Miracle-dz/UniFAR-FTUs huggingface dataset:
Outbreak of Moroccan Locust in Sardinia (Italy): A Remote Sensing Perspective

The Moroccan locust has been considered one of the most dangerous agricultural pests in the Mediterranean region. The economic importance of its outbreaks diminished during the second half of the 20th century due to a high degree of agricultural industrialization and other human-caused transformations of its habitat. Nevertheless, in Sardinia (Italy) from 2019 on, a growing invasion of this locust species is ongoing, being the worst in over three decades. Locust swarms destroyed crops and pasture lands of approximately 60,000 ha in 2022. Drought, in combination with increasing uncultivated land, contributed to forming the perfect conditions for a Moroccan locust population upsurge. The specific aim of this paper is the quantification of land cover land use (LCLU) influence with regard to the recent locust outbreak in Sardinia using remote sensing data. In particular, the role of untilled, fallow, or abandoned land in the locust population upsurge is the focus of this case study. To address this objective, LCLU was derived from Sentinel-2A/B Multispectral Instrument (MSI) data between 2017 and 2021 using time-series composites and a random forest (RF) classification model. Coordinates of infested locations, altitude, and locust development stages were collected during field observation campaigns between March and July 2022 and used in this study to assess actual and previous land cover situation of these locations. Findings show that 43% of detected locust locations were found on untilled, fallow, or uncultivated land and another 23% within a radius of 100 m to such areas. Furthermore, oviposition and breeding sites are mostly found in sparse vegetation (97%). This study demonstrates that up-to-date remote sensing data and target-oriented analyses can provide valuable information to contribute to early warning systems and decision support and thus to minimize the risk concerning this agricultural pest. This is of particular interest for all agricultural pests that are strictly related to changing human activities within transformed habitats.
Measurement of the thermal diffusivity of thin films with bolometers and with pyroelectric temperature sensors

Abstract Several methods for the measurement of the thermal diffusivity of thin films are developed. Common to all methods is the generation of a thermal wave via the absorption of intensity-modulated light on one surface of the film; resistive thin film bolometers and pyroelectric sensors are used for the temperature recording. For free-bearing films the thermal diffusivity is determined from front and rear side temperature spectra as a function of the modulation frequency, measured with resistive bolometers. If a pyroelectric material is mounted on a heat sink, the thermal diffusivity is obtained from the spectrum of the pyroelectric current. For very thin films pyroelectric substrates are recommended as temperature sensors. A novel method is also proposed, in which the thermal diffusivity is obtained without the influence of any other material properties and any sensor characteristics. Experimental results are presented with a 25 μm thick PVDF film and with a 1.25 μm thick Polyglutamate Langmuir-Blodge.
Multiview Registration of Surfaces Minimizing Error Propagation

The purpose of this paper is to describe a processing system on multi-view registration minimizing error propagation for 3D geometry modelling.In the geometry modelling stage, the algorithm based on graph and metaview method is used . In order to enhance its robustness, a method for judging bad pairwise registration is proposed based on the computation of two views’ overlapping percentage. In order to enrich its completeness, combined the graph analysis with the metaview method is used to deal with the measurement data for local details. Results show that the processing system can provide 3D geometry model with low distortion successfully.
Reachability-Based Packet Scheduler of Multipath QUIC for Heterogeneous Mobile Networks

