Miracle-dz/UniFAR-FTUs huggingface dataset:
Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition

In recent years, sparse representation based classification (SRC) has emerged as a popular technique in face recognition. Traditional SRC focuses on the role of the -norm but ignores the impact of collaborative representation (CR), which employs all the training examples over all the classes to represent a test sample. Due to issues like expression, illumination, pose, and small sample size, face recognition still remains as a challenging problem. In this paper, we proposed a patch based collaborative representation method for face recognition via Gabor feature and measurement matrix. Using patch based collaborative representation, this method can solve the problem of the lack of accuracy for the linear representation of the small sample size. Compared with holistic features, the multiscale and multidirection Gabor feature shows more robustness. The usage of measurement matrix can reduce large data volume caused by Gabor feature. The experimental results on several popular face databases including Extended Yale B, CMU_PIE, and LFW indicated that the proposed method is more competitive in robustness and accuracy than conventional SR and CR based methods.
Stimulated Raman scattering and second harmonic generation from a Nd : Y V O 4 laser at 1064 nm to generate 587 nm .

We have investigated a light generation at 587 nm based on a combination of two nonlinear processes, stimulated Raman scattering (SRS) in Nd : GdV O4 and second harmonic generation (SHG) in BBO, which efficiently convert the 1064 nm fundamental wavelength of a Nd : Y V O4 laser to yellow light. An average power of 0.72W was measured at the output of 1174 nm before SHG with only 3.7W pumping.
Dynamic Rendering of Remote Indoor Environments Using Real-Time Point Cloud Data

Modern color and depth (RGB-D) sensing systems are capable of reconstructing convincing virtual representations of real world environments. These virtual reconstructions can be used as the foundation for virtual reality (VR) and augmented reality environments due to their high-quality visualizations. However, a main limitation of modern virtual reconstruction methods is the time it takes to incorporate new data and update the virtual reconstruction. This delay prevents the reconstruction from accurately rendering dynamic objects or portions of the environment (like an engineer performing an inspection of a machinery or laboratory space). The authors propose a multisensor method to dynamically capture objects in an indoor environment. The method automatically aligns the sensors using modern image homography techniques, leverages graphics processing units (GPUs) to process the large number of independent RGB-D data points, and renders them in real time. Incorporating and aligning multiple sensors allows a larger area to be captured from multiple angles, providing a more complete virtual representation of the physical space. Performing processing on GPU's leverages the large number of processing cores available to minimize the delay between data capture and rendering. A case study using commodity RGB-D sensors, computing hardware, and standard transmission control protocol internet connections is presented to demonstrate the viability of the proposed method.
Research on Distillation Technology to Extract Essential Oil from Melaleuca Alterfornia ( TTO )

Tea tree oil (TTO) comes from the leaves of Melaleuca alternifornia that belongs to the myrtle family (Myrtaceae). It is one of the most powerful immune system stimulants and sorts out most viral, bacterial and fungal infections in a snap, while it is great to heal wounds and acnes. In Vietnam, Melaleuca trees can grow on acid land that stretches in a large portion of lands in the Mekong Delta region. So, there are some Melaleuca plantations developed under the Vietnamese government plans of increasing plantation forests now. The crude TTO was produced from the leaves and terminal branches of Melaleuca tree by steam distillation methods: using micro-wave, using outside boiler. The cleaned TTO with high concentration of terpinen-4-ol (over 95% v/v) was obtained by vacuum distillation process at different reflux ratios. The results showed that, in steam distillation process, the average productivity of crude TTO is among 2.37% (v/dry-wt) or 1.23% (v/wet-wt) and insignificantly changed with differences of raw material moisture, the vapour speed, also with different steam distillation methods. The optimal steam distillation time is 250 minutes. In vacuum distillation process, the optimal reflux ratio is R=2 and TTO product satisfied for pharmaceutical requirement. The purification of TTO meets International Standard ISO 4730. The results of this study are the basis for designing of TTO extraction systems on a large scale for industrial production.
Does maternal employment affect child nutrition status? New evidence from Egypt

ABSTRACT Even though maternal employment can increase family income, several studies suggest that it could have adverse consequences on children’s health. In this study, we use a nationally representative sample of 12,888 children, aged 0–5 years from Egypt to examine the impact of maternal employment on child nutritional indicators, namely: stunting, wasting, and being underweight and overweight. We adopted various estimation methods to control for observable and unobservable household characteristics in order to identify the causal effect of maternal employment. These different techniques include, propensity score matching (PSM), OLS regression with controlling for a wide range of individual characteristics, and an instrumental variable two-stage least squares (IV 2SLS) approach. Results of the PSM and OLS suggest that maternal employment is weakly associated with having a malnourished child. On the other hand, the IV 2SLS suggests a stronger and significant association between maternal employment and poor nutritional status among children.
Structural, Optical and Electrical Properties of NiO Nanostructure Thin Film

