Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Zero-day Controller Hijacking Attacks on the Power-Grid with Enhanced Deep Learning

Attacks against the control processor of a power-grid system, especially zero-day attacks, can be catastrophic. Earlier detection of the attacks can prevent further damage. However, detecting zero-day attacks can be challenging because they have no known code and have unknown behavior. In order to address the zero-day attack problem, we propose a data-driven defense by training a temporal deep learning model, using only normal data from legitimate processes that run daily in these power-grid systems, to model the normal behavior of the power-grid controller. Then, we can quickly find malicious codes running on the processor, by estimating deviations from the normal behavior with a statistical test. Experimental results on a real power-grid controller show that we can detect anomalous behavior with over 99.9% accuracy and nearly zero false positives.
Thailandamide, a Fatty Acid Synthesis Antibiotic That Is Coexpressed with a Resistant Target Gene

Microbes encode many uncharacterized gene clusters that may produce antibiotics and other bioactive small molecules. Methods for activating these genes are needed to explore their biosynthetic potential. ABSTRACT Microbes encode many uncharacterized gene clusters that may produce antibiotics and other bioactive small molecules. Methods for activating these genes are needed to explore their biosynthetic potential. A transposon containing an inducible promoter was randomly inserted into the genome of the soil bacterium Burkholderia thailandensis to induce antibiotic expression. This screen identified the polyketide/nonribosomal peptide thailandamide as an antibiotic and discovered its regulator, AtsR. Mutants of Salmonella resistant to thailandamide had mutations in the accA gene for acetyl coenzyme A (acetyl-CoA) carboxylase, which is one of the first enzymes in the fatty acid synthesis pathway. A second copy of accA in the thailandamide synthesis gene cluster keeps B. thailandensis resistant to its own antibiotic. These genetic techniques will likely be powerful tools for discovering other unusual antibiotics.
Comparison of Database Search Methods for the Detection of Legionella pneumophila in Water Samples Using Metagenomic Analysis

Metagenomic analysis has become a powerful tool to analyze bacterial communities in environmental samples. However, the detection of a specific bacterial species using metagenomic analysis remains difficult due to false positive detections of sequences shared between different bacterial species. In this study, 16S rRNA amplicon and shotgun metagenomic analyses were conducted on samples collected along a stream and ponds in the campus of Hokkaido University. We compared different database search methods for bacterial detection by focusing on Legionella pneumophila. In this study, we used L. pneumophila-specific nested PCR as a gold standard to evaluate the results of the metagenomic analysis. Comparison with the results from L. pneumophila-specific nested PCR indicated that a blastn search of shotgun reads against the NCBI-NT database led to false positive results and had problems with specificity. We also found that a blastn search of shotgun reads against a database of the catalase-peroxidase (katB) gene detected L. pneumophila with the highest area under the receiver operating characteristic curve among the tested search methods; indicating that a blastn search against the katB gene database had better diagnostic ability than searches against other databases. Our results suggest that sequence searches targeting long genes specifically associated with the bacterial species of interest is a prerequisite to detecting the bacterial species in environmental samples using metagenomic analyses.
Contribution of Novel Amino Acid Alterations in PmrA or PmrB to Colistin Resistance in mcr-Negative Escherichia coli Clinical Isolates, Including Major Multidrug-Resistant Lineages O25b:H4-ST131-H30Rx and Non-x

