Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-design

End-user development (EUD) activities range from customization to component configuration and programming. Office software, such as the ubiquitous spreadsheet, provides customization facilities, while the growth of the Web has added impetus to end-user scripting for interactive functions in Web sites. In scientific and engineering domains, end users frequently develop complex systems with standard programming languages such as C++ and Java. However, only a minority of users adapt commercial off-the-shelf (COTS) software products. Indeed, composing systems from reusable components, such as enterprise resource planing (ERP) systems, defeats most end users who resort to expensive and scarce expert developers for implementation.
Differential Modulation Schemes for Cooperative Diversity

Recent developments of wireless networks show that cooperative diversity can produce multi-input multi-output (MIMO) advantages by forming a virtual antenna array with distributed network nodes. Although differential schemes have long been appreciated in conventional MIMO communications since they provide the benefit of simplicity at the receiver by avoiding channel estimation, their performance and possible benefits in the distributed scenario have not been thoroughly investigated. In this paper, we examine two differential schemes for a cooperative diversity setup using a decode-and-forward relaying protocol. The first scheme (scheme I) is a direct extension of the conventional differential scheme for a single-input single-output (SISO) channel; whereas the second (scheme II) is a distributed cooperative counterpart of differential space-time coding (STC). We develop the maximum likelihood (ML) decision rules for two cases, in which the effect of the relay decision is captured by the transition probability. Simulations confirm that both schemes provide full diversity gain. Comparisons of the two schemes show that scheme I outperforms scheme II in terms of symbol error rate (SER); while scheme II can support a higher transmission rate, and this rate advantage increases as the number of relays increases
Mesoporous bioactive glass nanoparticles doped with magnesium: drug delivery and acellular in vitro bioactivity

The effects of the magnesium doping of binary glass (Si–Ca) on particle texture, on the biomineralization process in simulated body fluid (SBF) as well as on drug loading and release were examined. For this purpose, magnesium-doped binary bioglass nanoparticles (85SiO2–(15 − x)CaO–xMgO, with x = 1, 3, 5 and 10 mol%) were prepared by a base catalysed sol–gel method. N2 adsorption isotherm analysis showed an enhancement in specific surface area as the Mg molar fraction increased. In addition, the FTIR spectra of the samples after soaking in SBF for various periods of time confirmed the presence of new chemical bonds related to the apatite phase, as was also confirmed by SEM observations. XRD patterns of the samples after soaking revealed that the crystallization to form a more stable apatite-like phase was hindered with increasing magnesium content in the glass composition. Furthermore, it was proved that the kinetics of drug release improved with increasing magnesium content. The porosity and the specific surface area were found to be responsible for this improvement.
A secure and privacy-preserving incentive framework for vehicular cloud

Vehicular Cloud Computing (VCC) plays a critical role in data generation where a large number of vehicles collect various kinds of sensing resources with large-volume features. The resources are diversified according to various vehicle capabilities. While the information that should be collected is essential for the success of VCC applications, how to stimulate the vehicle owners to provide their sensing resources in VCC is also crucial to its success. When vehicle owners choose to contribute their data for economically appealing compensation, they may be concerned about their privacy. This thesis first proposes a promising secure and privacy-preserving incentive mechanism framework for VCC. An incentive to convince vehicle owners with excess on-board capabilities to join in VCC without the risk of privacy disclosure. The incentive mechanism employs game theory to model the interactions between the VCC server and vehicles. With the incentive mechanism, the VCC server, which represents the task announcement can select competent vehicles to collaborate for the announced task, and the vehicle owners can earn payments from their participation. Further, the incentive mechanism guarantees the fairness between all participants in terms of payment. This is because the critical payment scheme can ensure the truthfulness of all the participants such that each vehicle honestly reports its true sensing cost. The signcryption technique and homomorphic concept are exploited to achieve mutual authentication between the VCC server and vehicles, and prevent the privacy information of these vehicles from being disclosed. Simulation results are provided to show that the privacy-preserving incentive mechanism is beneficial to both the VCC server and vehicles to achieve a win-win situation. Moreover, we study the situation in which the VCC server announces a spatial task that can be exploited by an adversary or malicious Roadside unit (RSU) to reveal vehicles’ privacy. Protecting the privacy of participants becomes an essential to the prosperity of the VCC applications. Therefore, we propose a novel secure and privacy-preserving scheme for enhancing security in VCC-based tasks announcement. The proposed scheme combines a multiple receiver signcryption technique with proxy re-encryption in order to protect message content that includes the private information of the vehicles from being disclosed during task announcement. The scheme can achieve data confidentiality and integrity against the malicious RSU, which means that the RSU is not able to access private information or corrupt the task announcement during the recruiting process. The distinctive feature of the proposed scheme eliminates the issue of increasing the computation delay that most of the multiple receiver signcryption schemes are suffering from when the number of receivers increases. Compared to the other multiple receiver signcryption
A study on cooperative interference detection for UWB systems