Nickel oxide was deposited on highly cleaned glass substrates using spray pneumatic technique. The effect of precursor molarity on structural, optical and electrical properties has been studied. The XRD lines of the deposited NiO were enhanced with increasing precursor molarity due to the improvement of the films crystallinity. It was shown that the crystalline size of the deposited thin films was calculated using DebyeScherer formula and found in the range between 9 and 47 nm. The optical properties have been discussed in this work. The absorbance (A), the transmittance (T) and the reflectance (R) were measured and calculated. Band gap energy is considered one of the most important optical parameter, therefore measured and found ranging between 3.64 and 3.86 eV. The NiO thin film reduces the light reflection for visible range light. The increase of the electrical conductivity to maximum value of 0.0896 (Ω cm) – 1 can be explained by the increase in carrier concentration of the films. A good electrical conductivity of the NiO thin film is obtained due to the electrically low sheet resistance. NiO can be applied in different electronic and optoelectronic applications due to its high band gap, high transparency and good electrical conductivity.
1 A Comparative Study of Predictable DRAM Controllers

Recently, the research community has introduced several predictable DRAM controller designs that provide improved worst-case timing guarantees for real-time embedded systems. The proposed controllers significantly differ in terms of arbitration, configuration and simulation environment, making it difficult to assess the contribution of each approach. To bridge this gap, this paper provides the first comprehensive evaluation of state-of-the-art predictable DRAM controllers. We propose a categorization of available controllers, and introduce an analytical performance model based on worst-case latency. We then conduct an extensive evaluation for all state-of-the-art controllers based on a common simulation platform, and discuss findings and recommendations.
Microfoundations of Inflation Persistence in the New Keynesian Phillips Curve

This paper proposes a dynamic stochastic general equilibrium model that endoge­nously generates inflation persistence. We assume that although firms change prices periodically, they face convex costs that preclude optimal adjustment. In essence, the model assumes that price stickiness arises from both the frequency and size of price adjustments. The model is estimated using Bayesian techniques, and the results strongly support both sources of price stickiness in the U.S. data. In contrast with traditional sticky price models, the framework yields inflation inertia, a delayed effect of monetary policy shocks on inflation, and the observed "reverse dynamic" correlation between inflation and economic activity.
Effects of market default risk on index option risk-neutral moments

We investigate the relative importance of market default risk in explaining the time variation of the S&P 500 Index option-implied risk-neutral moments. The results demonstrate that market default risk is positively (negatively) related to the index risk-neutral volatility and skewness (kurtosis). These relations are robust in the presence of other factors relevant to the dynamics and microstructure nature of the spot and option markets. Overall, this study sheds light on a set of economic determinants which help to understand the daily evolution of the S&P 500 Index option-implied risk-neutral distributions. Our findings offer explanations of why theoretical predictions of option pricing models are not consistent with what is observed in practice and provide support that market default risk is important to asset pricing.
Boltzmann-type models with uncertain binary interactions

In this paper we study binary interaction schemes with uncertain parameters for a general class of Boltzmann-type equations with applications in classical gas and aggregation dynamics. We consider deterministic (i.e., a priori averaged) and stochastic kinetic models, corresponding to different ways of understanding the role of uncertainty in the system dynamics, and compare some thermodynamic quantities of interest, such as the mean and the energy, which characterise the asymptotic trends. Furthermore, via suitable scaling techniques we derive the corresponding deterministic and stochastic Fokker-Planck equations in order to gain more detailed insights into the respective asymptotic distributions. We also provide numerical evidences of the trends estimated theoretically by resorting to recently introduced structure preserving uncertainty quantification methods.
Racial Disparities and Mistrust in End-of-Life Care

There are established racial disparities in healthcare, including during end-of-life care, when poor communication and trust can lead to suboptimal outcomes for patients and their families. In this work, we find that racial disparities which have been reported in existing literature are also present in the MIMIC-III database. We hypothesize that one underlying cause of this disparity is due to mistrust between patient and caregivers, and we develop multiple possible trust metric proxies (using coded interpersonal variables and clinical notes) to measure this phenomenon more directly. These metrics show even stronger disparities in end-of-life care than race does, and they also tend to demonstrate statistically significant higher levels of mistrust for black patients than white ones. Finally, we demonstrate that these metrics improve performance on three clinical tasks: in-hospital mortality, discharge against medical advice (AMA) and modified care status (e.g., DNR, DNI, etc.).
Development of Bona Fide Pre-Employment Physical Fitness Standards for Canadian Forces (CF) and Department of National Defence (DND) Firefighters: Sub-study of Cardiopulmonary Responses to Exercise in

