on electrodes to harvest light for power generation and hydrogen production. Understanding of the behavior of proteins in such situations and the design of surface-binding proteins for technological applications is currently limited by the largely empirical approaches used. We are, therefore, developing the application of molecular modeling to the elucidation of the behavior of peptides at fluid/solid interfaces ‐ in this talk, we will provide details of these models and their application to the study of peptides at fluid/solid interfaces and their de novo rational design.
An approach to conceptual modelling of ETL processes

In this paper, we propose a new conceptual model based on the visualization of data flow showing transformations of records accompanied with attribute transformations. A data warehouse development relies on the development of Extract, Transform, and Load (ETL) processes responsible for extracting data from transactional systems, data quality checks, transformation and conversion and loading data to target tables or cubes in a data warehouse. During the planning and design phases for data warehouse, the ETL conceptual model should be developed not only to show an overview of the whole process, but also to map sources, targets and necessary transformations, verify transformation logic, ensure that requirements are met and the needed structures and content exist. Once created, the conceptual model can be used for development of an ETL process, maintenance/optimization and redesign of a process due to new business requirements and database schema changes, all of which makes it a valuable addendum to data warehouse documentation.
A Tiny Quadrature Oscillator Using Low-Q Series LC Tanks

A new quadrature oscillator topology is proposed, which arranges four low-Q series LC tanks in a ring structure driven by inverters operating in class-D. With a very small area of 0.007 mm2 that is comparable to conventional ring oscillators, this oscillator has 7-20 dB better phase noise FoM of 177 dB. It is widely tunable for nearly an octave from 2.66 to 4.97 GHz.
IDN 1 and IDN 2 are required for de novo DNA methylation in Arabidopsis thaliana

DNA methylation is an epigenetic mark affecting genes and transposons. Screening for mutants that fail to establish DNA methylation yielded two we termed “involved in de novo” (idn) 1 and 2. IDN1 encodes DMS3, an SMC-related protein, and IDN2 encodes a previously unknown double-stranded RNA–binding protein with homology to SGS3. IDN1 and IDN2 control de novo methylation and small interfering RNA (siRNA)-mediated maintenance methylation and are components of the RNA-directed DNA methylation pathway.
Space shift keying modulation for MIMO channels

In this paper, we present space shift keying (SSK) as a new modulation scheme, which is based on spatial modulation (SM) concepts. Fading is exploited for multiple-input multiple-output(MIMO) channels to provide better performance over conventional amplitude/phase modulation (APM) techniques. In SSK, it is the antenna index used during transmission that relays information, rather than the transmitted symbols themselves. This absence of symbol information eliminates the transceiver elements necessary for APM transmission and detection (such as coherent detectors). As well, the simplicity involved in modulation reduces the detection complexity compared to that of SM, while achieving almost identical performance gains. Throughout the paper, we illustrate SSK's strength by studying its interaction with the fading channel. We obtain tight upper bounds on bit error probability, and discuss SSK's performance under some non-ideal channel conditions (estimation error and spatial correlation). Analytical and simulation results show performance gains over APM systems (3 dB at a bit error rate of 10-5), making SSK an interesting candidate for future wireless applications. We then extend SSK concepts to incorporate channel coding, where in particular, we consider a bit interleaved coded modulation (BICM) system using iterative decoding for both convolutional and turbo codes. Capacity results are derived, and improvements over APM are illustrated (up to 1 bits/s/Hz), with performance gains of up to 5 dB.
Characterisation of Challenges for Testing of Adaptive Systems

Context: Exercising the implementation of an adaptive system (AS) effectively, in order to detect faults, is not a trivial task. This is due to characteristics of this type of systems, such as the high number of configurations and runtime adaptations. In this context, the characterisation of challenges for testing ASs may support the definition of suitable testing strategies. However, such characterisation is currently spread over several studies in the literature. Objective: analysing testing-related challenges for ASs which are described in the literature, and establishing a generic classification. Method: we extended a Systematic Literature Review (SLR) of studies that address challenges for AS testing. By analysing the combined results (original and extended), we mapped descriptions found in individual studies, based on their similarities, in order to create a list of generic challenges. Results: a list of 12 generic challenges based on 34 specific ones described by several authors. Additionally, we analysed the relationship between the challenges and inherent properties of ASs. Conclusion: different terminology, varied levels of details and particular contexts (e.g. specific AS implementations) are recurring problems related to the characterisation of challenges for testing ASs. Generalisations such as the one proposed in this work may help researchers and practitioners do devise customised testing strategies that focus in recurring, inherent properties of ASs.
System-level model of electrothermal microsystem with temperature control circuit

