Miracle-dz/UniFAR-FTUs huggingface dataset:
Hemophagocytic Lymphohistiocytosis Associated with Sarcoidosis: A Case Report and Review of the Literature

Hemophagocytic lymphohistiocytosis (HLH) is a rare and often fatal inflammatory syndrome characterized by histiocyte proliferation and hemophagocytosis. Primary HLH primarily occurs in children and is caused by genetic mutations. Secondary HLH, more often seen in adults, occurs as a result of infections, malignancies or rarely rheumatic diseases. HLH secondary to sarcoidosis is rare. We present a case of HLH associated with recently diagnosed sarcoidosis in a 61year-old female.
The Effect of Nonideal Cascade Impactor Stage Collection Efficiency Curves on the Interpretation of the Size of Inhaler-Generated Aerosols

Cascade impactors, operating on the principle of inertial size separation in (ideally) laminar flow, are used to determine aerodynamic particle size distributions (APSDs) of orally inhaled product (OIP) aerosols because aerodynamic diameter can be related to respiratory tract deposition. Each stage is assumed typically to be an ideal size fractionator. Thus, all particles larger than a certain size are considered collected and all finer particles are treated as penetrating to the next stage (a step function stage efficiency curve). In reality, the collection efficiency of a stage smoothly increases with particle size as an “S-shaped” curve, from approximately 0% to 100%. Consequently, in some cases substantial overlap occurs between neighboring stages. The potential for bias associated with the step-function assumption has been explored, taking full resolution and two-stage abbreviated forms of the Andersen eight-stage nonviable impactor (ACI) and the next-generation pharmaceutical impactor (NGI) as example apparatuses. The behavior of unimodal, log-normal APSDs typical of OIP-generated aerosols has been investigated, comparing known input values to calculated values of central tendency (mass median aerodynamic diameter) and spread (geometric standard deviation, GSD). These calculations show that the error introduced by the step change assumption is larger for the ACI than for the NGI. However, the error is sufficiently small to be inconsequential unless the APSD in nearly monodisperse (GSD ≤1.2), a condition that is unlikely to occur with realistic OIPs. Account may need to be taken of this source of bias only for the most accurate work with abbreviated ACI systems.
Real-Time Driver Maneuver Prediction Using LSTM

Driver maneuver prediction is of great importance in designing a modern Advanced Driver Assistance System (ADAS). Such predictions can improve driving safety by alerting the driver to the danger of unsafe or risky traffic situations. In this research, we developed a model to predict driver maneuvers, including left/right lane changes, left/right turns and driving straight forward 3.6 seconds on average before they occur in real time. For this, we propose a deep learning method based on Long Short-Term Memory (LSTM) which utilizes data on the driver's gaze and head position as well as vehicle dynamics data. We applied our approach on real data collected during drives in an urban environment in an instrumented vehicle. In comparison with previous IOHMM techniques that predicted three maneuvers including left/right turns and driving straight, our prediction model is able to anticipate two more maneuvers. In addition to this, our experimental results show that our model using identical dataset improved F1 score by 4% and increased to 84%.
The Public Sector Accounting Reform of 2014 in the Light the Experiences of the Local Governments : A Pilot Project to Explore the Problems

The renewal of public finance accounting in 2014 can be labelled as one of the greatest changes in the Hungarian public sector. The accounting information system used previously had significant shortcomings, which ultimately led to disruptions in the operation of the local government system and its indebtedness. The aim of the research is to explore the experience of the local governments regarding the process of the introduction of the accounting reform and the emerging system. In the research, interviews and small group sessions were conducted with 18 experts from 8 institutions. Based on what was said, the transitional period was a turbulent process, and compliance with the new regulation tested the adaptability of local governments. The opinions regarding the new system are heterogeneous. According to the involved experts, the new approach can provide a more true and fair view and present up-to-date information about the given organisational unit. However, the introduction of the new system was not fully successful as the new system proved to be more complex and more difficult to handle. In addition, it was also revealed that in most cases the data of the accounting information system fail to fulfil their intended purpose in financial management.
THE INFLUENCE OF DIFFERENT STRUCTURE OF MAGNETIC MODULATION RING ON THE TORQUE PERFORMANCE OF COAXIAL MAGNETIC GEAR

