Miracle-dz/UniFAR-FTUs huggingface dataset:
A Compact Dual Band Triangular Patch Antenna with Spiral Resonator for wireless applications

A novel dual band triangular patch antenna designed using Spiral resonators (SR) in its patch is presented. The metamaterial structure (SR) used in this design effectively reduces the size of conventional patch resulting in dual resonances with wide apart spectra. The antenna is found to resonate at 10.38, 13.99 GHz with gains of 3.6 and 5.4 dBs respectively. The antenna has an Omnidirectional pattern and good directivity at the resonant bands. Keywords: Triangular Microstrip patch antenna, linear polarization, wireless applications
Occurrence, Distribution and Toxins of Benthic Cyanobacteria in German Lakes

Cyanobacteria are favored by climate change and global warming; however, to date, most research and monitoring programs have focused on planktic cyanobacteria. Benthic cyanobacteria blooms also increase and pose a risk to animal and human health; however, there is limited knowledge of their occurrence, distribution and the toxins involved, especially in relation to their planktic conspecifics. Therefore, we analyzed the benthic and planktic life forms of cyanobacterial communities in 34 lakes in Germany, including a monitoring of cyanotoxins. Community analyses were based on microscopic examination and Illumina sequencing of the 16S rRNA gene. The analyses of cyanotoxins were carried out using LC-MS/MS and ELISA. Observed benthic mats containing cyanobacteria consisted mainly of Nostocales and Oscillatoriales, being present in 35% of the lakes. Anatoxin was the most abundant cyanotoxin in the benthic samples, reaching maximum concentrations of 45,000 µg/L, whereas microcystin was the predominate cyanotoxin in the open-water samples, reaching concentrations of up to 18,000 µg/L. Based on the results, specific lakes at risk of toxic cyanobacteria could be identified. Our findings suggest that monitoring of benthic cyanobacteria and their toxins should receive greater attention, ideally complementing existing open-water sampling programs with little additional effort.
Invariant Model Combining Geometry and Appearance for Facial Detection and Gender Classification From Arbitrary Viewpoints

In this chapter, we tackle in the same process the problems of face detection and gender classification, where the faces present a wide range of the intra-class appearance are taken from arbitrary viewpoints. We try to develop complete probabilistic model to represent and learn appearance of facial objects in both shape and geometry with respect to a landmark in the image, and then to be able to predict presence and position of the appearance of the studied object class in new scene. After have predicted the facial appearance and the geometry of invariants, geometric hierarchical clustering combines different prediction of positions of face invariant. Then, the algorithm of cluster selection with a best appearance localizes faces in the image. Using a probabilistic classification, each facial feature retained in the detection step will be weighted by a probability to be male or female. This set of features contributes to determine the gender associated to a detected face. This model has a good performance in presence of viewpoint changes and a large appearance variability of faces.
Remote sensing image scene classification based on generative adversarial networks

ABSTRACT Scene classification of remote sensing images plays an important role in many remote sensing image applications. Training a good classifier needs a large number of training samples. The labeled samples are often scarce and difficult to obtain, and annotating a large number of samples is time-consuming. We propose a novel remote sensing image scene classification framework based on generative adversarial networks (GAN) in this paper. GAN can improve the generalization ability of machine learning network model. However, generating large-size images, especially high-resolution remote sensing images is difficult. To address this issue, the scaled exponential linear units (SELU) are applied into the GAN to generate high quality remote sensing images. Experiments carried out on two datasets show that our approach can obtain the state-of-the-art results compared with the classification results of the classic deep convolutional neural networks, especially when the number of training samples is small.
Polarization-independent transparent effect in windmill-like metasurface

A windmill-like metasurface featuring a polarization-independent electromagnetically induced transparency (EIT) at microwave frequencies is numerically and experimentally demonstrated. The unit cell of the metasurface consists of four rotated identical metal wires, with a 45° angle between the adjacent wires. Destructive coupling between the resonance modes of the metal wires results in the emergence of a transparent window. By combining the metal wires with different degrees of symmetry, EIT effects in the metasurface show polarization-independent properties to incident linear and circular polarization waves. In addition, it is numerically demonstrated that the metasurface possesses a low-loss slow wave property with a group index of 125 and sensing capability based on the refractive index with a figure of merit of 8.73. Such a scheme may lead to many potential applications in areas of slow light and sensing.
DETECTION OF FAST-FLUX BOTNETS THROUGH DNS TRAFFIC ANALYSIS