In this paper we demonstrate a system-level simulation of a temperature controlled microsystem which is based on a reduced order model of a micro hotplate. Together with the electro-thermal microstructure we have implemented a control scheme, which allows the hotplate to operate either at a defined setpoint independent of ambient temperature or to follow defined temperature sweeps. An optimization algorithm was employed to identify suitable parameters for a PI-controller.
A comparative case study of non-music major participation in two contrasting collegiate choral ensembles

ABSTRACT The purpose of this comparative case study was to examine the motivation for participation in traditional and non-traditional vocal ensembles by students who are not pursuing a career in music and the perceived benefits of this participation. Participants were selected from a traditional mixed choral ensemble and a student-run a cappella ensemble. Data consisted of interviews, written reflections, and field observations. Both groups of participants indicated musical outcomes, emotional release, and achieving school/life balance as benefits of vocal ensemble participation. The personal motivations for the members of the different groups varied, with the traditional mixed choral ensemble students focused more on individual musical development and gaining technique, whereas the a cappella students reported group interaction and singing with others as the main factors for participation.
Factors of Usability Design for Multilingual and Multicultural Websites

The availability and popularity of new informational mediums within the last ten to fifteen years has prompted a drastic change in the way businesses and institutions educate and interact with potential clients. The World Wide Web has made the biggest impact on clients and businesses by providing a means to create a world-wide presence. Web designers, as part of the global community, are now challenged with the task of making highly usable Websites for a world audience. This paper identifies problems regarding multilingual and multicultural usability, examines strategies for effective translation of content, and provides suggestions for designing highly usable Websites for a global audience
Lower Bounds on Complexity of Testing Membership to a Polygon for Algebraic and Randomized Computation Trees

We describe a new method for proving lower bounds for algebraic computation trees. We prove, for the first time, that the minimum depth for arbitrary computation trees for the problem of testing the membership to a polygon with $N$ nodes is $\Omega(\log N)$. Moreover, we prove that the corresponding lower bound for the randomized computation trees matches the above bound. Finally, we prove that for the algebraic exp-log computation trees (cf. [GSY 93]), the minimum depth is $\Omega(\sqrt{\,\log N})$. We generalize the last result to the multidimensional case, showing that if an exp-log computation tree tests a membership to a semialgebraic set with a sum of Betti numbers $M$, then the depth of a tree is at least $\Omega(\sqrt{\,\log M})$.
Blind Estimation of Carrier Frequency Offset in Multicarrier Communication Systems

Orthogonal Frequency Division Multiplexing (OFDM) systems are very sensitive to carrier frequency offset (CFO), caused by either frequency differences between transmitter and receiver local oscillators or by frequency selective channels. The CFO disturbs the orthogonality among subcarriers of OFDM system and results intercarrier interference (ICI), which degrades the bit error rate (BER) performance of the system. This paper presents a new blind CFO estimation scheme for single-input single-output (SISO) OFDM systems. The presented scheme is based on the assumption that the channel frequency response changes slowly in frequency domain. In this scheme an excellent tradeoff between complexity and performance, as compared to existing estimation schemes, is obtained. The improved performance of the present scheme is confirmed through extensive simulations.
Positive and Negative quality effects in Distributed Scrum Projects: An industrial case study

As more and more software development projects utilize agile methods in a distributed environment, new process models have emerged. Distributed Scrum has increasingly gained popularity and best-practices state that the Integrated Scrums model in combination with eXtreme programming practices should be applied to maximize the software quality. However, it remains unclear if it is suitable for all types of distributed projects. Previous case studies within the field have focused on how to implement Scrum in a distributed environment and code velocity compared to other process models. However, rather few studies have taken the quality effect as a viewpoint. This paper presents a combination of a literature study and an industrial case study with the purpose of finding aspects and practices that effects the software quality in a distributed project where Scrum is utilized. This was done through a root cause analysis with an Ishikawa diagram as a tool, where the quality effects were mapped to different activities. Aspects that have had positive or negative quality effect in the project examined were analyzed and compared with literature. In addition, challenging aspects in a distributed environment are discussed and recommendations are presented. Finally, this paper concludes that when there exist a substantial amount of non-standardized legacy code, it is preferred to utilize the Scrum of Scrums model due to the decreased dependency between the Scrum-teams. This, to fully benefit from the positive quality effects that Scrum provides.
Recommending #-Tags in Twitter

