Miracle-dz/UniFAR-FTUs huggingface dataset:
Competitiveness of the Exotic Silphium perfoliatum against the Native Urtica dioica: A Field Experiment

Silphium perfoliatum (cup plant) is native to North America and is increasingly used as a bioenergy crop in Germany. Spontaneous occurrences of this species have already been detected in several European countries. To assess the possible risk to biodiversity by spreading of S. perfoliatum, we investigated the competitiveness of this species against the native and highly competitive Urtica dioica over four years in a field experiment in Bayreuth (Germany). S. perfoliatum grew well among U. dioica, although its biomass was strongly reduced by surrounding U. dioica. Projection area, plant height, and reproductive potential were less or similarly reduced by surrounding U. dioica as by the intraspecific competition. Moreover, S. perfoliatum significantly suppressed the growth of the competitive U. dioica. A settlement and establishment of S. perfoliatum in the native flora of Central Europe and a suppression of uncompetitive plant species are therefore conceivable.
Classification of guitar tab and numbered musical notation using ResNet50 network

With the advancement of deep learning and the growth of AI, a new concept for classifying music score images has been introduced. This paper presents a classification method for guitar tabs and numbered musical notation based on the ResNet50 network. The ResNet50 residual network model is used to extract features from music score images, and then the classification is performed based on the recognition probability. Results of the experiments indicate that the recognition accuracy of this model can reach 99.154%, suggesting that the ResNet50 network-based classification method holds good research potential in music score image classification.
Ekstraksi Alumina (Al2O3) dari Mineral Tanah Napa Pesisir Selatan

— Alumina has a wide range of industrial and technical applications and can be extracted from different locations, materials and methods. Napa soil from the Pesisir Selatan has been used as a raw material for alumina production. This alumina extraction process is the result of modifications to several methods including alkali fusion and hydrothermal methods. Napa soil is calcined at 750 0 C for 4 hours and washed with hydrochloric acid 1,5 M; 2 M; 2.5 M at 95 0 C, followed by alkali fusion by NaOH 10 M so that it is obtained Al(OH) 3 and converted to Al 2 O 3 with the calcination of 1100 0 C. The extraction results are characterized by XRF technology to understand the content of the analyzed sample. The extraction mass of alumina with different concentrations of HCl 1 M; 1,5 M; 2 M; 2.5 M is continuous 14,171 g; 41,127 g; 31,711 g; and 0 g. The result of XRF analysis of alumina extraction showed that the Al 2 O 3 content increased by 68.42%.
Nanoencapsulation of Phenolic Extracts from Native Potato Clones (Solanum tuberosum spp. andigena) by Spray Drying

Native potato clones grown in Peru contain bioactive compounds beneficial to human health. This study aimed to optimize the spray-drying nanoencapsulation of native potato phenolic extracts utilizing a central composite design and response surface methodology, obtaining the optimal treatment to an inlet temperature of 120 °C and an airflow of 141 L/h in the nano spray dryer B-90, which allowed maximizing the yield of encapsulation, antioxidant capacity (DPPH), encapsulation efficiency (EE), total phenolic compounds, and total flavonoids; on the other hand, it allowed minimizing hygroscopicity, water activity (Aw), and moisture. Instrumental characterization of the nanocapsules was also carried out, observing a gain in lightness, reddening of the color, and spherical nanoparticles of heterogeneous size (133.09–165.13 nm) with a negative ζ potential. Thermal, infrared, and morphological analyses confirmed the encapsulation of the core in the wall materials. Furthermore, an in vitro release study of phenolic compounds in an aqueous solution achieved a maximum value of 9.86 mg GAE/g after 12 h. Finally, the obtained nanocapsules could be used in the food and pharmaceutical industry.
Influence of Deposition Time on Titanium Nitride (TiN) Thin Film Coating Synthesis Using Chemical Vapour Deposition

