Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinctively variable sequence-based nuclear DNA markers for multilocus phylogeography of the soybean- and rice-infecting fungal pathogen Rhizoctonia solani AG-1 IA

A series of multilocus sequence-based nuclear DNA markers was developed to infer the phylogeographical history of the Basidiomycetous fungal pathogen Rhizoctonia solani AG-1 IA infecting rice and soybean worldwide. The strategy was based on sequencing of cloned genomic DNA fragments (previously used as RFLP probes) and subsequent screening of fungal isolates to detect single nucleotide polymorphisms (SNPs). Ten primer pairs were designed based on these sequences, which resulted in PCR amplification of 200-320 bp size products and polymorphic sequences in all markers analyzed. By direct sequencing we identified both homokaryon and heterokaryon (i.e. dikaryon) isolates at each marker. Cloning the PCR products effectively estimated the allelic phase from heterokaryotic isolates. Information content varied among markers from 0.5 to 5.9 mutations per 100 bp. Thus, the former RFLP codominant probes were successfully converted into six distinctively variable sequence-based nuclear DNA markers. Rather than discarding low polymorphism loci, the combination of these distinctively variable anonymous nuclear markers would constitute an asset for the unbiased estimate of the phylogeographical parameters such as population sizes and divergent times, providing a more reliable species history that shaped the current population structure of R. solani AG-1 IA.
Composing code generators for C&C ADLs with Application-specific behavior languages (tool demonstration)

Modeling software systems as component & connector architectures with application-specific behavior modeling languages enables domain experts to describe each component behavior with the most appropriate language. Generating executable systems for such language aggregates requires composing appropriate code generators for the participating languages. Previous work on code generator composition either focuses on white-box integration based on code generator internals or requires extensive handcrafting of integration code. We demonstrate an approach to black-box generator composition for architecture description languages that relies on explicit interfaces and exploits the encapsulation of components. This approach is implemented for the architecture modeling framework MontiArcAutomaton and has been evaluated in various contexts. Ultimately, black-box code generator composition facilitates development of code generators for architecture description languages with embedded behavior languages and increases code generator reuse.
Optimizing transformational leadership and knowledge management as keys to innovation

This report intends to enhance the reviews on leadership literature by conducting a bibliometric study on 198 publications focused on transformational leadership research. These papers were published in the Scopus database between 1997 and 2023. Employing quantitative bibliometric analysis, the study aims to identify both current and prospective research trajectories pertaining to transformational leadership issues. To the best of our current understanding, there exists no scholarly investigation that examines the bibliographic data pertaining to transformational leadership domains. Therefore, this work represents a distinctive and original contribution to the existing body of literature. This study additionally offers a comprehensive examination of the patterns and paths inside a visual and schematic framework for the investigation of this subject matter. This may facilitate researchers in comprehending the prevailing patterns and prospective avenues for research, so empowering future authors to carry out their investigations with greater efficacy. There exists a number of underexplored themes or subjects pertaining to transformational leadership matters, such as knowledge sharing, leadership styles, digital transformation, innovative work behavior, competitive advantage and digital transformation. This discovery offers useful insights into the heterogeneous nature of this area across multiple disciplines.
Fast solution for the radiation of microstrip antenna arrays covered with metamaterial superstrates

A very fast and accurate analytical solution for the radiation fields of microstrip antenna arrays covered with artificial magneto-dielectric superstrates is proposed. The analytical solution is based on the reciprocity theorem in conjunction with the transmission line analogy and the cavity model. The artificial superstrate is designed using broadside coupled split ring resonator (SRR) inclusions. The proposed analytical formulation is validated with comparison with both full-wave simulations and measurements. The proposed formulation requires only 2.5 % of the time required by full-wave analysis.
GIS Internal Disconnector Fault Diagnosis Based on KPCA-ISSA-SVM Method

In order to diagnose the fault of disconnector in gas insulated switchgear (GIS) more efficiently, the paper proposes a signal processing and fault classification method which combines kernel principal component analysis (KPCA) and improved sparrow search algorithm (ISSA) to optimize support vector machine (SVM). Firstly, the different working states of the disconnector in GIS are simulated experimentally, and the vibration signals under the corresponding state are obtained by NI data acquisition software. Then the entropy and time domain characteristics of the vibration signal are calculated, and the variance contribution rate of each characteristic value is calculated by KPCA method. The first eight principal components whose cumulative variance contribution rate is greater than 99% are taken as the final feature vector. Finally, ISSA algorithm was used to optimize the penalty factor and kernel parameters in the SVM model, and the KPCA-ISSA-SVM fault diagnosis model was established. The final feature vector was taken as the model input, and the fault classification diagnosis was carried out on the disconnector in GIS. The experimental results show that the proposed method can remove redundant information, simplify the diagnosis model, and improve the diagnosis accuracy and efficiency. Even in the case of few fault samples, the limited feature quantity can realize the efficient fault diagnosis of the disconnector in GIS.
A multiscale feature extraction approach for 3D range images