Twitter, currently the most popular microblogging tool available, is used to publish more than 140,000,000 messages a day. Many users use hashtags to categorize their tweets. However, hashtags are not restricted in any way in terms of usage or syntax which leads to a very heterogeneous set of hashtags occurring in the Twitter universe and therefore, decreases the search capabilities. In this paper, we present an approach for the recommendation of highly appropriate hashtags to the user during the creation process. The recommendations aim at encouraging the user to (i) use hastags at all, (ii) use more appropriate hashtags and (iii) avoid the usage of synonymous hashtags. Therefore the vocabulary of hashtags becomes more homogenous regarding both syntax and semantics.
Dust Rings and Filaments around the Isolated Young Star V1331 Cygni

We characterize the small- and large-scale environment of the young star V1331 Cygni with high-resolution HST WFPC2 and Digitized Sky Survey images. In addition to a previously known outer dust ring (≈30′′ in diameter), the WFPC2 scattered light image reveals an inner dust ring for the first time. This ring has a maximum radius of ≈6.5′′ and is possibly related to a molecular envelope. Large-scale optical images show that V1331 Cyg is located at the tip of a long dust filament linking it to the dark cloud LDN 981. We discuss the origin of the observed dust morphology and analyze the object's relation to its parent dark cloud LDN 981. Finally, based on recent results from the literature, we investigate the properties of V1331 Cyg and conclude that in its current state the object does not show sufficient evidence to be characterized as an FU Ori object.
Two Phase Static Analysis Technique for Android Malware Detection

The growing popularity of Android based smart phones has greatly fuelled the spread of android malware. Further, these malwares are evolving rapidly to escape from traditional signature-based detection methods. Hence, there is a serious need to develop effective android malware detection techniques. In this paper, we propose two phase static android malware analysis scheme using bloom filters. The Phase I involves two different bloom filters that classify a given sample into malware or benign class based on permission feature set only. The evaded malicious samples from Phase I are further analyzed by Phase II consisting Naïve Bayes Classifier using permission and code based mixed feature set. Inclusion of Phase I classification makes the technique computationally less intensive; while addition of the Phase II classification improves the overall accuracy of the proposed model. Experimental results indicate both detection accuracy and computational efficiency of the proposed technique.
Statistical approaches to the identification of late asthmatic reactions.

Late asthmatic reactions can be difficult to recognize because of their prolonged time course and the confounding effects of superimposed circadian rhythms of ventilatory function. Conventional methods of analysis are rather arbitrary. They depend for example on a 15 or 20% fall in forced expiratory volume in one second (FEV1) from baseline or from time-matched control measurements. We have, therefore, investigated whether statistical approaches applied to individual subjects can assist in the identification of late asthmatic reactions. In two separate series of aerosol inhalation tests, three symptomatic workers, three asthmatic controls and three nonasthmatic controls were challenged blindly with increasing doses of two chemical agents, and saline. One of the agents, sodium isononanoyl oxybenzene sulphonate (SINOS) was a suspected cause of occupational asthma. Prior to the challenges, FEV1 was measured hourly on three control days. Cumulative late changes on both control and active challenge days were quantified as the area between a line extrapolated from a 10.00 h baseline and the actual measurements from 12.00-22.00 h (the 2-12 h area decrement). The area decrement measurements on control and active challenge days were compared using Student's t-tests. The sensitivity of this method for detecting late asthmatic reactions among potentially positive tests (SINOS challenge tests in the workers) was examined, as was its specificity. The latter was determined from the false positive rate among the negative tests. A second statistical method based on the pooled standard deviation of serial (hourly) FEV1 measurements was investigated in the same way. In total, the data from 220 challenge and 30 control days were available for analysis. (ABSTRACT TRUNCATED AT 250 WORDS)
Adaptive Sparse Kernel Principal Component Analysis for Computation and Store Space Constrained-based Feature Extraction

On the training samples number and kernel function and its parameter endured by Kernel Principal Component Analysis, this paper presents one-class support vector based Adaptive Sparse Kernel Principal Component Analysis (ASKPCA) through reducing the training samples with sparse learning based least squares support vector machine and adaptive self-optimizing kernel structure according to the input training samples. ASKPCA is adaptive to the computation and store space constrained applications, such as small size of hardware platform based image retrieval, medical assistant diagnosis system, and so on. Moreover, the few meaningful samples are found with solving the constraint optimization equation, and these training samples are used to compute the kernel matrix which decreases the computing time and saving space, and the algorithm is to increase the recognition accuracy and computing eﬃciency in the image processing under the hardware computing platform on the limit training samples. Experimental results on UCI datasets, ORL and YALE face databases and Wisconsin Breast Cancer database show that it is feasible to improve KPCA and Sparse Kernel Principal Component Analysis (SKPCA) on saving consuming space and optimizing kernel structure.
Anytime dynamic exploring rapid random tree approach in higher dimension search space for non-holonomic robotics

