Miracle-dz/UniFAR-FTUs huggingface dataset:
A Global Survey of Carbohydrate Esterase Families 1 and 10 in Oomycetes

Carbohydrate-active enzymes (CAZymes) are a cornerstone in the phytopathogenicity of filamentous microbes. CAZymes are required for every step of a successful infection cycle—from penetration, to nutrient acquisition (during colonization), to exit and dispersal. Yet, CAZymes are not a unique feature of filamentous pathogens. They are found across eukaryotic genomes and including, for example, saprotrophic relatives of major pathogens. Comparative genomics and functional analyses revealed that CAZyme content is shaped by a multitude of factors, including utilized substrate, lifestyle, and host preference. Yet, family size alone says little about usage. Indeed, in a previous study, we found that genes putatively coding for the CAZyme families of carbohydrate esterase (CE)1 and CE10, while not specifically enriched in number, were suggested to have lifestyle-specific gene expression patterns. Here, we used comparative genomics and a clustering approach to understand how the repertoire of the CE1- and CE10-encoding gene families is shaped across oomycete evolution. These data are combined with comparative transcriptomic analyses across homologous clusters within the gene families. We find that CE1 and CE10 have been reduced in number in biotrophic oomycetes independent of the phylogenetic relationship of the biotrophs to each other. The reduction in CE1 is different from that observed for CE10: While in CE10 specific clusters of homologous sequences show convergent reduction, CE1 reduction is caused by species-specific losses. Comparative transcriptomics revealed that some clusters of CE1 or CE10 sequences have a higher expression than others, independent of the species composition within them. Further, we find that CE1- and CE10-encoding genes are mainly induced in plant pathogens and that some homologous genes show lifestyle-specific gene expression levels during infection, with hemibiotrophs showing the highest expression levels.
NON-INVASIVE METHOD TO OBTAIN DNA FROM FRESHWATER MUSSELS (BIVALVIA: UNIONIDAE)

Abstract To determine whether DNA could be isolated from tissues obtained by brush-swabbing the mantle, viscera and foot, mantle-clips and swabbed cells were obtained from eight Quadrula pustulosa (Lea, 1831). DNA yields from clips and swabbings were 447.0 and 975.3 ηg/μL, respectively. Furthermore, comparisons of sequences from the ND-1 mitochondrial gene region showed a 100% sequence agreement of DNA from cells obtained by clips and swabs. To determine the number of swabs needed to obtain adequate yields of DNA for analyses, the visceras and feet of 5 Q. pustulosa each were successively swabbed 2, 4 and 6 times. DNA yields from the 2, 4 and 6 swabbed mussel groups were 399.4, 833.8 and 852.6 ng/μL, respectively. ND-1 sequences from the lowest yield still provided 846–901 bp for the ND-1 region. Nevertheless, to ensure adequate DNA yield from cell samples obtained by swabbing, we recommend that 4 swab-strokes of the viscera and foot be obtained. The use of integumental swabbing for collection of cells for determination of genetic relationships among freshwater mussels is noninvasive, when compared with tissue collection by mantle-clipping. Therefore, its use is recommended for freshwater mussels, especially state-protected or federally listed mussel species.
How Reliably Can We Measure a Child’s True IQ? Socio-Economic Status Can Explain Most of the Inter-Ethnic Differences in General Non-verbal Abilities

Roma children have been discriminated against for many years as they are denied access to high-quality education based on their scores on general non-verbal IQ tests. Rushton et al. (2007) showed that Roma perform more poorly than non-Roma on one such test (i.e., Raven Progressive Matrices), but suggest that this underperformance could be explained by Roma’s low socio-economic status. In this paper, we tested the non-verbal abilities of Roma children and expanded on the research of Rushton et al. (2007) by investigating empirically the potential mediating effects of socio-economic status on children’s performance on Raven Progressive Matrices. Results showed that the performance of Roma children was, on average, significantly lower than the performance of their non-Roma peers; however, the effect of ethnicity was partially mediated by the parents’ education and living conditions (while the parents’ income had no significant effect). As hypothesized by Rushton et al. (2007) some socio-economic factors can explain important variability in the performance of Roma children on general non-verbal tests, and their poor performance on such tests may lead to an underestimation of the true population mean.
Relational Integration in the Human Brain: A Review and Synthesis