In recent years, we need more bandwidth to enjoy entertainment contents such as video streaming, music and online gaming. To gain enough bandwidth, technologies that combine bandwidth by using multiple interfaces at same time are desired. Multipath transport protocols which combine multiple paths for packet delivery at the transport layer are a promising technology. Such protocols have a mechanism, called “packet scheduler”, to select the interface to send a packet. However, existing studies of the packet scheduler have not explicitly considered the compatibility of mobility with bonding of bandwidth. Therefore, when smartphone users move out of coverage of communication networks such as wireless Local Area Network (LAN) and Long Term Evolution (LTE) by vehicle, packet loss occurs, leading to a decrease of throughput. In this study, we propose a packet scheduler that selects an appropriate communication path so that packets can reach the peer before it moves out of the coverage. Based on routes of a vehicle and the position and communication range of the access point, the time at which a communication path will be lost is predicted. In addition, we employ MPQUIC (Multipath QUIC (Quick UDP Internet Connections)), which is a multipath transport protocol proposed as the extension of QUIC protocol, to reduce the ACK packet loss in multipath communication, and to reduce the time until the starts of retransmission. We evaluated the number of packet losses, the throughput and the time until starts of retransmission using a simulator and show the superiority of proposed method.
Detecting Brain Diseases using Hyper Integral Segmentation Approach (HISA) and Reinforcement Learning

—Medical Images are most widely done by the various image processing approaches. Image processing is used to analyze the various abnormal tissues based on given input images. Deep learning (DL) is one of the fast-growing field in the computer science and specifically in medical imaging analysis. Tumor is a mass tissue that contains abnormal cells. Normal tumor tissues may not grow in other places but if it contains the cancerous (malignant) cells these tissues may grow rapidly. It is very important to know the cause of brain tumors in humans and these should be detected in the early stages. Magnetic Resonance Imaging (MRI) images are most widely used to detect the tumors in the brain and these are also used to detect the tumors all over the body. Tumors are of various types such as noncancerous (benign) and cancerous (malignant). Sometimes tumors may convert into cancer cells based on the stage of the tumor. In this paper, a hyper integral segmentation approach (HISA) is introduced to detect cancerous tumors and non-cancerous tumors. Detecting cancerous cells in the tumors may reduce the life threat to the affected persons. The agent based reinforcement classification (ABRC) is used to classify the Alzheimer's disease (AD) and cancerous and non-cancerous cells based on the abnormalities present in the MRI images. Two publically available datasets are selected such as MRI images and AD-affected MRI images. Performance is analyzed by showing the improved metrics such as accuracy, f1-score, sensitivity, dice similarity score, and specificity.
Investigating the Effect of Animal Avatars on Users' Self-disclosure During Interaction in VR space

In social VR, users can communicate with others by expressing their own appearance by customizing an avatar. Several studies have shown that the appearance of the avatars that users use in social VR affects their self-disclosure. In this study, motivated by the findings of previous studies that interaction with animals has positive effects on humans, we use animal avatars in a VR space. To investigate the effect of the animal avatars’ appearance on user’s self-disclosure and subjective responses, we propose a one-to-one communication system in which the user and interlocutor use animal avatars. The system converts the user’s non-verbal information acquired by the sensors mounted on the head-mounted display (HMD) into the movements of the animal avatar and transmits them to the interlocutor. We also describe the design of an experiment using this system.
Deeply Learned Invariant Features for Component-based Facial Recognition

— Face recognition underage variation is a challenging problem. It is a difficult task because ageing is an intrinsic variation, not like pose and illumination, which can be controlled. We propose an approach to extract invariant features to improve facial recognition using facial components. Can facial recognition over age progression be improved by resizing independently each individual facial component? The individual facial components: eyes, mouth, and nose were extracted using the Viola-Jones algorithm. Then we utilize the eyes region rectangle with upper coordinates to detect the forehead and lower coordinates with the nose rectangle to detect the cheeks. The proposed work uses Convolutional Neural Network with an ideal input image size for each facial component according to many experiments. We sum up component scores by applying weighted fusion for a final decision. The experiments prove that the nose component provides the highest score contribution among other ones, and the cheeks are the lowest. The experiments were conducted on two different facial databases-MORPH, and FG-NET databases. The proposed work achieves a state-of-the-art accuracy that reaches 100% on the FG-NET dataset and the results obtained on the MORPH dataset outperform the accuracy results of the related works in the literature.
Role of global ﬁnancial crisis in causing dynamic connectedness of Asian equity markets