Colistin is a last-line drug for multidrug-resistant Gram-negative bacteria. We previously reported four plasmid-mediated colistin resistance (mcr) gene-negative colistin-resistant Escherichia coli clinical isolates, including the major pathogenic and fluoroquinolone-resistant strains O25b:H4-ST131-H30Rx (isolates SRE34 and SRE44; MIC for colistin = 16 mg/liter), non-x (SME296; MIC = 8 mg/liter), and O18-ST416 (SME222; MIC = 4 mg/liter). ABSTRACT Colistin is a last-line drug for multidrug-resistant Gram-negative bacteria. We previously reported four plasmid-mediated colistin resistance (mcr) gene-negative colistin-resistant Escherichia coli clinical isolates, including the major pathogenic and fluoroquinolone-resistant strains O25b:H4-ST131-H30Rx (isolates SRE34 and SRE44; MIC for colistin = 16 mg/liter), non-x (SME296; MIC = 8 mg/liter), and O18-ST416 (SME222; MIC = 4 mg/liter). In this study, we investigated the colistin resistance mechanism and identified novel amino acid substitutions or deletions in the PmrAB two-component system that activates eptA (encoding a phosphoethanolamine transferase) and arnT (encoding an undecaprenyl phosphate-alpha-4-amino-4-deoxy-l-arabinose arabinosyl transferase) in all colistin-resistant isolates. SRE34 possessed deletion Δ27–45 (LISVFWLWHESTEQIQLFE) in PmrB, SRE44 possessed substitution L105P in PmrA, and both SME222 and SME296 included substitution G206D in PmrB. Matrix-assisted laser desorption ionization–time of flight mass spectrometry revealed that lipid A is modified with phosphoethanolamine in all four isolates. Deletion of pmrAB decreased colistin MICs to 0.5 mg/liter and lowered eptA and arnT expression. Chromosomal replacement of mutated pmrA or pmrB in colistin-susceptible O25b:H4-ST131 strain SME98 (colistin MIC = 0.5 mg/liter) increased the colistin MIC to that of the respective parent colistin-resistant isolate. In addition, SME98 mutants in which pmrAB was replaced with mutated pmrAB showed no significant differences in bacterial growth and competition culture from the parent strain, except for the mutant with L105P in PmrA, whose growth was significantly suppressed in the presence of the parent strain. In conclusion, some O25b:H4-ST131 strains appear to acquire colistin resistance via phosphoethanolamine modification of lipid A through amino acid changes in PmrAB, and the amino acid changes in PmrB do not influence bacterial growth.
Omega-6:3 Ratio More Than Absolute Lipid Level in Diet Affects Associative Learning in Honey Bees

Floral pollen is a major source of honey bee nutrition that provides them with micro- and macro-nutrients, including proteins, fatty acids, vitamins, and minerals. Different pollens vary in composition, including in the essential fatty acids, alpha-linolenic acid (omega-3) and linoleic acid (omega-6). Monocultures, prevalent in modern agriculture, may expose honey bee colonies to unbalanced omega-6:3 diets. The importance of omega-3 in the diet for adequate learning and cognitive function, with a focus on suitable omega-6:3 ratio, is well documented in mammals. We have recently shown, for the first time in invertebrates, the importance of omega-3 in diets for associative learning ability in honey bees. In the current work, we examine the effect of the absolute amount of omega-3 in diet compared to the omega-6:3 ratio on honey bee associative learning. We fed newly emerged bees for 1 week on different artificial diets, which had lipid concentration of 1, 2, 4, or 8%, with omega-6:3 ratios of 0.3, 1, or 5, respectively. We then tested the bees in a proboscis-extension response olfactory conditioning assay. We found that both omega-6:3 ratio and total lipid concentration affected learning. The most detrimental diet for learning was that with a high omega-6:3 ratio of 5, regardless of the absolute amount of omega-3 in the diet. Bees fed an omega-6:3 ratio of 1, with 4% total lipid concentration achieved the best performance. Our results with honey bees are consistent with those found in mammals. Best cognitive performance is achieved by a diet that is sufficiently rich in essential fatty acids, but as long as the omega-6:3 ratio is not high.
Collagen from Cartilaginous Fish By-Products for a Potential Application in Bioactive Film Composite

The acid solubilised collagen (ASC) and pepsin solubilised collagen (PSC) were extracted from the by-products (skin) of a cartilaginous fish (Mustelus mustelus). The ASC and PSC yields were 23.07% and 35.27% dry weight, respectively and were identified as collagen Type I with the presence of α, β and γ chains. As revealed by the Fourier Transform Infrared (FTIR) spectra analysis, pepsin did not alter the PSC triple helix structure. Based on the various type of collagen yield, only PSC was used in combination with chitosan to produce a composite film. Such film had lower tensile strength but higher elongation at break when compared to chitosan film; and lower water solubility and lightness when compared to collagen film. Equally, FTIR spectra analysis of film composite showed the occurrence of collagen-chitosan interaction resulting in a modification of the secondary structure of collagen. Collagen-chitosan-based biofilm showed a potential UV barrier properties and antioxidant activity, which might be used as green bioactive films to preserve nutraceutical products.
Evaluation of anticancer agents using patient-derived tumor organoids characteristically similar to source tissues

