Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaboration for conservation: Assessing countrywide carnivore occupancy dynamics from sparse data

Assessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide.
What health preparations do international students make for their academic sojourn?

Abstract The exponential growth in international student mobility since the 1990s brings issues of travel health preparedness in overseas students and the impact of studying in a foreign country on their health to the fore. The direction of travel for much ‘education first’ educational tourism is from less- to more-economically developed countries, yet the existing literature tends to focus on the health-related expectations, precautions and behaviours of students travelling in the other direction. We explore the health implications of the international sojourn for students in UK higher education from various developing countries, and attendant risks such as the translocation of disease (a concern elevated by the COVID-19 pandemic). Drawing on, fusing and extending ideas from research on education and health mobilities, we examine students’ experiences beyond the much-discussed first few weeks after arrival which is typically understood in terms of culture shock. Using narrative research and interviews with a purposive sample of students from ten countries/territories to establish their travel health preparations and perceptions, we reveal that they made extensive use of non-medical sources of advice including family and friends, the internet and study abroad agents. When they did become ill it was an isolating, distressing and frustrating experience due to delays in obtaining a doctor’s appointment and the lack of social support away from home. Of some concern, these students perceived a low risk to traveling to and studying in the UK, and had given little thought to the possibility of inadvertently transmitting disease across borders. These findings will inform our understanding of international students’ health, and have the potential to shape related policy and practice in origin and destination countries alike.
Improvement in the Quality of Pomegranate Leather

New different products from pomegranate and roselle calyces either alone or blends of them with different ratio were prepared and dehydrated in leather form. The effect of processing on physiochemical, phytochemical composition and quality were evaluated. The results declared that roselle calyces extract includes the highest values of phytochemical compounds such as anthocyanin, total phenol, total flavonoid content, total tannic and acidity in comparison with pomegranate juice and pomegranate concentrate. These values were 321.50, 2007.72, 1336.33, 243.10 mg/100 g and 11.42% as citric acid respectively. Pomegranate and pomegranate roselle leather were also evaluated for their physiochemical composition and phytochemicals. The results showed that the replacement of pomegranate concentrate with roselle calyces extract for produced pomegranate leather recorded improvement in quality attributes (anthocyanin, total phenol, total flavonoid and total tannic) of the pomegranate leather by addition of roselle extract. The present study demonstrated that adding roselle extract to the processed pomegranate leather will improve the loss in the quality attribute.
Joint Estimation of SOC of Lithium Battery Based on Dual Kalman Filter

In order to improve the estimation accuracy of the state of charge (SOC) of electric vehicle power batteries, a dual Kalman filter method based on the online identification of model parameters is proposed to estimate the state of charge in lithium-ion batteries. Here, we build the first-order equivalent circuit model of lithium-ion batteries and derive its online identification model based on extended Kalman (EKF). Considering that the noise value in the EKF algorithm is difficult to select through experiments to achieve the best filtering effect, this paper combines an improved particle swarm optimization algorithm (IPSO) with EKF to realize online model parameter identification. At the same time, the EKF filtering method derived from the state space equation is also used in SOC estimation. It constitutes a dual Kalman filter method for online identification of model parameters and SOC estimation. The experimental and simulation results show that the IPSO–EKF algorithm can adaptively adjust the noise value according to the complex operating conditions of electric vehicles. Compared with the EKF algorithm, our algorithm can identify battery model parameters more accurately. The dual Kalman filter method composed of the IPSO–EKF algorithm and EKF applied to SOC estimation achieved a higher accuracy in the final algorithm verification.
Fast and Exact Leave-One-Out Analysis of Large-Margin Classifiers

Abstract Motivated by the Golub–Heath–Wahba formula for ridge regression, we first present a new leave-one-out lemma for the kernel support vector machines (SVM) and related large-margin classifiers. We then use the lemma to design a novel and efficient algorithm, named “magicsvm,” for training the kernel SVM and related large-margin classifiers and computing the exact leave-one-out cross-validation error. By “magicsvm,” the computational cost of leave-one-out analysis is of the same order of fitting a single SVM on the training data. We show that “magicsvm” is much faster than the state-of-the-art SVM solvers based on extensive simulations and benchmark examples. The same idea is also used to boost the computation speed of the V-fold cross-validation of the kernel classifiers.
An improved primal-dual approximation algorithm for the k-means problem with penalties

