Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Classroom Monitoring Using Novel Real-Time Facial Expression Recognition System

Emotions play a vital role in education. Technological advancement in computer vision using deep learning models has improved automatic emotion recognition. In this study, a real-time automatic emotion recognition system is developed incorporating novel salient facial features for classroom assessment using a deep learning model. The proposed novel facial features for each emotion are initially detected using HOG for face recognition, and automatic emotion recognition is then performed by training a convolutional neural network (CNN) that takes real-time input from a camera deployed in the classroom. The proposed emotion recognition system will analyze the facial expressions of each student during learning. The selected emotional states are happiness, sadness, and fear along with the cognitive–emotional states of satisfaction, dissatisfaction, and concentration. The selected emotional states are tested against selected variables gender, department, lecture time, seating positions, and the difficulty of a subject. The proposed system contributes to improve classroom learning.
Growth and fatty acid distribution over lipid classes in Nannochloropsis oceanica acclimated to different temperatures

After light, temperature is the most relevant environmental parameter in outdoors cultivation of microalgae. Suboptimal and supraoptimal temperatures negatively impact growth and photosynthetic performance with a subsequent effect on lipid accumulation. It is generally recognised that lower temperatures trigger an increase in fatty acid desaturation while higher temperatures trigger the opposite reaction. The effect of temperature on lipid classes has been less studied in microalgae and in certain cases, the effect of light cannot be completely excluded. In this research, the effect of temperature on growth, photosynthesis, and lipid class accumulation in Nannochloropsis oceanica was studied at a fixed light gradient with a constant incident light intensity (670 μmol m-2 s-1). A turbidostat approach was used to achieve temperature acclimated cultures of Nannochloropsis oceanica. Optimal growth was found at 25-29°C, while growth was completely arrested at temperatures higher than 31°C and lower than 9°C. Acclimation to low temperatures triggered a decrease in absorption cross section and photosynthesis rates with a tipping point at 17°C. Reduced light absorption was correlated with a decrease in content of the plastid lipids monogalactosyldiacylglycerol and sulfoquinovosyldiacylglycerol. The increase of diacylglyceryltrimethylhomo-serine content at lower temperatures indicated a relevant role of this lipid class in temperature tolerance. Triacylglycerol content increased at 17°C and decreased at 9°C emphasising a metabolic switch in stress response. Total and polar eicosapentaenoic acid content remained constant at 3.5 and 2.4% w/w, despite the fluctuating lipid contents. Results show an extensive mobilisation of eicosapentaenoic acid between polar lipids classes at 9°C to ensure cell survival under critical conditions. Graphical Abstract
The role of elimination trees in sparse factorization

In this paper, the role of elimination trees in the direct solution of large sparse linear systems is examined. The notion of elimination trees is described and its relation to sparse Cholesky factorization is discussed. The use of elimination trees in the various phases of direct factorization are surveyed: in reordering, sparse storage schemes, symbolic factorization, numeric factorization, and different computing environments.
The Distribution of Normal Pressures on a Prolate Spheroid

During the course of certain experiments conducted at the National Physical Laboratory in 1919, a number of observations were made of the normal pressure at points on the surface of a prolate spheroid of length/diameter ratio 4. The results were compared with the corresponding pressures, calculated by purely theoretical methods, on a similar body in rectilinear motion in an ideal fluid. The comparison showed that agreement between theory and experiment was remarkably good for three-quarters the length of the model, even when the axis of the model was inclined to the direction of motion. The closeness of the agreement suggested that a more extensive investigation would be likely to lead to very interesting results. It was therefore decided to conduct a comprehensive series of experiments with a view to obtaining a more complete comparison. The scope of the investigation was widened to cover not only rectilinear motion which is reproduced in wind-tunnel experiments, but to include purely rotational motion (spin about a minor axis) and also motion in a circle. The whirling arm at the Laboratory provided the necessary means for reproducing this motion in the experimental part of the work.
GillespieSSA: Implementing the Gillespie Stochastic Simulation Algorithm in R

The deterministic dynamics of populations in continuous time are traditionally described using coupled, first-order ordinary differential equations. While this approach is accurate for large systems, it is often inadequate for small systems where key species may be present in small numbers or where key reactions occur at a low rate. The Gillespie stochastic simulation algorithm (SSA) is a procedure for generating time-evolution trajectories of finite populations in continuous time and has become the standard algorithm for these types of stochastic models. This article presents a simple-to-use and flexible framework for implementing the SSA using the high-level statistical computing language R and the package GillespieSSA. Using three ecological models as examples (logistic growth, Rosenzweig-MacArthur predator-prey model, and Kermack-McKendrick SIRS metapopulation model), this paper shows how a deterministic model can be formulated as a finite-population stochastic model within the framework of SSA theory and how it can be implemented in R. Simulations of the stochastic models are performed using four different SSA Monte Carlo methods: one exact method (Gillespie's direct method); and three approximate methods (explicit, binomial, and optimized tau-leap methods). Comparison of simulation results confirms that while the time-evolution trajectories obtained from the different SSA methods are indistinguishable, the approximate methods are up to four orders of magnitude faster than the exact methods.
Heat Conduction in a Rarefied Gas between Concentric Cylinders