Patient-derived tumor xenograft models represent a promising preclinical cancer model that better replicates disease, compared with traditional cell culture; however, their use is low-throughput and costly. To overcome this limitation, patient-derived tumor organoids (PDOs) were established from human lung, ovarian and uterine tumor tissues, among others, to accurately and efficiently recapitulate the tissue architecture and function. PDOs were able to be cultured for >6 months, and formed cell clusters with similar morphologies to their source tumors. Comparative histological and comprehensive gene expression analyses proved that the characteristics of PDOs were similar to those of their source tumors, even following long-term expansion in culture. At present, 53 PDOs have been established by the Fukushima Translational Research Project, and were designated as Fukushima PDOs (F-PDOs). In addition, the in vivo tumorigenesis of certain F-PDOs was confirmed using a xenograft model. The present study represents a detailed analysis of three F-PDOs (termed REME9, 11 and 16) established from endometrial cancer tissues. These were used for cell growth inhibition experiments using anticancer agents. A suitable high-throughput assay system, with 96- or 384-well plates, was designed for each F-PDO, and the efficacy of the anticancer agents was subsequently evaluated. REME9 and 11 exhibited distinct responses and increased resistance to the drugs, as compared with conventional cancer cell lines (AN3 CA and RL95-2). REME9 and 11, which were established from tumors that originated in patients who did not respond to paclitaxel and carboplatin (the standard chemotherapy for endometrial cancer), exhibited high resistance (half-maximal inhibitory concentration >10 µM) to the two agents. Therefore, assay systems using F-PDOs may be utilized to evaluate anticancer agents using conditions that better reflect clinical conditions, compared with conventional methods using cancer cell lines, and to discover markers that identify the pharmacological effects of anticancer agents.
A Polynomial-Time Algorithm for $(2-2/k)$-stable Instances of the k-terminal cut Problem

The $k$-terminal cut problem is defined on an edge-weighted graph with $k$ distinct vertices called `terminals. ' The goal is to remove a minimum weight collection of edges from the graph such that there is no path between any pair of terminals. The $k$-terminal cut problem is known to be NP-hard. There has been interest in determining special classes of graphs for which $k$-terminal cut can be solved in polynomial time. One special class of graphs is the class of $\gamma$-stable graphs, a notion introduced by Bilu and Linial. An instance of $k$-terminal cut is said to be $\gamma$-stable if edges in the cut can be multiplied by up to $\gamma$ without changing the unique optimal solution. For several years, the best-known result for $\gamma$-stable instances of $k$-terminal cut stated that the problem can be solved in polynomial time for $\gamma \geq 4$ by solving a certain linear program. This result was recently improved to $\gamma \geq 2 - 2/k$ using the same linear program. In this paper, we match the result with a completely different approach, showing that $\gamma$-stable instances of $k$-terminal cut can be solved in polynomial time for $\gamma \geq 2 - 2/k$, with a faster algorithm. The result is surprising: we show that a known $(2 - 2/k)$-approximation algorithm for the problem actually delivers the unique optimal solution for $(2 - 2/k)$-stable graphs. For all graphs, including those which are not $(2-2/k)$-stable, there is an easy-to-check certificate to determine if the output of the algorithm is optimal. The algorithm utilizes only minimum cut procedures, obviating the use of linear programming.
How to Make Privacy Policies both GDPR-Compliant and Usable

It is important for organisations to ensure that their privacy policies are General Data Protection Regulation (GDPR) compliant, and this has to be done by the May 2018 deadline. However, it is also important for these policies to be designed with the needs of the human recipient in mind. We carried out an investigation to find out how best to achieve this.We commenced by synthesising the GDPR requirements into a checklist-type format. We then derived a list of usability design guidelines for privacy notifications from the research literature.We augmented the recommendations with other findings reported in the research literature, in order to confirm the guidelines. We conclude by providing a usable and GDPR-compliant privacy policy template for the benefit of policy writers.
Heterogeneity of Cell Surface Glutamate and GABA Receptor Expression in Shank and CNTN4 Autism Mouse Models