With the breakthrough of exploring Rapid Random Tree and several other improvement efforts, the sampling-based motion planning method has been gaining ground in 2D planning and gradually being accepted by many systems as their global planning algorithm. There are many recent approaches on integrating the incremental nature and algorithmic simplicity of sampling-based approach with the agile replanning strategy studied on Incremental Heuristic based motion planning algorithms. Therefore, we develop an anytime dynamic RRT∗ for non-holonomic systems. We also implement Lyapunov function, which better represents the true-cost-to-go, in order to generate ideal and smoother trajectories. Our method proved to be more robust than some state-of-the-art planning algorithms, with lower cost and smoother path. We evaluate our algorithm with 3 major benchmarks in simulated as well as real-environment. We compared our algorithm with other major planning approaches and proved the cost yields between 8.5%∼16.7% less cost and as may reach as low as 58.17% and 95% less than RRT and RRT∗ respectively.
Gaining Insights from Future Research Topics in Social Entrepreneurship: A Content-Analytic Approach

To identify what scholars consider to be important and interesting for future research in social entrepreneurship (SE), this chapter analyzes 248 SE papers and generated 327 topics for future research. From these 327 topics, a modified Delphi process generated 27 underlying themes. Subject matter experts were surveyed as to how interesting each research topic is and the extent to which the topics lend themselves to theoretical or empirical development; this assessment was also used to calculate aggregate scores for each theme. In this chapter, we present all research topics that scored at or above 2.5 on a 5-point scale for both questions. We discuss the implications of both the method and the results of the study.
Numerical Simulation of the Gas-Liquid Flow in a Square Cross-Sectioned Bubble Column

Bubble columns are widely used in the chemical and biochemical process industry. In order to develop design tools for engineering purposes, a large amount of research has been carried out in the area of CFD of gas-liquid flows. Amongst others, Becker et al. (Chem. Eng. Sci., vol. 49, p. 5747-5762, 1994) found that the gas-liquid flow in bubble columns shows pseudo-periodic behaviour. Sokolichin and Eigenberger (Chem. Eng. Sci., vol. 54, p. 2273-2284, 1999) used the k-ε model and 3D transient simulations to simulate the gas-liquid flow in 2D flat and 3D cylindrical bubble columns. Using this method, they found a grid independent pseudo-periodic solution. In the present paper the commercial code CFX 4.3 is used to simulate the gas-liquid flow in 3D rectangular bubble columns. Both these codes are 3D transient, and based on the two-fluid model. The turbulence viscosity in the liquid phase is modelled by the k-ε model and an expression, which takes the bubble-induced turbulence into account. The results of the simulations are compared with PIV and LDA measurements. The simulations of the flow of a bubble plume in a flat bubble column correspond well with both the experiments and simulation results obtained by other researchers. Both the velocity and the velocity fluctuations are in quantitative agreement with experiments. The movement of a bubble plume in a 3D bubble column was also simulated. In contrary to the other case only little temporal behaviour was found. This disagrees with the strongly time dependent flow, which was observed experimentally. In the simulation the bubble plume moves into one corner and stays there for the rest of the simulation time. This resulted in asymmetric velocity profiles. The velocity profiles are better predicted higher up in the column.
The estimation of cartoons effect on children's behavior based on exaggeration action by using neural network

Exaggeration is one of 12 basic principles of animation. The aim of exaggeration is to increase audience's significance or attention. Unfortunately, exaggeration action can be in the form of violence scenes. So, it may affect the child's psychology and behavior. This research aimed to make prediction system of cartoons which could have negative impact on children by using neural network method. The input parameters of our neural network were scenes duration, duration of exaggeration action, total duration of actions, and quantitative of exaggeration action. The output parameter of our neural network system are G, PG, PSG and R. These labels are MPPA rating value. Our neural network prediction system used three scenarios of parameters input set with back propagation method, the value of epoch: 0, number of epoch: 500, learning rate: 0.3 and momentum: 0.2. These scenarios were qualitative, quantitative and the combination of quantitative-quantitative parameters input set. The accuracy of our prediction system using quantitative parameters input set was 76%, second scenario got 63% accuracy rate and third scenario got 76% accuracy rate. This result showed that the exaggeration scene in an animation film is able to influence the behavior of children despite the scene have short duration.