Botnets are networks build up of a large number of bot computers which provide the attacker with massive resources such as bandwidth, storage, and processing power. In turn allowing the attacker to launch massive attacks such as Distributed Denial of Service (DoS) attacks, or undertake spamming or phishing campaigns. One of the main approaches for botnet detection is based on monitoring and analyzing DNS query/responses in the network, where botnets make their detection more difficult by using techniques such as fast-fluxing. Moreover, the main challenge in detecting fast-flux botnets arises from their similar behavior with that of legitimate networks, such as CDNs, which employ a round-robin DNS technique. In this paper, we propose a new system to detect fastflux botnets by passive DNS monitoring. The proposed system first filters out domains seen in historical DNS traces assuming that they are benign. We believe this assumption to be valid as benign domains usually have longer life time when compared to botnet domains, which are usually short lived. Hence CDN domains which are the main cause of miss-classification, when looking for malicious fast-flux domains, are removed. Afterwards, a few simple features are calculated to help in properly categorizing the domains in question as either benign or botnet related. The proposed system is evaluated by employing DNS traces from our campus network and encouraging evaluation results are obtained.
β-Nucleated Polypropylene: Preparation, Nucleating Efficiency, Composite, and Future Prospects

The β-crystals of polypropylene have a metastable crystal form. The formation of β-crystals can improve the toughness and heat resistance of a material. The introduction of a β-nucleating agent, over many other methods, is undoubtedly the most reliable method through which to obtain β-PP. Furthermore, in this study, certain newly developed β-nucleating agents and their compounds in recent years are listed in detail, including the less-mentioned polymer β-nucleating agents and their nucleation characteristics. In addition, the various influencing factors of β-nucleation efficiency, including the polymer matrix and processing conditions, are analyzed in detail and the corresponding improvement measures are summarized. Finally, the composites and synergistic toughening effects are discussed, and three potential future research directions are speculated upon based on previous research.
Science and the international climate negotiations

W ea th er – N ov em be r 2 01 7, V ol . 7 2, N o. 1 1 ozone in the stratosphere over Antarctica in the austral spring – the ozone hole – was a shock, since it was largely unpredicted. At the same time climate concerns were growing in two directions – the potential warming impact of rising levels of greenhouses gases and the potential for a dramatic drop in temperatures following a massive nuclear exchange, dubbed a ‘nuclear winter’. The latter provided a strong impetus for efforts to limit the nuclear arms race (Oreskes and Conway, 2010). The first truly international scientific assessment of climate change was undertaken under the auspices of the International Council of Scientific Unions (ICSU), WMO and the United Nations Environment Programme (UNEP) at a meeting in Villach (1985). Subsequent meetings in Villach and Bellagio (1987) set out the main conclusions and policy options for dealing with greenhouse gases (Jaeger, 1988). Importantly, it recognised the need for a global convention to address climate change. It is also of interest to note that the recommendations identified the main direction of travel required to address climate change which we would recognise today – namely, energy efficiency, development of non-fossil energy systems, reduced deforestation, limiting the growth of non-CO2 gases, planning for sea-level rise and enhanced support for policy-related research. The initial Villach conference also called for periodic assessment of climate science, which eventually led WMO and UNEP to set up the IPCC in 1988. Up to this point it would be reasonable to say that climate change was still viewed largely as a scientific matter, although political awareness was rising, particularly on the back of the publication of the Brundtland Report, Our Common Future, which looked at the challenges of environment and development together (WCED, 1987).
Editorial: Molecular insights in plant reproductive isolation barriers

COPYRIGHT © 2023 Mino, Lafon Placette and Tezuka. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 26 July 2023 DOI 10.3389/fpls.2023. 1257823
Development of an Operational Convective Nowcasting Algorithm Using Raindrop Size Sorting Information from Polarimetric Radar Data

Raindrop size sorting is a ubiquitous microphysical occurrence in precipitating systems. Owing to the greater terminal fall speed of larger particles, a raindrop’s fall trajectory can be sensitive to its size, and strong air currents (e.g., a convective updraft) can enhance this sensitivity. Indeed, observational and numerical model simulation studies have confirmed these effects on raindrop size distributions near convective updrafts. One striking example is the lofting of liquid drops and partially frozen hydrometeors above the environmental 0°C level, resulting in a small columnar region of positive differential reflectivity ZDR in polarimetric radar data, known as the ZDR column. This signature can serve as a proxy for updraft location and strength, offering operational forecasters a tool for monitoring convective trends. Beneath the 0°C level, where WSR-88D spatiotemporal resolution is highest, anomalously high ZDR collocated with lower reflectivity factor at horizontal polarization ZH is often observed within and beneath convective updrafts. Here, size sorting creates a deficit in small drops, while relatively large drops and melting hydrometeors are present in low concentrations. As such, this unique raindrop size distribution and its related polarimetric signature can indicate updraft location sooner and more frequently than the detection of a ZDR column. This paper introduces a novel algorithm that capitalizes on the improved radar coverage at lower levels and automates the detection of this size sorting signature. At the algorithm core, unique ZH–ZDR relationships are created for each radar elevation scan, and positive ZDR outliers (often indicative of size sorting) are identified. Algorithm design, examples, performance, strengths and limitations, and future development are discussed.
A Continuous Camera Placement Optimization Model for Surround View