In coaxial magnetic gear (CMG), magnetic modulation ring is composed of a modulator and a connecting bridge. The torque performance of the magnetic gear is affected by the different structures of the magnetic modulation ring. In this paper, fifteen different kinds of magnetic modulation rings with different structures are proposed; they consist of three different shapes of modulators and five different locations of connection bridges. By using the two-dimensional finite element method (FEM), the magnetic flux density, magnetic line distribution, static torque, and steady-state torque of the CMG with different structures of magnetic modulation ring are analyzed. The results show that the innermost bridge has the least effect on the torque and torque ripple of the CMG, while the outermost bridge has the opposite effect. The torque capacity of the circular modulator and arc modulator is higher than that of the square modulator, and the circular modulator helps to reduce the inner torque ripple, while the square modulator helps to reduce the outer torque ripple. This paper can provide some references for the design of the magnetic modulation ring.
Thermal Modeling and Characterization of Twisted Coiled Actuators for Upper Limb Wearable Devices

A key issue with wearable technology today is the popular use of stiff electrical motors to actuate the joints. Although their performance is ideal in terms of power, bandwidth, accuracy, and speed, they do not have the inherent ability to replicate many key biological properties. This includes the ability to modulate compliance, produce linear actuation, and provide high power-to-weight ratios. The solutions to replicating these properties usually include complex mechanisms in the form of gear boxes, parallel spring mechanisms, and control algorithms, making these devices costly, heavy, and large. As an alternative, the twisted coiled actuator (TCA) is flexible, soft, and can provide large strain and high power outputs when thermally activated. This article provides a new solution to modeling the thermal behavior of TCAs within an active air cooled enclosure. The thermal models were validated against multiple inner tube diameters, heating powers, cooling pressures, and TCA sizes, and predicted the temperature to within 8.16 $^\circ \text{C}$ during heating, and 4.33 $^\circ \text{C}$ during cooling, corresponding to 92.7% and 94.5% accuracy, respectively. After model validation, the sensitivity of the input design parameters to performance characteristics, such as system bandwidth and efficiency, were investigated to provide specific use cases on model optimization techniques.
What Do Linguistic Expressions Tell Us about Learners’ Confusion? A Domain-Independent Analysis in MOOCs

The substantial growth of online learning, and in particular, through massively open online courses (MOOCs), supports research into nontraditional learning contexts. Learners’ confusion is one of the identified aspects which impact the overall learning process, and ultimately, course attrition. Confusion for a learner is an individual state of bewilderment and uncertainty as to how to move forward. The majority of recent works in MOOCs neglects the individual factor and measure the influence of community-related aspects (e.g., votes, views) for confusion classification. While these are useful measures, these models neglect the personalized context, such as an individual's affect or emotions. Toward this, and within the MOOC context, we propose machine learning models based solely on language and discourse features extracted from learners’ discussion posts. With over 83% F1-score in all domains, it is evident that linguistic-only features are highly effective in confusion classification, with our models outperforming previous models developed for confusion classification. In this article, we also obtain good performance for cross-domain confusion classification between 70.7% and 84.5% F1-score for all domain pairs (i.e., training on one domain and testing on another domain). Primarily, this article contributes through the development of a novel linguistic feature set that is predictive for effective confusion classification.
THE CHEMICAL BONDING OF Re3Cl9 AND REVEALED BY THE ADAPTIVE NATURAL DENSITY PARTITIONING ANALYSES

Chemical bonding of neutral rhenium trichloride Re3Cl9 and doubly charged has been brought into question in the current work. Despite recently reported propositions of π-aromaticity of neutral Re3Cl9 based on negative nuclear independent chemical shift (NICS) values[ 1 , 2 ] to the contrary, it is shown to be a purely classical chemical molecule, according to the results of the recently developed Adaptive Natural Density Partitioning (AdNDP) analysis. [ 3-5 ] The formation of three consecutive double bonds in a triatomic cycle formed by rhenium atoms that was initially predicted by Cotton et al.[ 6-8 ] is confirmed. The chemical bonding picture changes dramatically upon addition of two excess electrons to Re3Cl9. The rhenium atoms of the resulting doubly charged cluster are shown to be held together via three single Re-Re σ-bonds, three Re-Cl-Re σ-bonds, and a totally delocalized π-bond based on valence d atomic orbitals (d-AO) of rhenium atoms with minor contributions coming from the density associated with six apical chlorine atoms, which makes π-aromatic.
Modeling the dynamics of partial wetting