Autism spectrum disorder (ASD) refers to a large set of neurodevelopmental disorders, which have in common both repetitive behavior and abnormalities in social interactions and communication. Interestingly, most forms of ASD have a strong genetic contribution. However, the molecular underpinnings of this disorder remain elusive. The SHANK3 gene (and to a lesser degree SHANK2) which encode for the postsynaptic density (PSD) proteins SHANK3/SHANK2 and the CONTACTIN 4 gene which encodes for the neuronal glycoprotein CONTACTIN4 (CNTN4) exhibit mutated variants which are associated with ASD. Like many of the other genes associated with ASD, both SHANKs and CNTN4 affect synapse formation and function and are therefore related to the proper development and signaling capability of excitatory and inhibitory neuronal networks in the adult mammal brain. In this study, we used mutant/knock-out mice of Shank2 (Shank2−/−), Shank3 (Shank3αβ−/−), and Cntn4 (Cntn4−/−) as ASD-models to explore whether these mice share a molecular signature in glutamatergic and GABAergic synaptic transmission in ASD-related brain regions. Using a biotinylation assay and subsequent western blotting we focused our analysis on cell surface expression of several ionotropic glutamate and GABA receptor subunits: GluA1, GluA2, and GluN1 were analyzed for excitatory synaptic transmission, and the α1 subunit of the GABAA receptor was analyzed for inhibitory synaptic transmission. We found that both Shank2−/− and Shank3αβ−/− mice exhibit reduced levels of several cell surface glutamate receptors in the analyzed brain regions—especially in the striatum and thalamus—when compared to wildtype controls. Interestingly, even though Cntn4−/− mice also show reduced levels of some cell surface glutamate receptors in the cortex and hippocampus, increased levels of cell surface glutamate receptors were found in the striatum. Moreover, Cntn4−/− mice do not only show brain region-specific alterations in cell surface glutamate receptors but also a downregulation of cell surface GABA receptors in several of the analyzed brain regions. The results of this study suggest that even though mutations in defined genes can be associated with ASD this does not necessarily result in a common molecular phenotype in surface expression of glutamatergic and GABAergic receptor subunits in defined brain regions.
Simple Real-Time Pattern Recognition for Industrial Automation

Industrial automation often involves time-intensive operations on real-time inputs, and accuracy is critical to the functioning of the full industrial pipeline. While older methods are simplistic but inaccurate, newer methods are more accurate but often complex and time-consuming. In this paper, we achieve 100% accuracy using simple methods on an image classification task. We take advantage of the electronic systems involved in the industrial pipeline, and offer a methodology that is applicable to other tasks as well. This paper describes our method, and details all the technicalities considered while designing it. An analysis of the edge cases of our method is also made.
Power-based Side-Channel Instruction-level Disassembler

Modern embedded computing devices are vulnerable against mal-ware and software piracy due to insufficient security scrutiny and the complications of continuous patching. To detect malicious activity as well as protecting the integrity of executable software, it is necessary to monitor the operation of such devices. In this paper, we propose a disassembler based on power-based side-channel to analyze the real-time operation of embedded systems at instruction-level granularity. The proposed disassembler obtains templates from an original device (e.g., IoT home security system, smart thermostat, etc.) and utilizes machine learning algorithms to uniquely identify instructions executed on the device. The feature selection using Kullback-Leibler (KL) divergence and the dimensional reduction using PCA in the time-frequency domain are proposed to increase the identification accuracy. Moreover, a hierarchical classification framework is proposed to reduce the computational complexity associated with large instruction sets. In addition, covariate shifts caused by different environmental measurements and device-to-device variations are minimized by our covariate shift adaptation technique. We implement this disassembler on an AVR 8-bit microcontroller. Experimental results demonstrate that our proposed disassembler can recognize test instructions including register names with a success rate no lower than 99.03% with quadratic discriminant analysis (QDA).
WB-Trees: A Meshed Tree Representation for FinFET Analog Layout Designs*