Relational integration is required when multiple explicit representations of relations between entities must be jointly considered to make inferences. We provide an overview of the neural substrate of relational integration in humans and the processes that support it, focusing on work on analogical and deductive reasoning. In addition to neural evidence, we consider behavioral and computational work that has informed neural investigations of the representations of individual relations and of relational integration. In very general terms, evidence from neuroimaging, neuropsychological, and neuromodulatory studies points to a small set of regions (generally left lateralized) that appear to constitute key substrates for component processes of relational integration. These include posterior parietal cortex, implicated in the representation of first-order relations (e.g., A:B); rostrolateral pFC, apparently central in integrating first-order relations so as to generate and/or evaluate higher-order relations (e.g., A:B::C:D); dorsolateral pFC, involved in maintaining relations in working memory; and ventrolateral pFC, implicated in interference control (e.g., inhibiting salient information that competes with relevant relations). Recent work has begun to link computational models of relational representation and reasoning with patterns of neural activity within these brain areas.
Processing of Different Temporal Scales in the Human Brain

Abstract While recalling life events, we reexperience events of different durations, ranging across varying temporal scales, from several minutes to years. However, the brain mechanisms underlying temporal cognition are usually investigated only in small-scale periods—milliseconds to minutes. Are the same neurocognitive systems used to organize memory at different temporal scales? Here, we asked participants to compare temporal distances (time elapsed) to personal events at four different temporal scales (hour, day, week, and month) under fMRI. Cortical activity showed temporal scale sensitivity at the medial and lateral parts of the parietal lobe, bilaterally. Activity at the medial parietal cortex also showed a gradual progression from large- to small-scale processing, along a posterior–anterior axis. Interestingly, no sensitivity was found along the hippocampal long axis. In the medial scale-sensitive region, most of the voxels were preferentially active for the larger scale (month), and in the lateral region, scale selectivity was higher for the smallest scale (hour). These results demonstrate how scale-selective activity characterizes autobiographical memory processing and may provide a basis for understanding how the human brain processes and integrates experiences across timescales in a hierarchical manner.
Body RemiXer: Extending Bodies to Stimulate Social Connection in an Immersive Installation

Body RemiXer is a mixed reality installation that connects immersants across the virtual/actual divide through emergent tactility and abstract embodiment. Using a virtual reality headset, Kinect and projections, the installation explores the potential of immersive technology to create copresent experiences that foster intercorporeal relationships between immersants wearing a headset and those using the projections. Immersants’ bodies are at the center of the installation, activated as a site for social exchange. Body RemiXer has been exhibited at an art festival and at several smaller events. The authors’ observations during these exhibits reveal Body RemiXer's capacity to disrupt social norms and stimulate new connections.
Edge Effects on Sapling Characteristics and Microclimate in a Small Temperate Deciduous Forest Fragment

ABSTRACT: Edge effect is the change in forest structure and composition from the forest edge to the interior and has many conservation implications. We investigated whether sapling density, size, shade tolerance, and species composition, as well as microclimatic conditions, varied depending on proximity to, and aspect of, the forest edge. Across a small (2.25 ha), roughly square, forest fragment surrounded by agriculture, we measured density, size, and species composition of saplings less than 8.3 cm dbh, as well as light intensity, temperature, percent soil moisture, and relative humidity. To test for possible nutrient enhancement on the edges due to agricultural practices, we analyzed soil samples for differences in soil nutrients and pH between the edges and the interior. Both north and south edges had significantly higher sapling density and light intensity and lower average sapling size than the interior of the forest. Average shade tolerance of saplings was lowest on the south edge. Temperature was greatest on the south edge and relative humidity was greatest in the interior. Percent soil moisture, nutrient concentrations, organic matter, and pH showed no significant trends. Our results suggest that light is the most important environmental factor in determining species composition, density, and size of saplings across edge-interior gradients. Our results also show that species compositional edge effects do not penetrate deeply into this mature forest fragment at present, but that they likely penetrated deeper in the forest when the edge was young and narrowed as the edge matured.
The cytoskeleton of the naked green flagellate Spermatozopsis similis: Isolation, whole mount elecron microscopy, and preliminary biochemical and immunological characterization

The cytoskeleton of the naked, biflagellate green alga Spermatozopsis similis Preisig & Melkonian was isolated by treatment of cells with Nonidet P-40 (0.1%) in lysis buffer (30 mM HEPES, 5 mM EGTA, 15 mM KCl, pH 7) and studied in detail by whole-mount electron microscopy. Isolated cytoskeletons retain the twisted shape of live cells and consist of the two axonemes, the basal apparatus with 4 microtubular and two fibrous roots, and 8–10 secondary cytoskeletal microtubules (SCMT's). The four microtubular flagellar roots differ in number of microtubules (two types with 2 or 5 microtubules, respectively), in their association with fibrous roots of the system I-type (two-stranded roots), in total length (two roots with an average of 4.5 μm and two roots with and average of 7.5 μm), and in length of individual root microtubules. Certain of the root microtubules and most of the SCMT's extend to the posterior end of the cell where they converge, terminate and are interconnected by a fibrous cap-like structure, the rhizosyndesmos. This novel structure consists of a network of 2 nm filaments that presumably lacks centrin as indicated by double immunofluorescence (anti-α-tubulin and anti-centrin) of isolated cytoskeletons. Two-dimensional gel electrophoresis of isolated, purified basal apparatuses of S. similis identifies among other proteins two isoforms of centrin and α- and β-tubulin as intrinsic components.
Calculation of Current Total Harmonic Distortion for a Single-Phase Current Source Multilevel Inverter