This paper presents a multiscale feature extraction technique for 3D range images. Optimized and improved 3D Gaussian filtering and saliency map computation have been conceived jointly to the exploitation of connectivity relationships naturally induced by the 2D acquisition grid. The proposed algorithmic and implementation solutions guarantee good repeatability of detected features on different views and demonstrated superior computational performance compared to other known approaches.
Optical Routing for 3D System-On-Package

Optical interconnects enable faster signal propagation with virtually no crosstalk. In addition, wavelength division multiplexing allows a single waveguide to be shared among multiple interconnects. This paper proposes efficient algorithms for the construction of timing and congestion-driven waveguides considering the optical resource constraints. We develop the first optical router for system-on-packages (SOPs), which reduce electrical wirelength by 11% and improve performance by 23%, when a single optical layer is introduced for every placement layer
Controls on redox-sensitive trace metals in the Mauritanian oxygen minimum zone

Abstract. The availability of the micronutrient iron (Fe) in surface waters determines primary production, N2 fixation, and microbial community structure in large parts of the world's ocean, and thus it plays an important role in ocean carbon and nitrogen cycles. Eastern boundary upwelling systems and the connected oxygen minimum zones (OMZs) are typically associated with elevated concentrations of redox-sensitive trace metals (e.g., Fe, manganese (Mn), and cobalt (Co)), with shelf sediments typically forming a key source. Over the last 5 decades, an expansion and intensification of OMZs has been observed and this trend is likely to proceed. However, it is unclear how trace-metal (TM) distributions and transport are influenced by decreasing oxygen (O2) concentrations. Here we present dissolved (d; <0.2 µm) and leachable particulate (Lp; >0.2 µm) TM data collected at seven stations along a 50 km transect in the Mauritanian shelf region. We observed enhanced concentrations of Fe, Co, and Mn corresponding with low O2 concentrations (<50 µmol kg−1), which were decoupled from major nutrients and nutrient-like and scavenged TMs (cadmium (Cd), lead (Pb), nickel (Ni), and copper (Cu)). Additionally, data from repeated station occupations indicated a direct link between dissolved and leachable particulate Fe, Co, Mn, and O2. An observed dFe (dissolved iron) decrease from 10 to 5 nmol L−1 coincided with an O2 increase from 30 to 50 µmol kg−1 and with a concomitant decrease in turbidity. The changes in Fe (Co and Mn) were likely driven by variations in their release from sediment pore water, facilitated by lower O2 concentrations and longer residence time of the water mass on the shelf. Variations in organic matter remineralization and lithogenic inputs (atmospheric deposition or sediment resuspension; assessed using Al as indicator for lithogenic inputs) only played a minor role in redox-sensitive TM variability. Vertical dFe fluxes from O2-depleted subsurface-to-surface waters (0.08–13.5 µmol m−2 d−1) driven by turbulent mixing and vertical advection were an order of magnitude larger than atmospheric deposition fluxes (0.63–1.43 µmol m−2 d−1; estimated using dAl inventories in the surface mixed layer) in the continental slope and shelf region. Benthic fluxes are therefore the dominant dFe supply to surface waters on the continental margins of the Mauritanian upwelling region. Overall, our results indicated that the projected future decrease in O2 concentrations in OMZs may result in increases in Fe, Mn, and Co concentrations.
Preparing Cyber-physical Systems Functional Models for Implementation

The design process of Cyber-Physical Systems (CPS) normally starts with the development of a functional model, used for simulation purposes. This model is composed of the control algorithms and a mathematical representation of the physical system to be controlled. The approach, called Assisted Transformation of Models (AST), provides a means to transform the functional model into an architectural model, which is intended to detail how the computing system should be implemented on a real (typically embedded) platform. Up to now, AST only focused on the transformation of the control part. It is assumed that the mathematical model will be treated as a device, i.e., that it will be seen as an external element to the system under development. The consequence of this assumption is that there will be work left to be done by the designers, since the control application running on a real platform requires sensing and actuation instead of the mathematical model. This paper describes how to extend the AST approach in order to transform a CPS functional model into an architectural model that also takes into consideration the sensing and actuation subsystems. For instance, it addresses how designers should modify the functional model to consider a set of sensors and actuators, the possibility to express their dynamic characteristics (like sampling frequency, time response, and period) and technological details (like communication protocol and power supply). The outcome of this proposal is not only a proper generation of the architectural model, but also an adaptation of the functional model to be used with Hardware-In-the-Loop (HIL) simulations.
A Fifty Gigabit Per Second IP Router

Aggressive research on gigabit per second networks has led to dramatic improvements in network transmission speeds. One result of these improvements has been to put pressure on router technology to keep pace. This paper describes a router, nearly completed, which is more than fast enough to keep up with the latest transmission technologies. The router has a backplane speed of 50 Gb/s and can forward tens of millions of packets per second.
The effect of a structured empathy course on the students of a medical and a nursing school.