The behavior of interfaces and contact lines arises from intermolecular interactions like Van der Waals forces. To consider this multi–phase behavior on the continuum scale, appropriate physical descriptions must be formulated. While the Continuum Surface Force model is well–engineered for the description of interfaces, there is still a lack of treatment of contact lines, which are represented by the intersection of a fluid–fluid interface and a solid boundary surface. In our approach we use the “non compensated Young force” to model contact line dynamics and therefore use an extension to the Navier–Stokes equations in analogy to the extension of a two–phase interface in the CSF model. Because particle–based descriptions are well–suited for changing and moving interfaces we use Smoothed Particle Hydrodynamics. In this way we are not only able to calculate the equilibrium state of a two–phase interface with a static contact angle, but also for instance able to simulate droplet shapes and their dynamical evolution with corresponding contact angles towards the equilibrium state, as well as different pore wetting behavior. Together with the capability to model density differences, this approach has a high potential to model recent challenges of two–phase transport in porous media. Especially with respect to moving contact lines this is a novelty and indispensable for problems, where the dynamic contact angle dominates the system behavior.
Diagnosis of Open-Phase Faults for a Five-Phase PMSM Fed by a Closed-Loop Vector-Controlled Drive Based on Magnetic Field Pendulous Oscillation Technique

An online diagnostic approach of open-phase faults for a five-phase permanent magnet synchronous motor (PMSM) fed by a closed-loop vector-controlled drive is presented in this article. This approach is accomplished based on the magnetic field pendulous oscillation (MFPO) phenomenon, in which a significant “swing-like” pendulous oscillation in the magnetic field is observed in case of open-phase faults. According to an analysis of the signatures of MFPO patterns under faulty conditions, all possible open-phase faults are detected, including single-phase open faults, two-adjacent phase open faults, and two-nonadjacent phase open faults. Moreover, this approach is capable of localizing the faulted phase/phases by further extracting the phase angle features of MFPO angular position waveforms under faulty conditions. Meanwhile, in order to minimize the number of sensors to reduce the implementation cost of this diagnostic approach, a phase-locked loop technique is developed to overcome the fault masking difficulties associated with the compensation action of the closed-loop vector-controlled drive. As a result, this diagnostic approach only requires four current sensors and a speed sensor, which are typically already available in five-phase PMSM drive systems for control purposes. Finally, experimental results demonstrate the effectiveness of the presented approach.
Indicators of Good Principal Leadership Based on Principal, Teachers, and Administration Staff Perspectives in The Era of Industrial Revolution 4.0

Research relating to the leadership of principals in Indonesia generally uses indicators from various theories and literatures. In fact, principal, teachers and staff who are directly involved with the activities of school principals, of course, they have their own criteria and indicators relate to good principal leadership. This study aims to explore and find the good principal leadership indicators based on principals, teachers, and administration staff perspectives. An open question about the characteristics of a good principal ledership was asked to 124 respondents (12 principals, 93 teachers, and 19 administrative staff). The answer is directed and written at least 3 characteristics words. Furthermore, 670 statement as answers were analyzed qualitatively to take the similarity of meaning and there are 36 Statements with different meaning. Quantitative analysis is done to sort the indicators based on Response Indeks (RI). The results show there are 29 indicators, namely: Wise, Honest, To be responsible, Role models, Discipline, Assertive, Charimatic, Mastering IT, Fair, Smart, Visionary, Transparent, Democratic, Responsive, Open, Friendly, Protect, Humble, Communicative, Motivator, Souled leader, Able to solve problems, Creative, Loyal, Professional, Social soul, SelfCofidence, and Trustful.
Selection of Optimal Building Facade Texture Images From UAV-Based Multiple Oblique Image Flows

Oblique photogrammetry with multiple cameras onboard unmanned aerial vehicle (UAV) has been widely applied in the construction of photorealistic three-dimensional (3-D) urban models, but how to obtain the optimal building facade texture images (BFTIs) from the abundant oblique images has been a challenging problem. This article presents an optimization method for selection of BFTIs from the image flows acquired by five oblique cameras onboard UAV. The proposed method uses multiobjective functions, which consists of the smallest occlusion of the BFTI and the largest façade texture area, to select the optimal BFTIs. Geometric correction, color equalization, and texture repairment are also considered for correction of BFTI’s distortions, uneven color, and occlusion by other objects such as trees. Visual C++ and OpenGL under the Windows Operating System are used to implement the proposed methods and algorithms. The proposed method is verified using 49 800 oblique images collected by five cameras onboard the Matrice 600 Pro (M600 Pro) UAV system over Dongguan Street, in the City of Ji’nan, Shandong, China. To restore the partially occluded textures, different thresholds and different sizes of windows are experimented, and a template window of $200\times200$ pixels2 is recommended. With the proposed method, 2740 BFTIs are extracted from 49 800 oblique images. As compared with the Pix4Dmapper and Smart 3-D method, it can be concluded that the optimal texture can be selected from the image flow acquired by multiple cameras onboard UAV and the approximately 95% memory occupied by the original BFTIs is reduced.
High Isolation and Low Cross-Polarization of Low-Profile Dual-Polarized Antennas via Metasurface Mode Optimization