The focus of this paper is a theoretical calculation of current Total Harmonic Distortion (THD) for a current source single-phase multilevel PWM inverter with CL-filter. Analytical approach to current ripple mean square / current THD calculation was introduced in the 1980s for a 2-level voltage source inverter with inductance dominated RL-load. This paper presents a generalization of this approach for a single-phase multilevel current source PWM inverter with an arbitrary number of current levels accounting for the CL-filter effect. The output of this research is a closed-form analytical current THD solution. Though one of the assumptions is large switching-to-fundamental frequencies ratio, the formulas are practically accurate for the said ratio larger than 20-25. The formulas become quite compact and simple without a loss of accuracy when using a Bessel function approximation. They demonstrate a single-phase PWM current source inverter current THD dependence on CL-filter parameters and current modulation index.
DCM-Based Bridgeless PFC Converter for EV Charging Application

This article proposes a single-phase switched-mode bridgeless ac–dc buck–boost derived converter that can serve as a front-end converter for the on-board electric vehicle (EV) charging application. The bridgeless scheme rules out the orthodox bridge rectifier and the affiliated losses. The proposed converter operates in discontinuous current conduction mode (DCM), thus achieving natural power factor correction for variable ac input. In addition to this, sensing of input voltage and input current is fended off because of DCM operation making the converter reliable, cost-effective, and robust compared with conventional continuous current conduction mode converters. Furthermore, the control becomes simple with the employment of a single sensor and the elimination of the phase-locked loop. The proposed front-end converter is well suited for low-voltage battery chargers ranging between 1.0 and 3.3 kW installed in golf-carts and E-rickshaws. A comprehensive steady-state analysis for one switching cycle and the design equations of the proposed converter are presented. The small-signal model of the proposed converter is presented for the implementation of the closed-loop control. Experimental results from a 1.0-kW concept-proof hardware prototype have been demonstrated, which upholds the converter analysis.
Design of GLR-Based Detectors for FDA-MIMO radar

This paper deals with the problem of adaptive detectors design for a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. At the design stage, adaptive detectors are devised according to the generalized likelihood ratio (GLR) criterion, where the target range is assumed unknown within the radar cell. In this respect, the maximum likelihood (ML) estimate of the target range under the H1 hypothesis is approximated either assuming a discrete grid of the possible values or resorting to a Newton-based optimization procedure. Numerical results are provided to illustrate the effectiveness of the devised detectors.
3D Printed Low-Cost Force-Torque Sensors

Force sensing is essential for many manipulation tasks and, more generally, for all robots physically interacting with their environment. While multi-axis force/torque sensors are readily available commercially, their cost and complex integration have so far limited a wide deployment. In this paper, we introduce a modular approach to design and to integrate low-cost force sensors directly into 3D printed robot parts. Based on off-the-shelf optical sensors embedded into deformable structures, sensitivity and load capacity can be selected from a wide range. A working six-axis sensor, including electronics, can be built for less than 20 dollars, plus a few hours of 3D printing. We present tested example designs for sensors of different complexity, from a basic one-dimensional deflecting beam to six-axis sensors with custom shapes. We summarize the basic sensor layout geometries, explain key 3D printing and integration aspects, discuss sensor calibration, and describe our Arduino firmware and ROS-based drivers.
Decentralized and Privacy-Preserving Public Auditing for Cloud Storage Based on Blockchain

Cloud storage systems provide a flexible, convenient and friendly way for users to outsource data. However, users lose control of their data once outsourcing them to the cloud. Public auditing was introduced to ensure data integrity, in which a third-party auditor (TPA) is delegated to execute auditing tasks. In general, TPA generates and sends challenge information to the cloud server (CS), which proves data possession accordingly. However, the TPA may not perform public auditing protocol honestly or may even collude with CS to deceive users. Some existing public auditing schemes utilize blockchain to resist against the malicious TPA. However, the CS may guess the challenge messages and there is a risk that users’ information may be leaked to the TPA during the process of auditing. In this paper, we propose a decentralized and privacy-preserving public auditing scheme based on blockchain (DBPA), in which a blockchain is utilized as an unpredictable source for the generation of (random) challenge information, and the auditor is required to record the audit process onto the blockchain. Due to the characteristics of blockchain, users can check the audit results publicly. Moreover, zero-knowledge proof is used in DBPA to protect user’s privacy during the audit process so that the response information returned by the CS does not leak information about user’s data. Security analysis and performance evaluation show that DBPA is secure and efficient.
Exploring Adversarial Properties of Insider Threat Detection