Abstract In the k-means problem with penalties, we are given a data set $${\cal D} \subseteq \mathbb{R}^\ell $$ of n points where each point $$j \in {\cal D}$$ is associated with a penalty cost pj and an integer k. The goal is to choose a set $${\rm{C}}S \subseteq {{\cal R}^\ell }$$ with |CS| ≤ k and a penalized subset $${{\cal D}_p} \subseteq {\cal D}$$ to minimize the sum of the total squared distance from the points in D / Dp to CS and the total penalty cost of points in Dp, namely $$\sum\nolimits_{j \in {\cal D}\backslash {{\cal D}_p}} {d^2}(j,{\rm{C}}S) + \sum\nolimits_{j \in {{\cal D}_p}} {p_j}$$. We employ the primal-dual technique to give a pseudo-polynomial time algorithm with an approximation ratio of (6.357+ε) for the k-means problem with penalties, improving the previous best approximation ratio 19.849+∊ for this problem given by Feng et al. in Proceedings of FAW (2019).
Policy and Business Cycle Shocks: A Structural Factor Model Representation of the US Economy

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and five. Focusing on the four-shock specification, we identify, using sign restrictions, two policy shocks, monetary and fiscal, and two non-policy shocks, demand and supply. We obtain the following results. (ii) Both supply and demand shocks are important sources of fluctuations; supply prevails for GDP, while demand prevails for employment and inflation. (ii) Monetary and fiscal policy shocks have sizable effects on output and prices, with no evidence of crowding-out of private aggregate demand components; both monetary and fiscal authorities implement important systematic countercyclical policies reacting to demand shocks. (iii) Negative demand shocks have a large long-run positive effect on productivity, consistently with the Schumpeterian “cleansing” view of recessions.
A Review of Affective Computing Research Based on Function-Component-Representation Framework

Affective computing (AC), a field that bridges the gap between human affect and computational technology, has witnessed remarkable technical advancement. However, theoretical underpinnings of affective computing are rarely discussed and reviewed. This paper provides a thorough conceptual analysis of the literature to understand theoretical questions essential to affective computing and current answers. Inspired by emotion theories, we proposed the function-component-representation (FCR) framework to organize different conceptions of affect along three dimensions that each address an important question: function of affect (why compute affect), component of affect (how to compute affect), and representation of affect (what affect to compute). We coded each paper by its underlying conception of affect and found preferences towards affect detection, behavioral component, and categorical representation. We also observed coupling of certain conceptions. For example, papers using the behavioral component tend to adopt the categorical representation, whereas papers using the physiological component tend to adopt the dimensional representation. The FCR framework is not only the first attempt to organize different theoretical perspectives in a systematic and quantitative way, but also a blueprint to help conceptualize an AC project and pinpoint new possibilities. Future work may explore how the identified frequencies of FCR framework combinations may be applied in practice.
Three-Dimensional Stress Intensity Factor Correction Method Based on Thickness Size Effect

This paper presents the fatigue crack growth test of 7N01 aluminum alloy specimens with different thicknesses under three-point bending. Moreover, the effect of specimen thickness on the fatigue crack growth life was analyzed. The influence mechanism of the thickness size effect on the stress intensity factor was explored. A three-dimensional stress intensity factor calculation model based on the thickness size effect was proposed by combining the finite element method and the interaction integral method. The results show that the fatigue crack growth life of 7N01 aluminum alloy decreases with the increase of specimen thickness. The numerical solutions of the stress intensity factor (the proposed model) are higher than the analytical solutions (the traditional formula) in the steady-state crack growth stage. The difference between numerical solutions and analytical solutions increases with the increase of crack growth length and specimen thickness. Compared with the analytical solutions, the relationship curve between crack length “a” and cycle number “N” from the numerical solutions is closer to the experimental data. This result proves that the proposed calculation model can correct the stress intensity factor with the thickness size effect.
Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

The magnetic field created by technical devices is a source of information. This information could be used in contactless diagnostics and predictive maintenance or for resolving problems along with standard NDT (nondestructive testing) methods, especially if we consider large, slow-speed devices, such as electromotors, transmissions, or generators. Identification of causalities of device failure processes with near magnetic field is one of the suitable NDT methods improving sustainability of systems. The measurements presented in the article were performed with the VEMA 04 fluxgate vector magnetometer with the DC-250 Hz bandwidth and 2 nT sensitivity. Postprocessing of the results was performed in the means of standard methods of discrete Fourier Transform, spectrogram creation and Wavelet Transform. The article presents data gathered during the measurement of a pair of extraction fans with power of 140 kW each and maximum revolutions up to 740 rev/min controlled by frequency converters and a single semi-Kaplan water power plant with 400 kW peak power at 1005 rev/min maximum generator speed. The measurements were performed before and after repairs of one of the ventilators in the ventilation system at 60% and 100% of maximal output power. The rotating magnetic fields of the fan electromotor stator, fan rotor revolutions, rotor slip frequency and ball-bearing frequencies were identified in frequency spectrums in the distance of 700 mm from fan electromotor axis in both cases. During the measurements on the semi-Kaplan turbine, the changes in states of mechanical and electrical components of the machine were monitored in the magnetic fields with increase of the power in the range of 0–95%, before and after phasing to the electrical grid. Standard processing methods, Discrete Fourier Transform, spectrograms and Discrete Wavelet Transform were used. In the spectrograms of the measured magnetic fields, the 1st–4th harmonics of the turbine shaft, generator shaft and also their side frequencies were identified. Significant changes of magnetic fields in time were identified in the area of 60–95% power. With the help of the Wavelet, transform intervals were identified where it is desirable to operate the turbine. The analyses of magnetic fields measurements performed on the power plant were compared with vibro-diagnostic principles.
A double hollow rectangular‐shaped patch and with the slotted ground plane monopole wideband antenna for microwave head imaging applications