Dynamic connectedness of equity markets especially when shock happened has been a concern for policymakers and market participants. In this paper, we examine the connectedness of Asian equity markets within the region when the US subprime crisis or better-known as the global financial crisis occurred in 2008.This paper wants to know whether there has been a shift in terms of net shock givers and receivers over the time? Subsequently, how has connectedness in equity markets changed over time? Finally, do markets become more connected during crisis period? We employ daily data of US, Japan, South Korea, China, Singapore, Malaysia, Indonesia and Thailand. We find that Singapore, US, Malaysia and South Korea played significant roles in bringing about dynamic connectedness of Asian equity markets. In terms of the global financial crisis, emerging market economies such as Singapore, Malaysia and South Korea seem to be vulnerable to the shock and may have contributed as spillover effect of shock to other Asian equity markets. Whereas economies such as China and Japan became a net receiver of shock.
Validity and Reliability of the Parental Health Literacy Questionnaire for Caregivers of Children Aged 0 to 3 Years in China

Caregivers’ health literacy plays a vital role in the quality of parenting and significantly impacts children’s physical and psychological health. However, the instruments to assess the health literacy of caregivers of children aged 0 to 3 years are lacking. This study aimed to evaluate the reliability and validity of the Chinese Parental Health Literacy Questionnaire (CPHLQ) in China. We conducted a cross-sectional study. Six hundred and thirty-four caregivers of children aged 0 to 3 years were recruited from Shandong, Yunnan, and Shaanxi Provinces, representing the eastern, central, and western regions of China, between November 2020 and January 2021. The reliability was evaluated by internal consistency reliability and split-half reliability. The construct validity was determined by confirmatory factor analysis. Social determinants of parental health literacy were assessed by multivariate linear regression model. Results showed that CPHLQ had satisfactory reliability and acceptable construct validity. Mothers compared to other types of caregivers, higher education levels, and nuclear or extended families compared to other family compositions were significantly associated with higher parental health literacy. The study further demonstrated that CPHLQ is a reliable and valid instrument to measure the health literacy of caregivers of children aged 0 to 3 years in the Chinese population. It can be used as an evaluation tool for intervention research, to inform policy-making and future health education interventions of improving caregivers’ health literacy.
Consistent Semantic Attacks on Optical Flow - Supplementary Material

In this supplementary we provide additional material on consisted targeted attacks. First, we provide the details of the cross category attacks against the vehicle category conducted on KITTI 15’. Then, we analyze the effect of varying α on attack EPE. Following that, we provide our results on both the human category attack on KITTI 15’ and the vehicle category attack on KITTI 12’. The results for the TTC as a function of the Median AA detection score is then presented. Finally, we provide further attack visualizations for the experiments conducted on KITTI 15’
Micromechanics Modeling of Transverse Tensile Strength for Unidirectional CFRP Composite

Transverse tensile strength of unidirectional (UD) composites plays a key role in overall failure of fiber-reinforced composites. To predict this strength by micromechanics, calculation of actual stress in constituent matrix is essentially required. However, traditional micromechanics models can only give the volume-averaged homogenized stress rather than an actual one for a matrix, which in practice will cause large errors. In this paper, considering the effect of stress concentration on a matrix, a novel micromechanics method was proposed to give an accurate calculation of the actual stress in the matrix for UD composite under transverse tension. A stress concentration factor for a matrix in transverse tensile direction is defined, using line-averaged pointwise stress (obtained from concentric cylinder assemblage model) divided by the homogenized quantity (obtained from a bridging model). The actual stress in matrix is then determined using applied external stress multiplied by the factor. Experimental validation on six UD carbon fiber-reinforced polymer (CFRP) specimens indicates that the predicted transverse tensile strength by the proposed method presents a minor deviation with an averaged relative error of 5.45% and thus is reasonable, contrary to the traditional method with an averaged relative error of 207.27%. Furthermore, the morphology of fracture section of the specimens was studied by scanning electron microscopy (SEM). It was observed that different scaled cracks appeared within the matrix, indicating that failure of a UD composite under transverse tension is mainly governed by matrix failure. Based on the proposed approach, the transverse tensile strength of a UD composite can be accurately predicted.
Semi-analytical validation of a dynamic large-eddy simulation procedure for turbulent premixed flames via the G-equation