Insider threat represents a major cybersecurity challenge to companies and government agencies. The challenges in insider threat detection include unbalanced data, limited ground truth, and possible user behaviour changes. This research presents an unsupervised machine learning (ML) based anomaly detection approach for insider threat detection. We employ two ML methods with different working principles, specifically auto-encoder and isolation forest, and explore various representations of data with temporal information. Evaluation results show that the approach allows learning from unlabelled data under adversarial conditions for insider threat detection with a high detection and a low false positive rate. For example, 60% of malicious insiders are detected under 0.1% investigation budget. Furthermore, we explore the ability of the proposed approach to generalize for detecting unseen anomalous behaviours in different datasets, i.e. robustness. Comparisons with other work in the literature confirm the effectiveness of the proposed approach.
Analysis of Wear of the Polymer Mold in the Production of Wax Casting Models of Aircraft Engine Blades

The purpose of the following article was to conduct an analysis of the surface topography illustrating the wear of the mold socket made via the additive technique as part of the production process of wax molding patterns of blades. The form has been made of RGD720 material via the application of the PolyJet printing method. Subsequently, a measurement has been taken via a contact method and the surface topography of the socket has been measured before and after completing 30 blade castings with the application of the TalyScan 150 3D profilometer. The Sa and Sz parameters have been generated via the application of the MautainsMap software. Based on the obtained results, one may conclude that a form made with the PolyJet method may, in the future, become an alternative to injection molds made of aluminum alloy in the process of the production of short blade casting series.
Analytical flux linkage approximation prototypes for reluctance synchronous machines

This paper proposes mathematical functions as analytical flux linkage approximations for nonlinear reluctance synchronous machines with significant self- and cross-saturation effects. The nonlinear flux linkage approximations for both axes are designed with function prototypes according to saturation trends of the flux maps. The proposed approximating functions are continuous and achieve a good fitting with small approximation errors over the whole operation range; as measurement results show.
Hybrid PWM and PFM Control Strategy for LLC Resonant Converter with Hold-up Time Operation Requirement

Hold-up time operation is crucial for some applications, such as distributed power systems and server power supply, which requires voltage regulation capability when the DC bus voltage decreases in a wide range. For conventional LLC resonant converter, to satisfy the hold-up time requirement, a small magnetizing inductance value is required to boost the system output voltage, which will lead to large circulating current and efficiency degradation. To solve this problem, a novel hybrid pulse width modulation (PWM) and pulse frequency modulation (PFM) control strategy for LLC resonant converter is proposed, a bi-directional switch and auxiliary inductor is connected in parallel with the transformer. For the proposed topology, the PFM is adopted in the normal operation stage to achieve the output voltage regulation; while for the hold-up time operation, by controlling the duty cycle of the bi-directional switch, the equivalent magnetizing inductance value can be modified to satisfy the voltage gain requirement. Therefore, the LLC resonant converter can be designed only at normal operation stage. Operation principles, design considerations, and simulation and experiment results are presented in this paper.
Texture Classification based Efficient Image Compression Algorithm for Wireless Capsule Endoscopy

This paper presents a novel method for classification of blocks into smooth and edge blocks in transform domain and a compression scheme for Wireless Capsule Endoscopy (WCE) with block classifier. WCE involves capturing, transmission and processing of gastrointestinal images. Power consumption is a critical issue in WCE, as it uses a button battery driven capsule endoscope to capture and transmit images. The captured image needs to be compressed to save the transmission power and low complexity compressor should be used to avoid more power consumption from the compressor itself. JPEG based compression techniques which consists Discrete Cosine Transform(DCT), quantizer and entropy encoder provides the best compression performance with less complexity compared to other various techniques. Pixel distribution in smooth blocks is uniform and energy is compacted only into low frequency bands in spectral domain. Because high frequency bands are almost having zero energy, only low frequency bands are quantized and entropy coded which saves power in processing high bands. Most of the endoscopic image has smooth region, this method is more suitable to WCE. Proposed algorithm improves compression rate by 9% without sacrificing quality compared to JPEG based compression algorithm.
Methodology to Analyze Effect of Electric Mining Machines on the Mine Grid

Increasing use of electric driven mining machines change the planning principles for mine electric grid. This study aims to define general principles on how to determine on which terms electric machines can be added to an existing mine grid and how to plan the grid for all-electric mines. Load flow simulations and spreadsheet calculations are used for analysis. The real mine grid structure and the load cycles of electric mining machines as well as other mine loads are used for case study. In the example case, harmonic disturbances are the most critical limitation in the grid design.