Miracle-dz/UniFAR-FTUs huggingface dataset:
Spo0J regulates the oligomeric state of Soj to trigger its switch from an activator to an inhibitor of DNA replication initiation

Control of DNA replication initiation is essential for bacterial cells to co‐ordinate the faithful replication and segregation of their genetic material. The Bacillus subtilis ATPase Soj is a dynamic protein that regulates DNA replication initiation by either inhibiting or activating the DNA replication initiator protein DnaA. Here we report that the key event which switches Soj regulatory activity is a transition in its oligomeric state from a monomer to an ATP‐dependent homodimer capable of DNA binding. We show that the DNA binding activity of the Soj dimer is required both for activation of DNA replication initiation and for interaction with Spo0J. Finally, we demonstrate that Spo0J inhibits Soj dimerization by stimulating Soj ATPase activity. The data provide a molecular explanation for the dichotomous regulatory activities of Soj, as well as assigning unique Soj conformations to distinct cellular localization patterns. We discuss how the regulation of Soj ATPase activity by Spo0J could be utilized to control the initiation of DNA replication during the cell cycle.
A Compact Planar Omnidirectional MIMO Array Antenna With Pattern Phase Diversity Using Folded Dipole Element

This paper presents a planar omnidirectional multiple-input multiple-output (MIMO) antenna with pattern phase diversity. The profiles of conventional dual-polarized omnidirectional MIMO antennas are too high to be planar integrated due to the limited bandwidth of vertical-polarized element. Therefore, a dual-channel horizontal-polarized MIMO antenna is proposed for the planar integration of omnidirectional MIMO antenna. The antenna is formed with four-element folded dipole array, and a compact feed network with two sets of 90° progressive phases is employed to feed the two channels with shared elements, thus the antenna can be integrated into a sheet of substrate with an ultralow profile of 0.8 mm. Although the polarization and radiation pattern (amplitude) of the two colocated channels are the same with each other, a high isolation is still achieved as a result of the orthogonal pattern phase. A prototype was fabricated to validate the performance. The measured highest isolation between two channels is 31.7 dB, and −10 dB isolated bandwidth is 2.29–2.57 GHz (11.7%) with S11 < −14 dB and envelope correlation coefficient less than 0.05, which shows a good diversity performance. Therefore, the proposed dual-channel antenna gives a feasible solution for the planar integration of the omnidirectional MIMO system.
Leptospira immunoglobulin‐like protein B (LigB) binding to the C‐terminal fibrinogen αC domain inhibits fibrin clot formation, platelet adhesion and aggregation

Leptospira immunoglobulin‐like (Lig) proteins including LigA and LigB are adhesins that bind to fibronectin, collagen, laminin and elastin. In addition, Lig proteins are fibrinogen (Fg)‐binding proteins, although the physiological role of the Lig–Fg interaction is unclear. In this study, a previously identified Fg‐binding region, LigBCen2 (amino acids 1014–1165 of LigB), has been further localized to LigBCen2R, which consists of the partial 11th and entire 12th Ig‐like domain (amino acids 1014–1119). LigBCen2R was found to bind to the C‐terminal αC domain of Fg (FgαCC; amino acids 392–644 in Fg α chain; isothermal titration calorimetry, KD = 0.375 µM; fluorescence spectrometry, KD = 0.364 µM). The quenching and blue shift observed for the maximum wavelength intensities of the tryptophan fluorescence spectra for FgαCCY570W upon LigBCen2RW1073C binding suggested an RGD motif close to the sole tryptophan on FgαCCY570W was buried in LigBCen2R upon saturation with FgαCC. A conformational change in LigBCen2R when bound to the FgαCC RGD motif blocked further binding to integrin αIIbβ3 on platelets, thus preventing their aggregation. LigBCen2R binding to FgαCC reduced clot formation but did not affect plasminogen and tissue‐type plasminogen activator interactions with FgαCC. This study is the first to report that a spirochaetal protein binds to the C‐terminal αC domain of Fg, which regulates thrombosis and fibrinolysis, and may help explain the pulmonary haemorrhage and thrombocytopenia seen in clinical cases of leptospirosis.
Multi-dimensional Thermometer Decoders for Unary DACs