The performance of a dynamic subgrid model for the turbulent burning speed of a premixed flame is investigated for a series of idealized test cases where the flame front is wrinkled by a multiple-scale shear flow; a rigorous asymptotic subgrid model is also implemented for comparison. Explicit formulae for the flame wrinkled shape and turbulent speed are available to generate a reference database. The role of the subgrid wrinkling models is to achieve the same overall flame shape and propagation speed in a simulation where only the largest scales of the flow are explicitly accounted for. Very good results are obtained when the subgrid burning speed enhancement is estimated using the asymptotic subgrid model. On the other hand, the dynamic model attempts to exploit the scaling observable in the simulation to extrapolate the turbulent burning speed enhancement in the original system. The performance of this strategy is adequate for some regimes but poor for others; the source of the problem is traced back to the existence of a scaling transition that occurs as the flame propagating speed is adjusted during the large-eddy simulation. A modification to the scaling of the enhanced burning is implemented to account for the existence of the two distinct scaling ranges; it improves significantly the predictions of the dynamic model away from the transition, but results in the near-critical range remain predictably very poor compared with the rigorous asymptotic model results. These conclusions based on a priori performance for the reference steady data are confirmed by comparing unsteady large-eddy and direct simulations. Results based on rigorous mathematical tools are possible here because of the separation of length scales in the special class of idealized flow fields used in this study: their relevance to more realistic flows is also discussed.
The Role of Poultry Litter and Its Biochar on Soil Fertility and Jatropha curcas L. Growth on Sandy-Loam Soil

Low agricultural output and a decline in plant-available nutrient content in soil pose significant challenges to developing countries. To test the hypothesis that poultry litter and its biochar improve soil quality, nutrient status, and plant growth, a greenhouse pot experiment with sandy-loam soil was conducted. Selected application rates of poultry litter (0, 15, 30, 60, and 120 g/kg) and its biochar pyrolyzed at 350 °C and 600 °C were used. With the addition of organic amendments, Jatropha plant height, leaf number, and stem diameter improved significantly, as did soil fertility indicators (pH, organic matter content, cation exchange capacity, and plant-available nutrients). When compared to the control, increased application rates ranging from 60 g/kg to 120 g/kg significantly improved soil properties and plant growth. PL (Poultry litter)- and BC350 (Biochar produced at 350 °C)-treated soil outperformed other organic amendments in terms of soil quality, nutrient status, and plant growth. Soil pH, CEC, and OM were found to be positively correlated with available plant nutrients, with PL-treated soils having higher levels of plant available nutrients. Because the properties of the feedstocks complement each other, combined organic amendments improved studied parameters, particularly PLBC600 (Poultry litter mixed with biochar produced at 600 °C) compared to BC600 (Biochar produced at 600 °C). Increased application rates of pure and combined feedstock effectively increased soil fertility and Jatropha growth; however, lower temperature biochar is recommended for use as a soil organic amendment.
Shining light into the Higgs portal with γ γ colliders

High-energy γ γ colliders constitute a potential running mode of future lepton colliders such as the ILC and CLIC. We study the sensitivity of a high-energy γ γ collider to the Higgs portal scenario to a hidden sector above the invisible Higgs decay threshold. We show that such γ γ collisions could allow to probe the existence of dark sectors through the Higgs portal with precision competitive with other planned collider facilities, proﬁting from the unique combination of sizable cross-section with clean ﬁnal state and collider environment. In addition, this search could cover the singlet Higgs portal parameter space yielding a ﬁrst-order electroweak phase transition in the early Universe.
N = ( 2 , 2 ) extended sl ( 3 | 2 ) Chern–Simons Ad S 3 supergravity with new boundaries