Increasing use of Advanced Driver Assistance Systems (ADAS) in autonomous vehicles is rising the demand for advanced perception systems. With more sensors being placed on the vehicle than ever, a need arises to optimize the placement of the sensors on the vehicle's body to maximize coverage at minimal cost. Camera Placement Optimization (CPO) methods tailored for multi-camera networks to maximize a vehicle's surrounding view coverage are limited. While existing CPO methods tend to sample the simulation space to work in the discrete domain using integer programming-based problem formulation, this article proposes a novel approach to optimize for camera poses for vehicle surround-view in the continuous domain using gradient-free blackbox optimization techniques by defining a non-linear objective function. Experimental results on more than 100 instances of real world 3D models of vehicles of various shapes and sizes show that the proposed method is effective in maximizing coverage for vehicle surround-view by a multiple camera network in a reasonable amount of time. Comparisons against a discrete CPO formulation show that the proposed method significantly improves coverage accuracy by optimizing poses of multiple cameras for vehicle surround-view.
The quasi-normal modes of quantum criticality

We study charge transport of quantum critical points described by conformal field theories in 2+1 spacetime dimensions. The transport is described by an effective field theory on an asymptotically antide Sitter spacetime, expanded to fourth order in spatial and temporal gradients. The presence of a horizon at non-zero temperatures implies that this theory has quasi-normal modes with complex frequencies. The quasi-normal modes determine the poles and zeros of the conductivity in the complex frequency plane, and so fully determine its behavior on the real frequency axis, at frequencies both smaller and larger than the absolute temperature. We describe the role of particle-vortex or S-duality on the conductivity, specifically how it maps poles to zeros and vice versa. These analyses motivate two sum rules obeyed by the quantum critical conductivity: the holographic computations are the first to satisfy both sum rules, while earlier Boltzmann-theory computations satisfy only one of them. Finally, we compare our results with the analytic structure of the O(N) model in the large-N limit, and other CFTs. 1 ar X iv :1 21 0. 41 66 v4 [ co nd -m at . s tr -e l] 1 5 Ja n 20 13
Using memory-efficient algorithm for large-scale time-domain modeling of surface plasmon polaritons propagation in organic light emitting diodes

We demonstrate an efficient approach to numerical modeling of optical properties of large-scale structures with typical dimensions much greater than the wavelength of light. For this purpose, we use the finite-difference time-domain (FDTD) method enhanced with a memory efficient Locally Recursive non-Locally Asynchronous (LRnLA) algorithm called DiamondTorre and implemented for General Purpose Graphical Processing Units (GPGPU) architecture. We apply our approach to simulation of optical properties of organic light emitting diodes (OLEDs), which is an essential step in the process of designing OLEDs with improved efficiency. Specifically, we consider a problem of excitation and propagation of surface plasmon polaritons (SPPs) in a typical OLED, which is a challenging task given that SPP decay length can be about two orders of magnitude greater than the wavelength of excitation. We show that with our approach it is possible to extend the simulated volume size sufficiently so that SPP decay dynamics is accounted for. We further consider an OLED with periodically corrugated metallic cathode and show how the SPP decay length can be greatly reduced due to scattering off the corrugation. Ultimately, we compare the performance of our algorithm to the conventional FDTD and demonstrate that our approach can efficiently be used for large-scale FDTD simulations with the use of only a single GPGPU-powered workstation, which is not practically feasible with the conventional FDTD.
The Association between Melatonin-Containing Foods Consumption and Students’ Sleep–Wake Rhythm, Psychoemotional, and Anthropometric Characteristics: A Semi-Quantitative Analysis and Hypothetical Application