A digital-to-analog converter (DAC) with a unary architecture requires a thermometer decoder, which delay of conversion is a bottleneck of the DAC performance. A solution is an increase of groups number in the decoder for a decrease the delay. In this paper, general case of a multi-dimensional decoder is considered, and estimations are given for a number of logic gates and for delay of conversion. Moreover, the extreme decoder is discussed, and the rule of a logic function generation is formalized.
Application of Computational Intelligence to Identify Credit Card Fraud

Recently, computational intelligence algorithms have broadly used in many intelligence and expert systems. This paper tests the usefulness of computational intelligence for detecting credit card anomaly. UCSD2009, UC San Diego data mining contest’s datasets were used to detect credit card anomaly. Different classification algorithms of computational intelligence were applied on the dataset to measure the performance. The experimental result found that these classifiers perform better to detect fraud but the misclassification rate is still so high. Among all the classifiers, MultiClassClassifier performs better because this classifier detects most of the anomalies.
A Novel Joint Change Detection Approach Based on Weight-Clustering Sparse Autoencoders

With the rapid development of earth observation technology, the number of available remote sensing data has soared dramatically. It becomes a significant problem that how to use remote sensing images and how to improve the accuracy of change detection effectively. In this paper, a novel approach for change detection using weight-clustering sparse autoencoders (WCSAE) combined object-oriented classification with difference images (DIs) is proposed. First, bi-phase images are segmented as patches through the density-based spatial clustering of applications with noise algorithm. Afterward, the average and variance of superpixels are stacked as the input of WCSAE. To reduce the redundant information of extracted features, similar weights in the hidden layer of WCSAE are clustered layer-wise under termination conditions by using the hierarchical agglomerative clustering algorithm. For the improvement of the classification accuracy, L1/2 regularization is introduced in the objective function to extract more sparse features and avoid over-fitting. Next, the post-classification change detection map is obtained by means of comparing with classification results of two phase images. Then, by using the change vector analysis technology, the difference map is yielded and also classified under WCSAE to acquire the DI classification map. Finally, the joint probability judgment is implemented on the joint scopes to determine changed and unchanged areas. The effectiveness and superiority of the proposed method are verified in accordance with the experimental results on standard datasets and actual remote sensing images.
PRAST: Using Logic Bombs to Exploit the Android Permission Model and a Module Based Solution

Android security implements a permission model to protect a user’s most sensitive data. These permissions regulate an app’s access to different aspects of the device, however, a fatal flaw of Android’s permission model is that it relies on the discretion of the user to determine which apps are granted permissions and which are not with limited assistance in their choice from the device. As a result, a specialized type of malware known as a logic bomb has affected Android devices. These logic bombs are designed to execute malicious code when activated by triggers, and can be designed to take advantage of users who poorly vet their applications or even hide themselves inside applications that appear to be benign. On Android, logic bombs usually carry out malicious intent by violating permissions, using a permission for some activity the user never intended. We have found 18 different permissions that applications can violate to carry out some form of malicious intent, and have developed an app, called HyenaDroid, to violate each of these permissions and create logic bombs. This provides evidence that the current Android security revolving around permissions is in need of either an update to the permissions model, or an additional system to assist the user with navigating the Android permissions model. Our research also proposes such a system, PRAST. PRAST is designed as a modular system, combining a level of efficiency that can be run during the download on an Android device, along with the effectiveness and accuracy of external analysis systems.
Log-based Anomalies Detection of MANETs Routing with Reasoning and Verification