A low-profile dual-polarized metasurface antenna with high isolation and low cross-polarization is proposed in this communication. The proposed metasurface consists of an array of <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> patches. Through characteristic mode analysis (CMA), a pair of degenerate modes is identified to achieve the desired radiation features. By modifying the patches of the metasurface, the strongest mode current distributions of the two modes are moved from the center to the edge of the metasurface. One feed port can efficiently excite only one particular mode, and the other mode cannot be excited simultaneously. Each of the modes are differentially fed using two Y-shaped microstrip lines via two slots. As a result, both high isolation and low cross-polarization can be obtained. The simulation and experimental results show that the proposed antenna achieves not only a low profile of <inline-formula> <tex-math notation="LaTeX">$0.05\lambda _{0}$ </tex-math></inline-formula> (where <inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the free-space wavelength at the center resonant frequency) but also a broad impedance bandwidth of 36% and a high isolation of 53 dB. In particular, the enhanced cross-polarization discrimination (XPD) is lower than −40 dB at the broadside, lower than −33 dB within ±30° of the main lobe, and lower than −28 dB within ±60° of the main lobe.
First study of food webs in a large glacial river: the trophic role of invasive trout

The aim of this study was to determine the food webs structure of a large Patagonian river in two river sections (Upstream and Midstream) and to evaluate isotopic overlap between native and introduced species. We used stable isotope analyses of δ15N and δ13C and stomach content. The Upstream section had a more complex food webs structure with a greater richness of macroinvertebrates and fish species than Midstream. Upstream basal resources were dominated by filamentous algae. Lake Trout were found to have a higher trophic position than all other fish species in that area although, the most abundant fish species, were Rainbow Trout. Depending on the life stage, Rainbow Trout shifted from prey to competitor/predator. In the Midstream section, the base of the food webs was dominated by coarse particulate organic matter, and adult Rainbow Trout had the highest trophic level. Isotopic values changed among macroinvertebrates and fish for both areas. The two most abundant native and invasive species — Puyen and Rainbow Trout — showed an isotopic separation in Midstream but did not in Upstream areas. The presence of invasive fish that occupy top trophic levels can have a significant impact on native fish populations that have great ecological importance in the region.
Mitigation of Leakage in FMCW Radars by Background Subtraction and Whitening

Leakage in frequency-modulated continuous-wave (FMCW) radar with a homodyne receiver induces strong signal components in the lower frequency parts of the radar observations. There, the dynamic range of the observations has been reduced, such that close and weak targets are hard to detect. In this letter, a signal processing method is proposed to mitigate the leakage. First, background subtraction is applied to cancel the leakage. As the cancellation is imperfect, a noisy signal portion remains: the leakage noise. A statistical model is developed to describe the leakage noise as a colored noise process. This model is parameterized from measurements and used to whiten the observations. As a result, the dynamic range is improved, and the close targets become better detectable.
Diel fledging patterns among grassland passerines: Relative impacts of energetics and predation risk

ABSTRACT The time of day that nestlings fledge from a nest is thought to be shaped by predation risk and energetics. To minimize predation risk, fledging is predicted to start as early in the day as possible so that nestlings can maximize time outside the nest to find a safe place to stay before nightfall. Fledging times are predicted to be tightly grouped and to not be affected by the number of nestlings, given that all nestlings are responding to the same relative risk of predation. Conversely, energetic considerations predict that fledging time of day should vary so that nestlings can maximize energy intake before having to forage for themselves. However, data to evaluate the relative importance of these drivers in grassland birds are scarce because of the difficulty of observing nestlings as they fledge. We used nest surveillance video from 178 nests to evaluate how the initiation and duration of fledging varied among 7 grassland passerine species, as well as by the number of nestlings in the nest and fledging date. Fledging initiation varied most strongly by species, with some effects of date. Across species, the median start time of fledging was 4.55 hr after sunrise. Fledging before the solstice started ∼30 min earlier compared to fledging at or after the solstice. Fledging duration increased with number of nestlings in the nest and was spread over >1 day in 21% of nests. While our results primarily supported the hypothesis that fledging is motivated by energetic considerations, additional data on basic life history traits and behavior will be needed to fully understand how fledging grassland birds balance energetics against predation risk.