Background: The self contained breathing apparatus (SCBA) increases the expiratory pressure required to maintain high rates of ventilation, suggesting that the expiratory work of breathing (WOB) is increased; however, this has never been reported. Objective: To determine if the WOB is increased with the SCBA regulator (BA condition) compared with a low resistance breathing valve (RV condition) during exercise. Research Design and Methods: Twelve healthy male subjects underwent two randomized exercise trials, consisting of cycling at 150, 180, 210, and 240 watts. Inspired and expired tidal volumes were measured using a body plethysmograph while esophageal pressures were measured with an esophageal balloon. Modified Campbell diagrams were created in order to calculate the resistive and elastic components of WOB during inspiration and expiration. Results: There were no differences in WOB between BA and RV conditions at 150 W. End-inspiratory and end-expiratory lung volumes were elevated (p<0.05)
Determination of measurement noise, conductivity errors and electrode mislocalization effects to somatosensory dipole localization

Calculating the spatial locations, directions and magnitudes of electrically active sources of human brain by using the measured scalp potentials is known as source localization. An accurate source localization method requires not only EEG data but also the 3-D positions and number of measurement electrodes, the numerical head model of the patient/subject and the conductivities of the layers used in the head model. In this study we computationally determined the effect of noise, conductivity errors and electrode mislocalizations for electrical sources located in somatosensory cortex. We first randomly selected 1000 electric sources in somatosensory cortex, and for these sources we simulated the surface potentials by using average conductivities given in the literature and 3-D positions of the electrodes. We then added random noise to measurements and by using noisy data; we tried to calculate the positions of the dipoles by using different electrode positions or different conductivity values. The estimated electrical sources and original ones are compared and by this way the effect of measurement noise, electrode mislocalizations and conductivity errors to somatosensory dipole localization is investigated. We conclude that for an accurate somatosensory source localization method, we need noiseless measurements, accurate conductivity values of scalp and skull layers and the accurate knowledge of 3-D positions of measurement sensors.
Photosynthetic impact of hypoxia on in hospite zooxanthellae in the scleractinian coral Pocillopora damicornis

Shallow water coral reefs may experience hypoxia under conditions of calm weather doldrums. Anaerobic responses of endosymbionts (i.e. zooxanthellae) within Pocillopora damicornis coral colonies were tested using both slow and fast chlorophyll a fluorescence induction kinetics. Zooxanthellae were examined in hospite when exposed to control conditions (26°C, 200 µmol pho- tons m -2 s -1 , 100% air-saturation, 4 cm s -1 flow) and to 2 treatments of reduced air content (40 and 0%), achieved by controlling the N2:O2 ratio in water circulating at 2 cm s -1 . Furthermore, the impact of water flow on photosynthesis was examined at 0% air saturation by turning off the flow entirely (0 cm s -1 ), thereby mimicking the environmental conditions of calm weather doldrums. Corals exposed to depleted air content (0% with and without flow) showed a significant decrease (p < 0.001) in effective quantum yield (φPSII) in comparison with controls. Maximum quantum yield was signifi- cantly reduced when gas exchange was inhibited (0% without flow), whereas non-photochemical quenching (NPQ) was not affected. Fast polyphasic fluorescence transients of chlorophyll a fluores- cence showed a significant increase in minimum dark-adapted fluorescence, F0, when corals were exposed to anaerobic conditions. Furthermore, an increase in the J peak (2 ms) corresponding to the reduction of the primary electron acceptor, QA, was observed in 0% air-saturation with flow. We found that the most sensitive parameters for detecting physiological change associated with hypoxia were φPSII using slow (pulse-amplitude modulation) fluorescence kinetics, as well as an increase in the O peak, ϕPo (electron transport efficiency before QA), and an elevation of the J peak on a double- normalised transient using fast (Plant Efficiency Analyser) induction kinetics.
Postnatal Myocardial Performance Index (MPI) in Recipient Infants of Twin-Twin Transfusion Syndrome: A Pulsed-Doppler Study