Ultra-WideBand (UWB) system shares the same frequency band with the other wireless communication systems. It is, however, necessary to detect the presence of the other wireless systems as primary systems in order to avoid interference to them. For this purpose, the energy detection method detects the presence of the primary system based on the observed energy at individual UWB device. On the other hand, in the cooperative-detection method, a master UWB device gathers the received signals from slave UWB devices and detects the presence of the primary system by combining the signals. However, the cooperative method does not consider spacial positions of the UWB devices and the primary system. In this paper, we propose a new detection method based on a combination of the received signals at more than two UWB devices. Although the conventional cooperative-detector provides one result, the proposed detector can provide some results for each UWB device. By computer simulations, we show an availability of the proposed method by comparing with the conventional one.
Intersystem Crossing in Thiobases Proceeds by a Dark Intermediate State

Thiobases are DNA or RNA nucleobases where an exocyclic carbonyl oxygen is replaced by a sulfur atom [1]. Thiation induces a red-shift in the absorption spectrum and causes also a dramatic change in the photophysics with respect to the canonical nucleobases: while in DNA/RNA monomers internal conversion from the photoexcited singlet 1ππ∗ state to the ground state mediated by a conical intersection (CI) is the main deactivation channel, the major relaxation pathway in thiobases is via the population of triplet states through an ultrafast intersystem crossing (ISC). Thiobases have attracted much interest in recent years due to their photo-therapeutic applications [1]. In spite of that, their ultrafast deactivation mechanisms are still debated.
Adductor Canal Block for Total Knee Arthroplasty: A Review of the Current Evidence

The positive impact of regional anesthesia on surgical outcome has continued to evolve. In recent years, the focus of acute pain management strategies following total knee arthroplasty has shifted from femoral nerve block to adductor canal block. We systematically analyzed the safety and efficacy of adductor canal blocks by reviewing 78 peer-reviewed publications, including 13 randomized controlled trials. There are a number of studies supporting the adductor canal nerve block as a viable alternative for postoperative analgesia after total knee arthroplasty. This novel block has been consistently demonstrated to have equivalent analgesic efficacy compared to femoral nerve block, while simultaneously reducing quadriceps weakness significantly less than femoral nerve block, thus facilitating earlier active mobilization. With focus on early rehabilitation, adductor canal block may be considered a contributory factor preventing complications such as deep vein thrombosis and joint rigidity from the lack of early mobilization. These advances could potentially result in a reduction of total length of hospital stay and therefore a reduction in associated health care costs. Based on the current evidence, we recommend that an adductor canal block could replace a femoral nerve block as the primary regional analgesic following total knee arthroplasty. *Corresponding author: Stanley C. Yuan, Department of Anesthesiology, Virginia Mason Medical Center 1100 9th Avenue, Seattle, Washington, 98101, USA United States,Tel: (206) 223-6980; E-mail: Stanley.yuan@virginiamason.org
Dynamically Reconfigurable High Impedance and Frequency Selective Metasurfaces Using Piezoelectric Actuators

Novel dynamically reconfigurable low-loss high impedance and frequency selective metasurfaces (FSmSs) are presented, operating at around 15 GHz and incorporating compact piezoelectric actuators. The high impedance metasurface (HIS) consists of an array of metallic elements printed on a thin dielectric substrate, placed over a ground plane, and supported by the actuators. Under a dc bias, the actuators produce a displacement between the two layers, resulting in a change in the reflection phase response. Furthermore, novel multilayer FSmSs are proposed achieving significant tuning of their passband response with low losses. The FSmSs consist of three closely spaced periodic arrays of subwavelength nonresonant elements, namely, an array of metallic square loops placed between two arrays of square apertures in metallic sheets, separated by air cavities. The combination of the square loop array and one of the square aperture arrays produces a high impedance surface response, which is tuned using the piezoelectric actuators. This in turn alters the resonance condition of the complete FSmS structure and thus the central frequency of the passband. The structures have been investigated through simulations and measurements with good agreement, achieving an experimental frequency tuning range of 17% for the HIS and of 8.8% for the FSmS as well as a maximum phase shift of over 177° for the HIS at approximately 14 GHz.
Efficient Wavelet-Based Image Retrieval Using Coarse Segmentation and Fine Region Feature Extraction