AIM The study aims to determine the effect of an empathy course for medical and nursing school students in one university in Turkey. Being able to relate to others empathetically is important for health professionals who need to develop therapeutic relationships with people who are sick, weak, sensitive and vulnerable. Professionals need empathic communication skills and professionalism not only for patients and their families but also for colleagues and other members of the health team. METHOD All first year students (257) from a medical and a nursing school in one Turkish university in 2008-2009 and 2009-2010 were enrolled to the study. The course included 10 h of lectures on empathy and communication skills given through five consecutive weeks with 2 h in a week in the first year of both schools. Data were collected by using the Empathic Communication Skills Scale (ECSS), and the Empathic Tendency Scale (ETS) before and after the course. There were 143 medical students and 83 nursing students (total: 226, 88%) who completed the ECSS and ETS in a pre-/post-test study. FINDINGS Results demonstrated that all students received significantly higher scores for the final application than for initial scores on both scales. This implied that the targeted educational programme could have a positive effect on learning empathy and gaining empathy skills and tendency. CONCLUSION Effective educational programmes might facilitate and improve empathic skills and empathic tendency of medical and nursing students, and both male and female students benefitted from the empathy course.
Edinburgh Research Explorer Identification of shared populations of human immunodeficiency virus type 1 infecting microglia and tissue macrophages outside the central nervous system

Infection of microglia and other cells of the macrophage/monocyte lineage in the central nervous system (CNS) by human immunodeﬁciency virus type I (HIV-1) underlies the development of giant cell encephalitis (GCE). It is currently unknown whether GCE depends on the emergence of virus populations speciﬁcally adapted to replicate in cells of the monocyte/macrophage lineage and whether this also leads to the speciﬁc targeting of macrophages in other nonlymphoid tissues. Autopsy samples from lymph node, brain (frontal region), lung, and full-thickness colon sections were obtained from nine study subjects with GCE and from nine without. The two groups showed no signiﬁcant differences in CD4 counts, disease progression, or treatment history before death. Genetic relatedness between variants recovered from lymph node and nonlymphoid tissues was assessed by sequence comparison of V3 and p17 gag regions using a newly developed method that scores the sample composition at successive nodes in a neighbor-joining tree. The association index enabled objective, numerical comparisons on the degree of tissue compartmentalization to be made. High proviral loads and p24 antigen expression in the brain were conﬁned to the nine individuals with GCE. GCE was also associated with signiﬁcantly higher proviral loads in colon samples (median of the GCE (cid:1) group: 1,010 copies/10 6 cells; median of GCE (cid:2) group, 10/10 6 cells; P (cid:3) 0.006). In contrast, there were no signiﬁcant differences in proviral load between the GCE (cid:1) and GCE (cid:2) groups in lymph node or lung samples, where HIV infection was manifested predominantly by inﬁltrates of lymphoid cells. V3 sequences from brain samples of individuals with GCE showed the greatest compartmentalization from those of lymph node, although samples from other tissues, particularly the colon, frequently contained variants phylogenetically related to those found in brain. The existence of shared, distinct populations of HIV speciﬁcally distributed in cells of the monocyte/ macrophage lineage was further indicated by immunocytochemical detection of CD68 (cid:1) , multinucleated giant cells expressing p24 antigen in samples of lung and colon in two individuals with GCE. This study provides the basis for future investigation of possible phenotypic similarities that underline the shared distributions of HIV variants infecting microglia and tissue macrophages outside the CNS.
Generalized Comb Decimation Filters for $\Sigma\Delta$ A/D Converters: Analysis and Design