Food is an important source of melatonin (MT), which belongs to a group known as chronobiotics, a class of substances that affect the circadian system. Currently, no studies have been conducted on how the consumption of foods containing MT (FMT) is associated with indicators characterizing the human circadian system. In this study, we tested the hypothesis that FMT consumption is associated with chronotype and social jetlag. A total of 1277 schoolchildren and university students aged M (SD) 19.9 (4.1) years (range: 16–25 years; girls: 72.8%) participated in a cross-sectional study. Each participant completed an online questionnaire with their personal data (sex, age, height, weight, waist circumference, and academic performance) and a sequence of tests to assess their sleep–wake rhythm (the Munich Chronotype Questionnaire), sleep quality (the Pittsburgh Sleep Quality Index), and depression level (the Zung Self-Rating Depression Scale). Study participants also completed a modified food frequency questionnaire that only included foods containing MT (FMT). They were asked how many foods containing MT (FMT) they had eaten for dinner, constituting their daily serving, in the past month. The consumption of foods containing MT (FMT) during the day (FMTday) and at dinner (FMTdinner) was assessed using this test. Multiple regression analyses were performed to assess the association between the studied indicators. We found that higher FMTday values were associated with early chronotype (β = −0.09) and less social jetlag (β = −0.07), better sleep quality (β = −0.06) and lower levels of depression (β = −0.11), as well as central adiposity (β = −0.08). Higher FMTdinner values were associated with a lower risk of central adiposity (β = −0.08). In conclusion, the data obtained confirm the hypothesis that the consumption of foods containing MT (FMT) is associated with chronotype and social jetlag in adolescents and young adults.
Estimation of Position and Resistance of a Sensorless PMSM: A Nonlinear Luenberger Approach for a Nonobservable System

We show that the pair <italic>(rotor position, resistance)</italic> of a nonsalient permanent magnet synchronous motor (PMSM) is not observable in the sensorless setting, namely, when only the electrical signals (voltages and intensities) are measured. However, if the rotation speed <inline-formula><tex-math notation="LaTeX">$\omega$</tex-math></inline-formula> and the current in rotating frame <inline-formula><tex-math notation="LaTeX">$i_d$</tex-math></inline-formula> are not constantly zero, we prove that there only exist a maximum of six indistinguishable solutions, the resistance being the root of a polynomial of degree six. Besides, in the particular case where <inline-formula><tex-math notation="LaTeX">$\omega$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$i_d$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$i_q$</tex-math></inline-formula> are constant, we show that the number of possible solutions is reduced to two, with two well-identified possible values for the resistance. Those two solutions can be dissociated if the sign of <inline-formula><tex-math notation="LaTeX">$i_q$</tex-math></inline-formula> (namely, the mode of use of the motor) is known. Inspired by the nonlinear Luenberger methodology, this property enables us to propose an estimation algorithm, which relies on a one-dimensional minimization of a criterion involving the voltages and intensities filtered at three distinct sufficiently large frequencies. Its performances are tested and illustrated in simulations on real data.
Linguistic interference in specialized translation. The case of the Italian medical language in Polish

The issue of linguistic interference will be analysed from the point of view of medical translations in the Italian-Polish linguistic pair. Since linguistic interference can manifest itself at almost all levels of the text (phonetic, orthographic, morphological, syntactic, socio-cultural), with the analysis of the fragments taken from translated medical documents we would like to understand which are the most frequent cases of the phenomenon when it comes to translated medical texts and which factors favour the interference most.
Intellectual Capital On Firm Value Through Financial Performance

This study aims to analyze the effect of intellectual capital on firm value through financial performance. This research was conducted at National Foreign Exchange Private Commercial Banks listed on the Indonesia Stock Exchange during the observation period from 2019 to 2021 and involved ten banks using a purposive sampling method. Data were analyzed using panel data regression and path analysis. The results show that human capital efficiency has a significant negative effect on financial performance; structural capital efficiency capital and employed efficiency have a significant positive effect on financial performance; human capital efficiency, capital employed efficiency, and financial performance have a significant positive effect on firm value; structural capital efficiency has a significant negative effect on firm value; human capital efficiency and capital employed efficiency have a significant negative effect on firm value through financial performance; structural capital efficiency has a significant positive effect on firm value through financial performance.
Techniques and Skills on Supervisory Leadership Relative to Teachers’ Motivation in Sariaya West District

The study aimed to determine the techniques and skills of supervisory leadership relative to teachers’ motivation. The study used of descriptive method where questionnaire was the primary data gathering instrument. One hundred fifteen (115) Teachers from Sariaya West District contributed to the study. Frequency, percentage, mean, SD and Pearson r were used in the statistical analysis of data. The study revealed as perceived by the Teachers-respondents on School Head’s Practice Techniques on Supervisory Leadership with regards to Consultative or Democratic Technique, Authoritarian or Dictatorial technique and non-inter fearing or Free-rein technique were found Evident. Likewise, rate of the school leaders often for level of Supervisory Leadership Skills in terms of Human Relation/ Interpersonal Skills, Conceptual and Technical: school head rate as Often in the Maslow’s stages of motivational theory that affect teacher- respondents in terms Physiological needs, safety needs, social needs, esteem needs and self- actualization. It was revealed that the techniques of supervisory leadership and motivation of teacher’s respondents were related with one another, the hypothesis stating that there is no significant relationship between the stated dependent variable and independent variable in the consultative and non-interfering techniques meanwhile Authoritarian technique is not supported by evidence hence it is not sustained.