Titanium nitride (TiN) thin film coatings were grown over silicon (p-type) substrate using the atmospheric pressure chemical vapour deposition (APCVD) technique. The synthesis process was carried out to evaluate the effect of deposition time on the physical and mechanical characteristics of TiN coating. Thin films grown over Si substrate were further characterised to evaluate the morphological properties, surface roughness and mechanical properties using a scanning electrode microscope (SEM), atomic force microscopy (AFM) and nanoindentation, respectively. EDS equipped with SEM showed the presence of Ti and N elements in considerable amounts. TiN morphology obtained from the SEM test showed small-sized particles on the surface along with cracks and pores. AFM results revealed that by increasing the deposition time, the surface roughness of the coating also increased. The nanomechanical properties such as nanohardness (H) and Young’s modulus (E), etc., evaluated using the nanoindentation technique showed that higher deposition time led to an increase in H and E. Overall, it was observed that deposition time plays a vital role in the TiN coating deposition using the CVD technique.
Conditional quantile estimation using optimal quantization: a numerical study

We construct a nonparametric estimator of conditional quantiles of Y given X = x using optimal quantization. Conditional quantiles are particularly of interest when the condi-tional mean is not representative of the impact of the covariable X on the dependent variable Y . L p -norm optimal quantization is a discretizing method used since the 1950's in engineer-ing. It allows to construct the best approximation of a continuous law with a discrete law with support of size N . The aim of this work is then to use optimal quantization to construct con-ditional quantile estimators. We study the convergence of the approximation (N → ∞) and the consistency of the resulting estimator for this fixed-N approximation. This estimator was implemented in R in order to evaluate the numerical behavior and to compare it with existing methods.
A Bibliometric Analysis of Emotion at the Intersection of the Concepts of Biophilic and Design

Emotion is the research subject of many disciplines. Among these studies, emotion emerges as a concept related to biophilic design. The present investigation used bibliometric analysis, which included documents from the Scopus and Web of Science Core Collection stores of data to the science mapping approach in the VOSviewer. Considering the analysis’ findings, it can be said that the examination of emotion at the intersection of biophilic and design under the heading the concept of architecture is a field of study that is new, open to examination, and open to association with different concepts.
The toroidal obscuration in AGN

Observations give strong support for the unification scheme of active galactic nuclei (AGN), based on toroidal dusty obscuration of the central engine. The inevitable spread in torus properties invalidates the widespread notion that type 1 and 2 AGNs are intrinsically the same objects. Instead, AGNs are drawn preferentially from the distribution of torus covering factors; type 1 are more likely drawn from the distribution lower end, type 2 from its higher end. Studies of unification statistics cannot be performed without taking into account the intrinsic distribution of torus covering factors. The only practical way to determine this distribution function is from modeling of the infrared emission of a complete sample of AGNs blindly selected from hard X-ray surveys, such as INTEGRAL observations. The broad line region (BLR) and the dusty torus are, respectively, the inner and outer segments, across the dust sublimation radius, of a continuous cloud distribution. All clouds are embedded in a disk wind, whose mass outflow rate is diminishing as the accretion rate, i.e., AGN luminosity, is decreasing. Both the torus and BLR disappear at sufficiently low luminosities, leaving radio jets as the sole release channel for the accreted mass that does not reach the central black hole.
Leishmania infantum Axenic Amastigotes Induce Human Neutrophil Extracellular Traps and Resist NET-Mediated Killing

Neutrophils are multifaceted cells that, upon activation, release meshes of chromatin associated with different proteins, known as neutrophil extracellular traps (NETs). Leishmania amazonensis promastigotes and amastigotes induce NET release, and we have identified the signaling pathways involved in NET extrusion activated by promastigotes. Amastigotes maintain the infection in vertebrate hosts, and we have shown the association of NETs with amastigotes in human biopsies of cutaneous leishmaniasis. However, the interaction of amastigotes and neutrophils remains poorly understood. Our study aimed to characterize the pathways involved in the formation of NETs induced by axenic amastigotes from L. infantum, the causal agent of visceral leishmaniasis. Human neutrophils pretreated with signaling pathway inhibitors were incubated with amastigotes, and NET release was quantified in the culture supernatant. Amastigote viability was checked after incubation with NETs. We found that the release of NETs by neutrophils stimulated with these amastigotes requires the participation of elastase and peptidyl arginine deaminase and the involvement of PI3K, ROS, and calcium. Moreover, amastigotes are not susceptible to NET-mediated killing. Altogether, these findings improve our comprehension of the signaling pathways implicated in the interaction between amastigotes and human neutrophils.
Accelerating truncated singular-value decomposition: a fast and provable method for robust principal component analysis