This paper addresses the design of generalized comb decimation filters, proposing some novel decimation schemes tailored to SigmaDelta modulators. We present a mathematical framework to optimize the proposed decimation filters in such a way as to increase the SigmaDelta quantization noise (QN) rejection around the so called folding bands, frequency intervals whose QN gets folded down to baseband because of the decimation process. Comparisons are given in terms of passband drop and selectivity with respect to classic comb filters with orders ranging from 3 to 6. As far as the practical implementation of the proposed filters is concerned, we present two different architectures, namely a recursive and a nonrecursive implementation, the latter of which constitutes the basis for realizing multiplier-less generalized comb filter (GCF) realizations. We propose a mathematical framework for evaluating the sensitivity of GCFs to the approximation of the multipliers embedded in the filter architectures. The considerations deduced from the sensitivity analysis, pave the way to an optimization algorithm useful for approximating the multipliers with power-of-2 coefficients
Reliability of Anxiety Stress Irritability Behavioral Changes (Asib) – Neuro Psychosomatic Scale in the Post - Covid 19 Population

The Corona Virus Disease (COVID-19) has lead to universal psychosocial impact by causing mass hysteria, economic burden and financial losses. Mass fear of COVID-19, also called as “coronaphobia”, has generated a plethora of psychiatric problems all over the society. Disease itself multiplied by forced quarantine to combat COVID-19 applied by nationwide lockdowns can produce acute panic, anxiety, obsessive behaviors, hoarding, paranoia, and depression, and post-traumatic stress disorder (PTSD) in the long run. The ASIB neuro psychosomatic scale for post COVID - 19 patients is basically designed to evaluate the level of neuro psychosomatic impairments caused by COVID – 19.
Efficient Sublogic-Cone-Based Switching Activity Estimation using Correlation Factor

Switching activity is one of the key factors that determine digital circuits’ power consumption. While gate-level simulations are too slow to support the average power analysis of modern designs blocks (e.g., millions or even billions of gates) over a longer period of time (e.g., millions of cycles), probabilistic methods provide a solution by using RTL simulation results and propagating the switching activity through the combinational logic. This work presents a sublogic-cone-based, probabilistic method for switching activity propagation in combinational logic circuits. We divide the switching activity estimation problem into two parts: incremental propagation (across the entire circuit) and accurate calculation (within the sublogic cones). To construct the sublogic cones, we first introduce a new metric called correlation factor to quantify the impact induced by the correlations between signal nets; then we develop an efficient algorithm that uses the calculated correlation factor to guide the construction of sublogic cones. The experimental results show that our method produces 73.2% more accurate switching activity estimation results compared with the state-of-the-art method, and achieves a 19X speedup at the meantime.
COMPARATIVE STUDY ON THE DEVELOPMENT OF ETHERNET FLOW CONTROL

Ethernet has been the world's most comprehensive networking for more than 30 years. This popularity is due to its simplicity, maturity, low costs and a wide existing base. Fast and Gigabit Ethernet have brought more bandwidth to the technology and by transmitting from half-duplex to full-duplex link, Ethernet’s throughput has increased. With these properties Ethernet is expected to speed up the deployment and use of next generation networks and services. The current activity in building Gigabit speed networks, growing network bandwidth and intensive network applications led to flow control and congestion control became a high priority in network design and research. Recently, the IEEE congestion management study group has been set up to deal with the congestion and flow control problems in Ethernet networks. They had standardized a method (IEEE802.3x standard) to provide a pause-based flow control, which is applicable to all version of full-duplex Ethernet. The aim of this standard is to improve throughput, latency and packet loss. There are some problems for the IEEE802.3x standard; for instance, pause-based flow control can potentially cause heal-of-line blocking and more congestion, and in some cases quality of service (QoS) can not operate properly due to equal punishment for different traffic priority. Recent studies carried out some of these problems and have attempted to solve them in order to improve the IEEE802.3x standard. This paper analyzed and reviewed different proposed methods in terms of the strengths and weaknesses of their contributions. In addition, this paper provided future trends on the development of IEEE802.3x Ethernet flow control.
USING SPATIOTEMPORAL RELATIONAL DATA MINING TO IDENTIFY THE KEY PARAMETERS FOR ANTICIPATING ROTATION INITIATION IN SIMULATED SUPERCELL THUNDERSTORMS

This project expands upon the work outlined in McGovern et al (2007) and Rosendahl (2008) in two important ways: changing the definition of storm cells and extending the data mining techniques. The overall goal of each of these projects is to identify key parameters for tornadogenesis by applying data mining techniques to a full set of meteorological fields. This significantly differs from the traditional approach of analyzing radar data containing only reflectivity and the radial wind component. Tornadoes kill an average of 33.7 people annually and cause, in part, the $13B (Pielke and Carbone, 2002) of economic impact due to mesoscale storms annually in the United States. Although tornado forecasting has improved significantly with the introduction of Doppler radars, there is still room for improvement. The probability of detection (POD) is currently about 75%, and the false alarm ratio (FAR) is currently around 78%.