This paper introduces a lightweight wideband planar antenna with an antenna array configuration for microwave head imaging. The designed antenna is composed of a double hollow rectangular‐shaped patch and with the slotted ground. Its measurements are small: 0. 28λ × 0. 24λ × 0. 006λ, where λ is the lowest operating frequency's wavelength. The design process has been completed using CST and then fine‐tune the parameters of the architecture structure to accomplish the ideal bandwidth. The antenna is manufactured and measured in order to test antenna properties. The prototype was being used for brain screening than with the Hugo‐head model. With adequate impedance matching, the antenna meets an operational bandwidth of 1.82 GHz (1.22–3.04 GHz) with an overall peak gain of 5 dBi with a stable radiation property. Fidelity factors both for face‐to‐face and side by side alignment are 92.7% and 83.75%, respectively, indicating that the antenna had a little signal interruption. To determine the backscattered signals of the antenna with Hugo‐head phantom, a nine‐antenna array‐based setup is assumed, with one antenna serving as a transmitter and the remaining eight receiving the dispersed signals.
Caesalpinia sappan L. Ethanolic Extract Decrease Intracellular ROS Level and Senescence of 4T1 Breast Cancer Cells

Highly and uncontrolled cell proliferation on cancer cells may boost ROS level intracellular accumulation up significantly. Sappan heartwood (Caesalpinia sappan L.) have been known to have cytotoxicity effect toward several cancer cells. This research was conducted to develop Caesalpinia sappan L. heartwood ethanolic extract (CSE) as chemopreventive agent which can be used as cancer therapy, looked from antioxidant and anti-senescence activity toward 4T1 breast cancer cell. CSE was obtained through maceration using ethanol 70% as solvent. Cytotoxicity activity of CSE was done by using MTT assay with IC50 as parameter. This IC50 was used as basic to the next assay, ROS assay by using DCFDA staining flowcytometry to look ROS level intracellular of CSE toward 4T1 cell and senescence assay by using senescence associated β-galactosidase (SA β-gal) assay with % cell senescence as their parameter. CSE toxic to 4T1 cell that proved from IC50 value of 25 µg/mL. Single treatment of CSE on concentration 12,5; 25; and 37.5 µg/mL able to suppress ROS level intracellular. If compared with untreated cell, single treatment of CSE on concentration 6 and 12 µg/mL showed % cell senescence not significantly different. Based on this result, CSE is cytotoxic, has antioxidant and antisenescence activity, so it has great potential to developed as chemoprevention agent on cancer therapy.Keywords : Caesalpinia sappan L. , 4T1 breast cancer line, Reactive Oxygen Species (ROS), anti-senescence
Electromechanical Performance Analysis of the Hybrid Piezoelectric-Electromagnetic Energy Harvester under Rotary Magnetic Plucking Excitation

This paper presents an analysis of the hybrid piezoelectric-electromagnetic energy harvester (P-EMEH) driven by contactless rotary magnetic plucking. A lumped-parameter model of the hybrid P-EMEH is developed, and the model parameters are determined from the finite element analysis (FEA) method. A parametric study is conducted to investigate the effects of driving force parameters, load resistance, and electromechanical coupling strengths (EMCSs) on the maximal displacements and velocities, average power inputs and outputs, and energy efficiencies of the system for indicating the performance of the hybrid P-EMEH. The results show that the hybrid P-EMEH can obtain the improved power inputs by reducing the gyration radii of the rotary magnet and shortening the gaps between the two magnets. The structural vibrations can be strongly suppressed owing to the optimal piezoelectric power outputs, which can lead to the occurrence of valleys’ power of the electromagnetic element. At weak coupling, the hybrid P-EMEH can achieve higher power outputs than the single piezoelectric energy harvester (PEH) and the single electromagnetic energy harvester (EMEH). At strong coupling, the use of the PEH is more advantageous for energy harvesting due to wider power bandwidths at high dimensionless frequencies when compared with the hybrid P-EMEH. This work provides a fundamental understanding on the effect of load resistance and EMCSs on the dynamic and electrical characteristics of the magnetically plucked hybrid P-EMEH.
Auditory Time Thresholds for Subsecond but not Suprasecond Stimuli are Impaired in ADHD