Principal component analysis (PCA) is one of the most popular statistical procedures for dimension reduction. A modification of PCA, called robust principal component analysis (RPCA), has been studied to overcome the well-known shortness of PCA: sensitivity to outliers and corrupted data points. Earlier works have proved RPCA can be exactly recovered via semidefinite programming. Recently, researchers have provided some provable non-convex solvers for RPCA, based on projected gradient descent or alternating projections, in full or partial observed settings. Yet, we find the computational complexity of the recent RPCA algorithms can be improved further. We study RPCA in the fully observed setting, which is about separating a low rank matrix L and a sparse matrix S from their given sum D = L + S. In this thesis, a new non-convex algorithm, dubbed accelerated alternating projections, is introduced for solving RPCA rapidly. The proposed new algorithm significantly improves the computational efficiency of the existing alternating projections based algorithm proposed in [1] when updating the estimate of low rank factor. The acceleration is achieved by first projecting a matrix onto some low dimensional subspace before obtaining a new estimate of the low rank matrix via truncated singular-value decomposition. Essentially, truncated singular-value decomposition (a.k.a. the best low rank approximation) is replaced by a high-efficiency sub-optimal low rank approximation, while the convergence is retained. Exact recovery guarantee has been established, which shows linear convergence
Non-Asymptotic and Asymptotic Fundamental Limits of Guessing Subject to Distortion

This paper considers the problem of guessing random variables subject to distortion. We investigate both non-asymptotic and asymptotic fundamental limits of the minimum $t$-th moment of the number of guesses. These fundamental limits are characterized by the quantity related to the R\'enyi entropy. To derive the non-asymptotic bounds, we use our techniques developed in lossy compression. Moreover, using the results obtained in the non-asymptotic setting, we derive the asymptotic result and show that it coincides with the previous result by Arikan and Merhav.
Image restoration for large-motion blurred lunar remote sensing image

In the field of deep space science detection and high resolution earth observation, a relatively high motion velocity is often generated between the optical camera and the imaging target. Images obtained during the exposure time can produce image motion blur, which becomes one of the main obstacles to acquire high resolution image near the target. As an extended task of the third phase of China’s lunar exploration program, flight imaging of the planned sampling area of Chang’e-5 was carried out. A dual resolution camera with a wide field of view (FOV) camera and a narrow FOV camera was used for imaging mission. High flying speed causes the generation of large motion blurred images captured by the narrow FOV camera and the motion blur can be up to around 30 pixels. To deal with this problem, we analyzed the image features of the blurred images captured by the narrow FOV camera, and proposed a corresponding method that can estimate image motion value from the blurred lunar image based on small craters detection scheme and then adopted the regularization method to restore the image. The algorithm is applied in the batch processing of the real blurred lunar images and has achieved a significant restored effect.
Pacific Northwest conifer forest stand carrying capacity under future climate scenarios

Maximum stand density index (SDIMAX) represents the carrying capacity of a forest stand based on the relationship between the number of trees and their size. Plot‐level inventory data provided through a collaborative network of federal, state, and private forest management groups were utilized to develop SDIMAX models for important Pacific Northwest conifers of western Washington and Oregon, USA. The influence of site‐specific climatic and environmental variables was explored within an ensemble learning model. Future climate projections based on global circulation models under different representative CO2 concentration pathways (RCP 4.5 and RCP 8.5) and timeframes (2050s and 2080s) were utilized in a space‐for‐time substitution to understand potential shifts in modeled SDIMAX. A majority of the region showed decreases in carrying capacity under future climate conditions. Modeled mean SDIMAX decreased 5.4% and 11.4% for Douglas‐fir (Pseudotsuga menziesii (Mirb.) Franco) dominated forests and decreased 6.6% and 8.9% for western hemlock (Tsuga heterophylla (Raf.) Sarg. ) and Pacific silver fir (Abies amabilis), dominated forests under the RCP 4.5 in the 2050s and RCP 8.5 in the 2080s, respectively. Projected future conditions often fall outside the range of any contemporary climate profile, resulting in what may be referred to as extramural conditions. Within the study region, 45% and 46% of climate variables included in the final model were extramural for the Douglas‐fir and hemlock models, respectively, under RCP 8.5 in the 2080s. Although extrapolating beyond the range of input data is not appropriate and many unknowns remain regarding future climate projections, these results allow for general interpretations of the direction and magnitude of potential shifts in forest carrying capacity.
Photonic microwave true time delays for phased array antennas using a 49 GHz FSR integrated optical micro-comb source [Invited]