Semantic image segmentation and appropriate region content description are crucial issues for region-based image retrieval (RBIR). In this paper, a novel region-based image retrieval method is proposed, which performs fast coarse image segmentation and fine region feature extraction using the decomposition property of image wavelet transform. First, coarse image segmentation is conducted efficiently in the Low-Low(LL) frequency subband of image wavelet transform. Second, the feature vector of each segmented region is hierarchically extracted from all different wavelet frequency subbands, which captures the distinctive feature (e.g., semantic texture) inside one region finely. Experiment results show the efficiency and the effectiveness of the proposed method for region-based image retrieval.
New Optimized Soft Computing Speed Controller for PMSM Drive

This study proposes a soft computing speed controller where recurrent neural network speed controller is trained by genetic extended kalman filter, based on a predetermined genetic Proportional Integral (PI) controller. A genetic PI gives to this proposed speed controller exact values without mathematical equations, unlike the classical PI who is need for it necessary. With this proposed method the results of simulation obtained is as they are of real state of the Permanent Magnet Synchronous Motor (PMSM). The harmonic ripples of speed response are also minimized with Genetic Extended Kalman Filter (GEKF) and Neural Network Space Vector Modulation (NNSVM). This fusion between the Artificial Intelligence (AI) and optimized method of the extended kalman filter gives more superiority to the method proposed, like shows the simulations results compared to classical Neural Network Controller (NNC).
A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control

This paper proposes a novel brain-machine interfacing (BMI) paradigm for control of a multijoint redundant robot system. Here, the user would determine the direction of end-point movement of a 3-degrees of freedom (DOF) robot arm using motor imagery electroencephalography signal with co-adaptive decoder (adaptivity between the user and the decoder) while a synergetic motor learning algorithm manages a peripheral redundancy in multi-DOF joints toward energy optimality through tacit learning. As in human motor control, torque control paradigm is employed for a robot to be adaptive to the given physical environment. The dynamic condition of the robot arm is taken into consideration by the learning algorithm. Thus, the user needs to only think about the end-point movement of the robot arm, which allows simultaneous multijoints control by BMI. The support vector machine-based decoder designed in this paper is adaptive to the changing mental state of the user. Online experiments reveals that the users successfully reach their targets with an average decoder accuracy of over 75% in different end-point load conditions.
Screening and Isolation of Penicillinase Inhibitor, KA-107

It is known that penicillin resistance of bacteria is mainly caused by the inactivation of penicillin by penicillinase derived from such strains. We have developed a screening procedure for penicillinase inhibitors. Several microorganisms were found to produce such inhibitors, and from the culture filtrate of Streptomyces gedanensis ATCC 4880 a penicillinase inhibitor, named KA-107, was isolated. The characteristics of this inhibitor were revealed by an in vitro test by using penicillinase derived from penicillin resistant Staphylococcus aureus, FS-1277. When KA-107 was used in combination with penicillin-G, ampicillin, d- or l-phenethicillin, the growth inhibitory activity of these penicillins was maintained.
Decoupling Encoder and Decoder Networks for Abstractive Document Summarization

Abstractive document summarization seeks to automatically generate a summary for a document, based on some abstract “understanding” of the original document. State-of-the-art techniques traditionally use attentive encoder–decoder architectures. However, due to the large number of parameters in these models, they require large training datasets and long training times. In this paper, we propose decoupling the encoder and decoder networks, and training them separately. We encode documents using an unsupervised document encoder, and then feed the document vector to a recurrent neural network decoder. With this decoupled architecture, we decrease the number of parameters in the decoder substantially, and shorten its training time. Experiments show that the decoupled model achieves comparable performance with state-of-the-art models for in-domain documents, but less well for out-of-domain documents.
The Ethanol-Gas Flex Fuel car : What is the option value of choosing your own Fuel ?

Renewable energy sources are becoming more important as the world’s supply of fossil fuels decrease and also due to environmental concerns. Since 2003, when the ethanol-gasoline flex fuel car became commercially available in Brazil, the growth of this market has been significant, to the point where currently 40% of the fuel consumption in Brazil is from renewable biofuels. This has been made possible due to the success of the flex fuel car, which can run on ethanol, gasoline, or any mix of these in the same fuel tank, and which is sold at a premium over the non flex models, Flex fuel cars, on the other hand, provide the owner with the flexibility to choose fuels at each refueling stop. Given the uncertainty on future prices of ethanol and gas, this option adds value to the owner since he can always opt for the cheaper fuel whenever he fills up his car. We use the Real Options method to analyze the value of the flex fuel option assuming both a Geometric Brownian Motion and Mean Reverting diffusion processes and compare the results for both methods. We conclude that the flex option value is significant using either 2 method and twice as high as flex premium charged by the car manufacturers, which help explain the success that this type of automobile has enjoyed in Brazil since 2003. Our results also indicate that consumers should be wiling to purchase flex fuel cars even if manufactures increase the flex premium.
A prototype for continuous security awareness in financial institutions