Routing security plays an important role in Mobile Ad hoc Networks (MANETs). Despite many attempts to improve its security, the routing procedure of MANETs remains vulnerable to attacks. Existing approaches offer support for detecting attacks or debugging in different routing phases, but many of them have not considered the privacy of the nodes during the anomalies detection, which depend on the central control program or a third party to supervise the whole network. In this paper, we present an approach called LAD which uses the raw logs of routers to construct control a flow graph and find the existing communication rules in MANETs. With the reasoning rules, LAD can detect both active and passive attacks launched during the routing phase. LAD can also protect the privacy of the nodes in the verification phase with the specific Merkle hash tree. Without deploying any special nodes to assist the verification, LAD can detect multiple malicious nodes by itself. To show that our approach can be used to guarantee the security of the MANETs, we deploy our experiment in NS3 as well as the practical router environment. LAD can improve the accuracy rate from 2.28% to 29.22%. The results show that LAD performs limited time and memory usages, high detection and low false positives.
Using a Chatterbot as a FAQ Assistant in a Course about Computers Architecture

This Research to Practice Work in Progress presents a chatterbot used as a frequently asked questions assistant for students that follow a Computers Architecture course in the degree of Telecommunication Engineering Technology at the University of Vigo (Spain). The chatterbot is a conversational agent that interacts in natural language with the students. This agent will be in charge of doing the tasks, usually carried out by the teachers, such as answering the students’ questions and solving the common doubts that arise over and over again in every academic year. The bot is being developed in AIML (Artificial Intelligence Markup Language).
Group IVA phospholipase A2 participates in the progression of hepatic fibrosis

Group IVA phospholipase A2 (IVA‐PLA2) is an enzyme that intiates the arachidonic acid pathway and plays an important role in inflammation. We demonstrate that IVA‐PLA2 deficiency suppresses lipid deposition in the liver, which was induced by administration of a high‐fat and ‐cholesterol diet (HFCD) for 16 wk in mice. Herein, we performed 2‐dimensional gel‐based comparative proteomics to further define the suppressive effect of IVA‐PLA2 deficiency on fatty liver formation. In comparisons among 4 groups, wild‐type (WT)/normal diet (ND), IVA‐PLA2‐deficient knockout (KO)/ND, WT/HFCD, and KO/HFCD, 4 proteins, 3 of which are associated with hepatic fibrosis, were identified as molecules, of which altered expression by HFCD was suppressed in KO mice compared to WT mice. Therefore, we assessed the effect of IVA‐PLA2 deficiency on hepatic fibrosis induced by HFCD or carbon tetrachloride (CCl4) in mouse models. Biochemical and histological analyses revealed that IVA‐PLA2 deficiency markedly reduced overall collagen accumulation in the liver of HFCD‐ and CCl4‐derived mouse models. We found that IVA‐PLA2 deficiency prevented activation of hepatic stellate cells and infiltration of F4/80‐positive macrophages without affecting other immunocytes such as CD8(+) lymphocytes and natural killer cells. In summary, IVA‐PLA2 deficiency attenuates not only lipid deposition in the liver but also hepatic fibrosis formation. —Ishihara, K. , Miyazaki, A. , Nabe, T. , Fushimi, H. , Iriyama, N. , Kanai, S. , Sato, T. , Uozumi, N. , Shimizu, T. , Akiba, S. Group IVA phospholipase A2 participates in the progression of hepatic fibrosis. FASEB J. 26, 4111–4121 (2012). www.fasebj. org
An Initial Analysis of the Research on Interest and Introductory Programming : A Systematic Review of this Literature