We demonstrate significantly improved performance of a microwave true time delay line based on an integrated optical frequency comb source. The broadband micro-comb (over 100 nm wide) features a record low free spectral range (FSR) of 49 GHz, resulting in an unprecedented record high channel number (81 over the C band)—the highest number of channels for an integrated comb source used for microwave signal processing. We theoretically analyze the performance of a phased array antenna and show that this large channel count results in a high angular resolution and wide beam-steering tunable range. This demonstrates the feasibility of our approach as a competitive solution toward implementing integrated photonic true time delays in radar and communications systems.
A Reconfigurable Antenna With One Slit and a Small Clearance for Nona-Band Metal-Bezel Mobile Phones

In this article, a reconfigurable antenna with one slit and a small ground clearance is proposed for nona-band metal-bezel mobile phones. The proposed antenna consists of a low-frequency band (LB) antenna and a middle- and high-frequency band and new radio (MHB&NR) antenna. The LB antenna is a monopole antenna with a lumped-element matching circuit and a switching circuit. The MHB&NR antenna consist of a monopole antenna with a lumped-element matching circuit, a parasitic branch, and a parasitic slot. The reconfigurable method, lumped-element matching method, multiple branches method, and multiple modes method are applied to cover nine bands with a small clearance of 0.5 mm. The effect of the switch on the antenna efficiency and its efficiency improvement is analyzed in detail. The working modes with its impedance matching are analyzed based on the S-parameters and the current distributions. A capacitor is applied to share the resonant branch of the LB antenna and the MHB&NR antenna with a single slit. A prototype shows that the measured −6-dB impedance bandwidths are 284 MHz (0.695–0.979 GHz), 1070 MHz (1.71–2.78 GHz), and 470 MHz (3.28–3.75 GHz), which can cover the 0.704–0.96 GHz (LB: LTE700, GSM850, and GSM900), 1.71–2.69 GHz (MHB: UMTS, GSM1800, GSM1900, LTE2300, and LTE2500), and 3.4–3.6 GHz (N78) bands. The measured efficiencies in the LB, MHB, and N78 bands are 33%–55%, 46%–62%, and 43%–53%, respectively. The proposed nona-band antenna with one slit and a small clearance of 0.5 mm is a promising candidate for modern metal-bezel mobile phones.
Automated Glaucoma Screening and Diagnosis Based on Retinal Fundus Images Using Deep Learning Approaches: A Comprehensive Review

Glaucoma is a chronic eye disease that may lead to permanent vision loss if it is not diagnosed and treated at an early stage. The disease originates from an irregular behavior in the drainage flow of the eye that eventually leads to an increase in intraocular pressure, which in the severe stage of the disease deteriorates the optic nerve head and leads to vision loss. Medical follow-ups to observe the retinal area are needed periodically by ophthalmologists, who require an extensive degree of skill and experience to interpret the results appropriately. To improve on this issue, algorithms based on deep learning techniques have been designed to screen and diagnose glaucoma based on retinal fundus image input and to analyze images of the optic nerve and retinal structures. Therefore, the objective of this paper is to provide a systematic analysis of 52 state-of-the-art relevant studies on the screening and diagnosis of glaucoma, which include a particular dataset used in the development of the algorithms, performance metrics, and modalities employed in each article. Furthermore, this review analyzes and evaluates the used methods and compares their strengths and weaknesses in an organized manner. It also explored a wide range of diagnostic procedures, such as image pre-processing, localization, classification, and segmentation. In conclusion, automated glaucoma diagnosis has shown considerable promise when deep learning algorithms are applied. Such algorithms could increase the accuracy and efficiency of glaucoma diagnosis in a better and faster manner.
Evaluation of Some Sugar Beet Genotypes Under Drought Stress Based on Selection Indices