Twin-twin transfusion syndrome (TTTS), which is a complication of monochorionic diamniotic (MD) twin gestations, is known to be one of the most hazardous events in the perinatal-neoatal period [14]. In the womb, TTTS sometimes result in hydrops fetalis, severe intrauterine growth restriction, and fetal death. In postnatal infants with TTTS, especially in their recipient infants, it may be possible that intractable cardiorespiratory disturbances emerge promptly after birth. Neuronal damage such as periventricular leukomalacia (PVL), which cause occurrence of cerebral palsy in the growth stage, may be followed by these early neonatal events. Several past studies revealed that the pathophysiological basis of TTTS lay upon fetal heart failure caused by major vascular anastomoses in the common placenta [1-4]. Although both early assessment of cardiac performance and appropriate care for heart failure are essential in these infants for stabilization of their general status in the early neonatal period, accurate, detailed examination of cardiac function using methods such as invasive cardiac catheterization may be difficult or impossible[5-8]. Despite improvements in neonatal echocardiography as a non-invasive tool for assessing early cardiac function, there is still no consensus about which indices are most useful for this purpose in very premature infants. Recently, Tei has proposed a new cardiac performance index based on Doppler echocardiography that allows assessment of both systolic and diastolic ventricular function [9-11]. An abnormal increase in this myocardial performance index (MPI) has been proved to be a reliable indicator of the early phase of chronic heart failure in adults [9-13]. Several authors have also suggested that MPI might be of value in children with congenital heart disease and cardiomyopathy [14-16], and more recently in fetuses, neonates and premature infants [17,18]. The purpose of the present study was to assess the usefulness of MPI for postnatal circulatory management of recipient infants of TTTS.
Vehicle Motion Detection using CNN

This project describes a series of vehicle motion detection experiments for front camera video recordings of moving vehicles gathered from the KITTI dataset [7]. The experiments differ from existing attempts with the leverage of complex CNN architectures and the derivation and combination of input channels that intend to capture different aspects of the raw image including flow direction and object masks. Both transfer learning and built-from-scratch models are trained and evaluated. Input channel choice, fine tuning techniques including down-sampling and hyperparameter sweep, and other optimizations and observations are discussed. Three aspects of vehicle motion forward velocity, acceleration, and angular velocity are optimized using mean-square error loss, with the prediction result consolidated and visualized on top of the video frames. Overall, we achieved 3.536 validation MSE loss and 7.21 test MSE loss.
Plasmonics for Improved Photovoltaic Devices

Several approaches have been adopted in the past for increasing the light absorption in photovoltaic solar cells. The introduction of a plasmonic layer of Ib metal nanoparticles (pure or embedded in a dielectric layer) has been recognized as a viable alternate approach for enhancing light absorption. The scattering from metal nanoparticles near their localized plasmon resonance seemed to be a promising way of increasing the light absorption in thin-film solar cells. Enhancements in photo current have been observed for a wide range of semiconductors and solar cell configurations. In this short note, a review of the experimental and theoretical progress that has been made in recent years, the basic mechanisms, and an outlook on future prospects in this area is presented.
Quantifying scales of spatial variability in algal turf assemblages on coral reefs

Quantifying variability over multiple spatial scales is a fundamental goal in ecology,providing insight into which scale-dependent processes most strongly influence community structure.On coral reefs, the ubiquitous turf algae are the primary food source for herbivores and competitorsfor space with corals. Turf algae will likely increase in the future, because they thriveunder conditions that reduce coral cover. Turfs are typically treated as a single homogeneousfunctional group, but analyzing them as a variable assemblage is more informative. We used ahierarchical sampling design to quantify 4 scales of variability in turf assemblages from centimeters(within single dead coral heads) to kilometers (across islands) on the rarely studied LhaviyaniAtoll, Maldives. We used 4 metrics, each reflecting different ecological processes: percent cover,canopy height, richness, and assemblage composition. For most of these metrics, variability wassignificant at multiple spatial scales. However, for all metrics, the smallest scale (centimeters)explained the greatest proportion of overall variability. The least variability in cover, canopyheight, and richness occurred among sites (100s meters), suggesting that processes such as competition,predation, and vegetative growth are heterogeneous at small scales. In contrast, assemblagecomposition was least variable at the largest scale (kilometers), suggesting that oceanographicprocesses or a well-mixed propagule supply reduce variability. With declining coral andincreasing cover of turf on reefs worldwide, it will become increasingly important to understandthe dynamics of coral−turf competitive interactions. However, because turf assemblages arehighly variable at small spatial scales, these interactions require more detailed consideration.
NDSE : Method for Classification Instance Generation Given Meta-Feature Description

This paper addresses the problem of instance generation. We propose a method called NDSE that generates an instance of binary classification problem given its vector description. We solve this problem by reducing it to an optimization task and applying genetic search. We use operators of addition and removal of objects and features to handle crossover and mutation operators over classifications datasets for genetic algorithm. We conducted several experiments, the results of which show that our method outperforms baseline methods.