We present the ﬁrst example of N = ( 2 , 2 ) formulation for the extended higher-spin AdS 3 supergravity with the most general boundary conditions as an extension of the N = ( 1 , 1 ) work, discovered recently by us (Özer and Filiz in Eur Phys J C 80(11):1072, 2020). Using the method proposed by Grumiller and Riegler, we restrict a consistent class of the most general boundary conditions to extend it. An important consequence of our method is that, for the loosest set of boundary conditions it ensures that their asymptotic symmetry algebras consist of two copies of the sl ( 3 | 2 ) k . Moreover,weimposesomerestrictionsonthegauge ﬁelds for the most general boundary conditions, leading to the supersymmetric extensions of the Brown and Henneaux boundary conditions. Based on these results, we ﬁnally ﬁnd out that the asymptotic symmetry algebras are two copies of the super W 3 algebra for N = ( 2 , 2 ) extended higher-spin supergravity theory in AdS 3 .
An Inversion Theorem-Based Kernel Density Estimator for a Weighted Average and Difference of Weighted Averages with Applications

In this article, we develop a new and novel kernel density estimator for a sum of weighted averages from a single population based on utilizing the well defined kernel density estimator in conjunction with classic inversion theory. This idea is further developed for a kernel density estimator for the difference of weighed averages from two independent populations. The resulting estimator is “bootstrap-like” in terms of its properties with respect to the derivation of approximate confidence intervals via a “plug-in” approach. This new approach is distinct from the bootstrap methodology in that it is analytically and computationally feasible to provide an exact estimate of the distribution function through direct calculation. Thus, our approach eliminates the error due to Monte Carlo resampling that arises within the context of simulation based approaches that are oftentimes necessary in order to derive bootstrap-based confidence intervals for statistics involving weighted averages of i.i. d. random variables. We provide several examples and carry forth a simulation study to show that our kernel density estimator performs better than the standard central limit theorem based approximation in term of coverage probability.
Time Weighted Price

: In the era of high frequency trading and the pervasiveness of irregularly spaced trading, we control for the time element in the Modified Weighted Price Contribution (MWPC) model by Jahanshahloo and Spokeviciute (2018). We empirically show that our new modification controls for reaction time (Speed) of market participants to arrival of new information.
Crystallography using an X-ray free-electron laser

An X-ray free-electron laser (XFEL) produces short pulses (10–50 fs) of intense (mJ μm−2 at 120 Hz) X-rays, with high transverse coherence. Such pulses open novel spectroscopic and scattering methods for static and time-resolved studies of matter, and many are based on X-ray crystallography. With serial femtosecond crystallography, the XFEL allows high-resolution structural determination on sub-micron protein crystals. Although the XFEL pulse is destructive, its short duration ensures that effectively undamaged material is probed. Coherent scattering features provide information on the physical crystal form and may assist in determining the crystallographic phase. By introducing synchronized optical laser pulses, one can perform ‘pump-probe’ measurements of dynamic properties, on the sub-picosecond timescale. These include photo-initiated structural modifications in biomolecules, photo-excited lattice vibrations and photo-driven structural phase transitions. As with synchrotron radiation, the XFEL wavelength can be tuned to atomic resonances, allowing time-resolved resonant-diffraction measurements, which are particularly sensitive to selected order parameters (lattice, charge, spin, and orbital) in magnetic or correlated electron materials. Finally, it is anticipated that the special properties of XFEL pulses will allow entirely new types of X-ray scattering measurements, such as ptychographic crystallography on 2D bio-crystals, correlation-function determination of nanoparticle geometry and nonlinear crystallographic mixing of optical and X-ray pulses.