This study was conducted to determine drought tolerant indices of some sugar beet genotypes under water stress and non-stress conditions. Nine sugar beet (Beta Vulgaris L.) genotypes were tested in a Split-plot experiment based on a randomized complete block design in three replications under three levels of water stress 100%, 75% and 50% from plant requirements at the experimental farm Faculty of Agriculture, Suez Canal University, Ismailia, Egypt during 2015/ 2016 and 2016 / 2017 seasons. Twelve drought tolerance indices were used in this study, stress sensitivity index (SSI), stress tolerance (TOL), mean productivity (MP), geometric mean (GMP), harmonic mean (HM),yield stability index (YSI), yield index (YI), stress tolerance index (STI), sensitivity drought index (SDI), relative drought index (RDI), drought response index (DI) and stress susceptibility percentage index (SSPI). GMP, MP and STI were more informative towards classification of better or superior genotypes with respect to tolerant and sensitive groups. The results showed that the genotypes with high STI, GMP and MP values were suitable for cultivation under drought stress and non-stress environments. Both Yp and Ys of root yield in the control-50% analysis had significantly positive correlated (P value<0.05) with MP, GMP, YI, HM and DI, This indicates that these indices were more effective in identifying high yielding genotypes under drought stress as well as non-stress conditions.Principal components analysis showed that the first two components in the control-50% analysis, genotype Bts 1237 and Temar were identified as the most stable high yielding genotypes in both environments
The LHCb VeLo for Phase 1 upgrade

Large Hadron Collider beauty (LHCb) is a dedicated experiment for studying $b$ and $c$ hadrons at the Large Hadron Collider (LHC). LHCb uses a silicon-strip detector, the Vertex Locator (VELO), for high precision tracking of collisions from the LHC. During Long Shutdown 2 (LS2) of the LHC, the LHCb collaboration will upgrade the detector, switching from the current VELO, capable of a 1$~$MHz readout, to a hybrid pixel detector capable of reading out at the full bunch crossing rate of the LHC. Substantial progress has been made in the development of the new detector. The status of the silicon sensors, custom designed VeloPix ASIC and electronic system will be discussed in detail. The current status of the cooling system and RF foil will also be presented.
Establishment of an in vitro method for micropropagation of ironwort, (Sideritis raeseri Boiss. & Heldr.)

Ironwort / Mountain Tea (Sideritis raeseri Boiss & Heldr.) is an endangered (EN) plant species in Albania. This study aimed to develop a rapid clonal propagation protocol using in vitro methodologies. The ironwort seeds were pre-treated with three concentrations of GA3 (250, 500, and 1000 mg l-1). During the inoculation stage, two types of culture media, Murashige & Skoog (MS) and Woody Plant Medium (WPM), were tested, and the effects of both GA3 concentration and culture media used were evaluated. For the subculture stage, three cytokinins (6-benzylaminopurine / BAP, kinetin, zeatin) at four concentrations (0.5; 1.0; 1.5; 2.0 mg l-1), were compared for the RGR index, while for the rooting stage, two different auxins (1-naphthaleneacetic acid / NAA and indole-3-butyric acid / IBA) at four concentrations (0.5; 1.0; 1.5; 2.0 mg l-1) were tested. GA3 at 500 mg l-1 and MS medium resulted as more effective. The highest value of the RGR index during the subculture stage was obtained in the MS nutrient medium supplemented with BAP at 1.5 mg l-1. For rhizogenesis response, IBA was more effective for roots and length number. Based on these results, in vitro methodologies can be a promising tool for the mass production of this endangered plant species and with possible applications for enhancing the production of valuable nutraceuticals.