Information security is recognized as a management issue. Sarbanes-Oxley specifies that management is ultimately responsible for the security, accuracy, and privacy of information relating to corporate financial records and by ricochet the protection of Personally Identifiable Information (PII). Many organizations have established information security program. One of the key components of an information security program is to build security awareness as humans are considered as the weakest link of the security chain. In order for security awareness programs to add value to an organization and stay effective against the threat against human hacking, it is important to measure and continuously improve its effectiveness. This paper uses design science research approach to propose a prototype for continuous security awareness improvement in financial institutions. The prototype will be contribution in the information security field and will guide decision makers at financial institutions in their choice of security awareness product.
A Systems Approach to the Evaluation of Packaging Design Alternatives

This invention is directed to gels which are stable in storage, comprising a polymer matrix, a liquid dispersing agent embedded therein and optionally fillers or additives, characterized in that said polymer matrix is a polycondensation product of aldehydes and aminoplast-formers, at least 30% by weight of the aminoplast-formers having a molecular weight of between 200 and 10,000 and containing at least one ether, thioether, acetal, ester, urethane and/or carbonate group.
Detection and localization of hippocampal activity using beamformers with MEG: A detailed investigation using simulations and empirical data

The ability to detect neuronal activity emanating from deep brain structures such as the hippocampus using magnetoencephalography has been debated in the literature. While a significant number of recent publications reported activations from deep brain structures, others reported their inability to detect such activity even when other detection modalities confirmed its presence. In this article, we relied on realistic simulations to show that both sides of this debate are correct and that these findings are reconcilable. We show that the ability to detect such activations in evoked responses depends on the signal strength, the amount of brain noise background, the experimental design parameters, and the methodology used to detect them. Furthermore, we show that small signal strengths require contrasts with control conditions to be detected, particularly in the presence of strong brain noise backgrounds. We focus on one localization technique, the adaptive spatial filter (beamformer), and examine its strengths and weaknesses in reconstructing hippocampal activations, in the presence of other strong brain sources such as visual activations, and compare the performance of the vector and scalar beamformers under such conditions. We show that although a weight‐normalized beamformer combined with a multisphere head model is not biased in the presence of uncorrelated random noise, it can be significantly biased in the presence of correlated brain noise. Furthermore, we show that the vector beamformer performs significantly better than the scalar under such conditions. We corroborate our findings empirically using real data and demonstrate our ability to detect and localize such sources. Hum Brain Mapp, 2011. © 2010 Wiley‐Liss, Inc.
Effect of Feet Reflexology on Autism Symptoms and Constipation in Children with Autistic Spectrum Disorder

The autistic Spectrum Disorder represents specific distinguishable symptoms that have frequent concurrent conditions and constipation is the most frequent. It requires an effective non-disturbing management. Reflexology is a widely used technique and documented as a useful nursing intervention. This study aimed to determine the effect of feet reflexology on autism symptoms and constipation in children with ASD. Subject and Methods : a quasi-experimental design was utilized and it conducted at the psychiatric outpatient clinic, Menoufia University hospital. A purposive sample of 30 children was recruited. Two instruments were utilized: Autism Treatment Evaluation Checklist (ATEC) and Constipation Assessment Questionnaire (CAQ). Results : children had lower mean scores and severity of autism symptoms on post-intervention compared to pre-intervention speech/communication, sociability, sensory/cognitive, health/physical/behavior subdomains and the total ATEC score. The mean total score of constipation symptoms was lower on post-intervention compared to pre-intervention (35.93±16.04, 40.23±17.51 respectively) and there was a significant correlation (R=0.858) at the 0.01 level of significance between constipation and the severity of autism symptoms on post-intervention. Conclusion : the study concluded that autistic children exposed to feet reflexology experienced lower mean scores of autism symptoms and less severity of constipation compared to pre reflexology massage. There was a significant correlation between constipation and the severity of autism symptoms on post-intervention. Recommendation: Feet reflexology should be integrated as a part of routine daily care for autistic children and courses that enable nurses to obtain a certification in reflexology are needed. Keywords: Autism Symptoms, Constipation, Reflexology DOI : 10.7176/JHMN/60-09 Publication date :March 31 st 2019
User Selection Methods for Multiuser Two-Way Relay Communications Using Space Division Multiple Access

In this paper, we design a multiuser two-way relay system using space division multiple access (SDMA) communications and devise an optimal scheduling method that maximizes the sum rate while ensuring fairness among users. To reduce the computational load at the relays, we propose rate- and angle-based suboptimal scheduling methods. The numerical results illustrate tradeoff between complexity and the performance. Specifically, when the relay has two antennas, we verify that the rate-based method can provide significant computational savings at the cost of a rate reduction of less than 4% when compared with the optimal scheduling method.