This Research Full Paper presents a review of the literature related to novices’ interest in learning to code. Students’ interest in this topic has been mentioned in the Computer Science Education (CSE) field since the 1990s. Although it got the attention of computing faculty and shaped a wide number of proposals, students’ disinterest remains a complex struggle in Computer Science (CS) courses. On the other hand, we still have little knowledge about what theoretical concepts and methods of research are adopted by researchers who study interest, particularly among novices in programming. As an attempt to close this gap, we carried out a systematic review process to identify frequent assumptions and methodological decisions aiming to establish a sense of what happened in the last seventeen years in this research field. Based on our review, the findings revealed that although a high number of contributions is propagated, most of them are based on lesson learned reports that fail in producing reliable evidences to substantiate the effectiveness of some proposals. The analysis of the 36 publications considered relevant to our systematic review revealed that there is not a convergent understanding between CSE researchers of what is interest and how to measure. Not many of them study interest based on specific theories or observe how students’ interest changes over time. So, although we have found many publications referring to practical and experimental applications, we could see that this research area is still fragmented and led by a bit of uncertainty about what really can sustain novices more interested in learning coding.
Customization of an example-based dialog system with user data and distributed word representations

There is a need to develop spoken dialog systems which are capable of engaging in natural conversations with people, for example, the socially-isolated elderly. We propose an example-based dialog system featuring an adaptation method which customizes the dialog for each user. After retrieving user profile-related information from the Web, named entity extraction is applied to the retrieval results. Words with a high term frequency-inverse document frequency (TF-IDF) score are adopted as user related words. We then calculate the similarity between the selected user-related words and words in the existing example phrases of the dialog system. Cosine similarity between the distributed representations of the nouns is calculated using word2vec embedding. We then generate phrases adapted to the user by substituting user-related words for highly similar words in the original example phrases. Word2vec also has a special property which allows arithmetic operations such as plus and minus to be applied to distributed word representations. By applying operations to the words used in the original phrases, we were able to derive replacement words related to the user and insert them in the example phrases. We evaluated the naturalness of the generated phrases and found that the system could generate natural phrases.
Verification of CFD Method for Meshing Analysis on the Propeller Performance with OpenFOAM

This paper inspects the capability if using the Computational Fluid Dynamics (CFD) tools to investigate the effect of free surface with marine propeller. We conducted the numerical simulation for propeller performance on the open-water test. The numerical simulations were compared the meshing strategies for the propeller. The simulations show that effect on the thrust and torque. The OpenFOAM was applied to solve the propeller problem, where open water performances of propeller (KP505) is estimated by a Reynold-average Navier-Stokes equations (RANS) solver which is using the three-dimensional unsteady incompressible viscous flow and using the turbulence of k-Omega SST. For the mesh generation, unstructure meshes used in the numerical simulation with hexahedral meshing. The Arbitrary mesh strategy (AMI) and Multiple Rotating Frame (MRF) were compared to define the best meshing. The meshing strategies were selected in 3 categories, e.g coarse, medium, and fine mesh. Thus, the propeller can be performed in the best mesh. The numerical results were validated with the experimental data. The KT, KQ, and Efficiency of the propeller were compared to an experimental result and for all of the meshing strategies. Thus, the simulations show the influence of meshing in order to perform the propeller performance.
Decoding CUDA Binary

NVIDIA’s software does not offer translation of assembly code to binary for their GPUs, since the specifications are closed-source. This work fills that gap. We develop a systematic method of decoding the Instruction Set Architectures (ISAs) of NVIDIA’s GPUs, and generating assemblers for different generations of GPUs. Our framework enables cross-architecture binary analysis and transformation. Making the ISA accessible in this manner opens up a world of opportunities for developers and researchers, enabling numerous optimizations and explorations that are unachievable at the source-code level. Our infrastructure has already benefited and been adopted in important applications including performance tuning, binary instrumentation, resource allocation, and memory protection.
An Efficient Secure Scheme for Lossy and Lossless Data Aggregation in Smart Grid