The emerging design requirements with the FinFET technology, along with traditional geometrical constraints, make the FinFET-based analog placement even more challenging. Previous works can handle only partial FinFET-induced design constraints because some new constraints are intrinsically different from the traditional ones; as a result, directly extending previous methods to handle FinFET-induced constraints would incur solution quality degradation and runtime overhead. To remedy these disadvantages, we present a new hybrid graph (meshed tree) representation of a window mesh and CB-trees (namely, WB-trees) and a new placement flow with effective and efficient schemes to simultaneously handle FinFET-based design constraints and traditional ones. Experimental results based on industrial designs with various constraints show that our placer outperforms published works in both solution quality and runtime.
Genetic Algorithm Based QoS Perception Routing Protocol for VANETs

A genetic algorithm (GA) based QoS perception routing protocol (GABR) is proposed to guarantee the quality of service (QoS) influenced by broken links between vehicles and the failure of packets transmission in a vehicular ad hoc network (VANET). With the observation that all improvable paths are probed by the intersection based routing protocol, the genetic GA is utilized to optimize the global available paths which satisfies the QoS requirement. Moreover, by means of the numerical results, it is shown that the proposed scheme is significantly improved compared with protocols of the intersection based routing (IBR) and connectivity aware routing (CAR) in terms of transmission delay and packet loss rate.
Platelet Aggregation in Healthy Participants is Not Affected by Smoking, Drinking Coffee, Consuming a High-Fat Meal, or Performing Physical Exercise

Platelet aggregation can be measured using optical aggregation (light transmission aggregometry, LTA) as well as by impedance (Multiplate analyzer). The LTA (the gold standard method) can be influenced by many preanalytical variables. Several guidelines differ in recommendations for the duration patients should refrain from smoking, coffee, fatty meals, and physical exercise prior to blood collection for performing platelet function tests. In this pilot study, the influence of smoking, coffee, high-fat meal, or physical exercise on platelet aggregation was investigated to improve patient friendliness and laboratory logistics in platelet function diagnostics. Standardized blood collection was performed when participants were fasting and after each parameter (n=5 per group). As a control for diurnal fluctuations, participants (n=6) were fasting during both blood collections. Platelet aggregation was executed using standardized methods for LTA and Multiplate analyzer. Statistical analysis of the results using Wilcoxon signed-rank test did not show any significant differences in platelet aggregation in healthy participants under different preanalytical variables. Therefore, these variables are not expected to adversely affect testing, which can avoid canceling tests for those patients who inevitably did.
SPECIAL REVIEW: SMALL G PROTEINS IN PLATELETS Rho GTPases and their downstream effectors in megakaryocyte biology

Megakaryocytes differentiate from hematopoietic stem cells in the bone marrow. The transition of megakaryocytes to platelets is a complex process. Thereby, megakaryocytes extend proplatelets into sinusoidal blood vessels, where the proplatelets undergo fission to release platelets. Defects in platelet production can lead to a low platelet count (thrombocytopenia) with increased bleeding risk. Rho GTPases comprise a family of small signaling G proteins that have been shown to be master regulators of the cytoskeleton controlling many aspects of intracellular processes. The generation of Pf4-Cre transgenic mice was a major breakthrough that enabled studies in megakaryocyte-/platelet-specific knockout mouse lines and provided new insights into the central regulatory role of Rho GTPases in megakaryocyte maturation and platelet production. In this review, we will summarize major findings on the role of Rho GTPases in megakaryocyte biology with a focus on mouse lines in which knockout strategies have been applied to study the function of the best-characterized members Rac1, Cdc42 and RhoA and their downstream effector proteins.
Efficient Batch Statistical Error Estimation for Iterative Multi-level Approximate Logic Synthesis

Approximate computing is an emerging energy-efficient paradigm for error-resilient applications. Approximate logic synthesis (ALS) is an important field of it. To improve the existing ALS flows, one key issue is to derive a more accurate and efficient batch error estimation technique for all approximate transformations under consideration. In this work, we propose a novel batch error estimation method based on Monte Carlo simulation and local change propagation. It is generally applicable to any statistical error measurement such as error rate and average error magnitude. We applied the technique to an existing state-of-the-art ALS approach and demonstrated its effectiveness in deriving better approximate circuits.