Background. The literature on time perception in individuals with ADHD is extensive but inconsistent, probably reflecting the use of different tasks and performances indexes. Methods. A sample of 40 children/adolescents (20 with ADHD, 20 neurotypical) was engaged in two identical psychophysical tasks measuring auditory time thresholds for both subsecond (0.5-1s) and suprasecond (0.75-3s) stimuli. Results. Results showed a severe impairment in ADHD for subsecond thresholds (Log10BF=1.9). The deficit remained strong even when non-verbal IQ was regressed out and correlation with age suggests a developmental delay. Suprasecond thresholds were indistinguishable between the two groups (Log10BF = –0.5) and not correlated with subsecond thresholds. Conclusions. Since much evidence suggest that perception of subsecond stimuli does not load on cognitive control and working memory, the current results are consistent with a pure timing deficit in individuals with ADHD.
Sexological Worldview Development Explained by the Developmental Model of Intercultural Sensitivity

Abstract Sexological worldview is the lens through which someone sees and makes meaning of the sexual world around them. The Developmental Model of Intercultural Sensitivity (DMIS) may be a useful tool in operationalizing cultural humility and responsiveness to sexological differences. This research explored whether the DMIS explains the stages of someone’s sexological worldview development across a continuum of dualist to relativist perspectives and ways of interacting with others who are similar or different. The lead author interviewed 30 sexuality professionals and students in the US and found that the participants’ sexological worldview development could be explained using the DMIS framework. We discuss the use of the DMIS for the future design of Sexuality Attitudes Reassessment (SAR) programs, a type of training required in the credentialing of sexologists, and the measurement of SAR training outcomes as they pertain to cultural humility and responsiveness. Future research should focus on the development of an empirical instrument to measure sexological worldview development and SAR educators should create new, or align existing, training activities to match their SAR participants’ worldview development.
Fundamental Numerical Analysis of a Porous Micro-Combustor Filled with Alumina Spheres: Pore-Scale vs. Volume-Averaged Models

Inserting porous media into the micro-scale combustor space could enhance heat recirculation from the flame zone, and could thus extend the flammability limits and improve flame stability. In the context of porous micro-combustors, the pore size is comparable to the combustor characteristic length. It is insufficient to treat the porous medium as a continuum with the volume-averaged model (VAM). Therefore, a pore-scale model (PSM) is developed to consider the detailed structure of the porous media to better understand the coupling among the gas mixture, the porous media and the combustor wall. The results are systematically compared to investigate the difference in combustion characteristics and flame stability limits. A quantified study is undertaken to examine heat recirculation, including preheating and heat loss, in the porous micro-combustor using the VAM and PSM, which are beneficial for understanding the modeled differences in temperature distribution. The numerical results indicate that PSM predicts a scattered flame zone in the pore areas and gives a larger flame stability range, a lower flame temperature and peak solid matrix temperature, a higher peak wall temperature and a larger Rp-hl than a VAM counterpart. A parametric study is subsequently carried out to examine the effects of solid matrix thermal conductivity (ks) on the PSM and VAM, and then the results are analyzed briefly. It is found that for the specific configurations of porous micro-combustor considered in the present study, the PSM porous micro-combustor is more suitable for simplifying to a VAM with a larger Φ and a smaller ks, and the methods can be applied to other configurations of porous micro-combustors.
An automatic procedure for generating burn severity maps from the satellite images-derived spectral indices

ABSTRACT Fire, especially wildfire, which can be considered as one of the main threats to vegetation cover and animals' life, has attracted lots of attention from environmental researchers. To better manage the fire crisis and take the necessary measures to compensate for its damages, it is essential to have detailed information about the burn severity levels. Accordingly, satellite images and their spectral indices have been widely considered in the literature as powerful tools in producing burn severity information. Despite the efficiency of the previously proposed methods, the necessity of ground reference data for their thresholding step faces them with serious challenges. To address this problem, in this study, an automatic procedure based on the change-point analysis is presented for thresholding differenced normalized burn ratio (dNBR) and its another version, dNBR2. In this procedure, a mean-shift based change-point analysis is performed on the dNBR and dNBR2 images for classifying them into burn severity levels. Experiments, conducted on some parts of Alaska and California in the United States, illustrated the high efficiency of the proposed method. Moreover, as an applied experiment, the severity of the fires, occurred in 2020 in the Khaeiz protected area in Iran, was estimated and compared with local reports.