In this paper, we propose an efficient secure data aggregation scheme for the smart grid, which supports both lossy and lossless data aggregation. In order to reduce the computational overhead of the control center, our proposed model includes a number of entities, called gateways, which act as intermediaries between the users and the control center. At the end of each measurement interval, each user generates a report which is encrypted using the Paillier cryptosystem and contains the user’s consumption amount during the previous measurement interval as well as his or her prediction of consumption during another interval in the future. After receiving the user’s reports, gateways perform both lossy and lossless aggregation on the encrypted reports without being aware of their contents. In lossy aggregation mode, thanks to the homomorphic property of Paillier cryptosystem, the gateways generate the aggregated data of users’ predictions in order to help the control center to estimate the future electricity usage of the grid. In the lossless aggregation mode, gateways provide the control center with the users’ billing information. Moreover, to encourage the users to predict their future consumption amounts more precisely, this scheme uses special billing policies in which the accuracy of users’ predictions can affect their total electricity costs.
Alanine Scanning Mutagenesis of the Prototypic Cyclotide Reveals a Cluster of Residues Essential for Bioactivity*

The cyclotides are stable plant-derived mini-proteins with a topologically circular peptide backbone and a knotted arrangement of three disulfide bonds that form a cyclic cystine knot structural framework. They display a wide range of pharmaceutically important bioactivities, but their natural function is in plant defense as insecticidal agents. To determine the influence of individual residues on structure and activity in the prototypic cyclotide kalata B1, all 23 non-cysteine residues were successively replaced with alanine. The structure was generally tolerant of modification, indicating that the framework is a viable candidate for the stabilization of bioactive peptide epitopes. Remarkably, insecticidal and hemolytic activities were both dependent on a common, well defined cluster of hydrophilic residues on one face of the cyclotide. Interestingly, this cluster is separate from the membrane binding face of the cyclotides. Overall, the mutagenesis data provide an important insight into cyclotide biological activity and suggest that specific self-association, in combination with membrane binding mediates cyclotide bioactivities.
20.3 A 50MHz-Bandwidth 70.4dB-SNDR Calibration-Free Time-Interleaved 4th-Order Noise-Shaping SAR ADC

Noise-Shaping SAR (NS-SAR) is an emerging ADC architecture that offers both high resolution and high energy efficiency. State-of-the-art NS-SAR ADCs eliminate the need for op-amps, which relaxes design complexity and technology scaling issues. However, existing NS-SAR ADCs, with high FoM, are limited in bandwidth [1, 2] (typically in the MHz range). This makes NS-SAR ADCs unsuitable for applications that need bandwidths in the tens of MHz range, such as wireless communications. Traditionally, high-bandwidth, high-resolution applications utilize pipeline or continuous-time sigma-delta (CT-SD) ADCs, but these architectures are much more power hungry than the NS-SAR. Thus, to increase the bandwidth of NS-SAR ADCs and extend their low-power advantages, this work presents a new time-interleaved noise-shaping SAR (TINS-SAR) architecture that enables higher bandwidth. Although time-interleaving of ADCs is difficult for high resolution, interleaving impairments can be avoided when combining interleaving with noise-shaping. Our prototype 40nm CMOS TINS-SAR ADC has a measured SNDR of 70.4dB for a 50MHz bandwidth without calibration. It consumes only 13mW and occupies 0.061mm2, making it a potential substitute for CT-SD ADCs.
Instantaneous Phase and Excitation Source Features for Detection of Replay Attacks

In present era, the spoof detection has become an integral part of biometric systems and speaker verification is no exception to it. The replay attacks are the most common, where the attacker plays the recorded speech of a user to validate a false identity claim. Currently, constant-Q cepstral coefficient (CQCC) feature based system represents the standalone benchmark for spoof detection. However, we hypothesize that the phase and excitation source information of speech may carry additional artifacts that are useful for identifying the replay attacks. In this regard, instantaneous frequency cosine coefficients and two source features namely, discrete cosine transform of integrated linear prediction residual and residual mel frequency cepstral coefficient are explored. The studies are conducted on ASVspoof 2017 Version 2.0 database designed for the replay attacks. The results reveal that the phase and source features although perform poorer than CQCC, their fusion helps to achieve an improved performance. This indicates the complementary nature of information carried by the stated features is useful for detecting replay attacks. Further, an analysis on the behavior of each of these features under different replay configurations is also presented to highlight their effect in different scenarios.