Heat conduction through a rarefied gas contained between concentric cylinders is studied analytically. Emphasis is placed on the connection with the experimental determination of thermal accommodation coefficients by the low‐pressure method. The linearized BGK‐model equation is used, based on small relative temperature difference. Two coupled linear integral equations for the perturbed temperature and density are then formulated. An asymptotic analysis is carried out for the case of mean free path much greater than the inner but of the same order as the outer cylinder radius, which corresponds to typical operating conditions for experiments. The lowest‐order deviation of the heat flux from its free‐molecular value is of O[ln(Kn)/Kn], the same as that obtained by Knudsen iteration. Numerical calculations are performed to find this term. It is found that for a mean free path 20 or more times the inner cylinder radius the relative error introduced by using the free‐molecular value for the heat flux is less t.
Global bibliometric analysis of conceptual metaphor research over the recent two decades

Conceptual Metaphor has been a prevalent theme in the linguistic field for the recent twenty years. Numerous scholars worldwide have shown interest in it and published many academic papers from various stances on this topic. However, so far, there have been few rigorous scientific mapping investigations. With the help of bibliometric analysis tool, we selected 1,257 articles on Conceptual Metaphors published from 2002 to 2022, as collected in the Web of Sciences Core Collection database, from unique cognitive perspectives. The global annual scientific output of Conceptual Metaphor, including the cited articles, sources, keywords, and research trends, will be examined in this study. The most notable findings of this study are the following. First, there has been an upward trend in Conceptual Metaphor research over the last two decades. Second, the five most prominent research groups on Conceptual Metaphors are in Spain, the United States of America, China, Great Britain, and Russia. Third, future research on Conceptual Metaphors may focus on corpus linguistics, neurolinguistics, psychology, and critical discourse analysis. The interdisciplinary study may enhance the growth of Conceptual Metaphors.
An Automotive Reference Testbed with Trusted Security Services

While research in the field of automotive systems inclined in the past years towards technologies such as Vehicle-to-Everything (V2X) or Connected and Automated Vehicle (CAV), the underlying system security still plays a crucial role in assuring trust and system safety. The work at hand tackles the issue of automotive system security by designing a multi-service security system specially tailored for in-vehicle networks. The proposed trusted security services leverage Trusted Platform Module (TPM) to store secrets and manage and exchange cryptographic keys. To showcase how security services can be implemented in a in-vehicle network, a Reference TestBed (RTB) was developed. In the RTB, encryption and authentication keys are periodically exchanged, data is sent authenticated, the network is monitored by a Stateful Firewall and Intrusion Detection System (SF/IDS), and security events are logged and reported. A formal individual and multi-protocol analysis was conducted to demonstrated the feasibility of the proposed services from a theoretical point of view. Two distinct scenarios were considered to present the workflow and interaction between the proposed services. Lastly, performance measurements on the reference hardware are provided.
FIXING OF CYCLE SLIPS IN DUAL-FREQUENCY GPS PHASE OBSERVABLES USING DISCRETE WAVELET TRANSFORMS

The occurrence of cycle slips is a major limiting factor for achievement of sub-decimeter accuracy in positioning with GPS (Global Positioning System). In the past, several authors introduced a method based on different combinations of GPS data together with Kalman filter to solve the problem of the cycle slips. In this paper the same philosophy is used but with discrete wavelet transforms. For experiments we simulated artificial cycle slips in real data. Studies show that the selection of a proper wavelet basis functional basis for wavelet is a very important problem in wavelet transforms. Wavelet transforms accurately detects the place of cycle slips, especially in low noise test quantities.
A general dynamical statistical model with causal interpretation

Summary. We develop a general dynamical model as a framework for causal interpretation. We first state a criterion of local independence in terms of measurability of processes that are involved in the Doob–Meyer decomposition of stochastic processes; then we define direct and indirect influence. We propose a definition of causal influence using the concepts of a ‘physical system’. This framework makes it possible to link descriptive and explicative statistical models, and encompasses quantitative processes and events. One of the features of the paper is the clear distinction between the model for the system and the model for the observation. We give a dynamical representation of a conventional joint model for human immunodeficiency virus load and CD4 cell counts. We show its inadequacy to capture causal influences whereas in contrast known mechanisms of infection by the human immunodeficiency virus can be expressed directly through a system of differential equations.
Evaluation of E3SM land model snow simulations over the western United States

Abstract. Seasonal snow has crucial impacts on climate, ecosystems, and humans, but it is vulnerable to global warming. The land component (ELM) of the Energy Exascale Earth System Model (E3SM) mechanistically simulates snow processes from accumulation, canopy interception, compaction, and snow aging to melt. Although high-quality field measurements, remote sensing snow products, and data assimilation products with high spatio-temporal resolution are available, there has been no systematic evaluation of the snow properties and phenology in ELM. This study comprehensively evaluates ELM snow simulations over the western United States at 0.125∘ resolution during 2001–2019 using the Snow Telemetry (SNOTEL) in situ networks, MODIS remote sensing products (i.e., MCD43 surface albedo product), the spatially and temporally complete (STC) snow-covered area and grain size (MODSCAG) and MODIS dust and radiative forcing in snow (MODDRFS) products (STC-MODSCAG/STC-MODDRFS), and the snow property inversion from remote sensing (SPIReS) product and two data assimilation products of snow water equivalent and snow depth – i.e., University of Arizona (UA) and SNOw Data Assimilation System (SNODAS). Overall the ELM simulations are consistent with the benchmarking datasets and reproduce the spatio-temporal patterns, interannual variability, and elevation gradients for different snow properties including snow cover fraction (fsno), surface albedo (αsur) over snow cover regions, snow water equivalent (SWE), and snow depth (Dsno). However, there are large biases of fsno with dense forest cover and αsur in the Rocky Mountains and Sierra Nevada in winter, compared to the MODIS products. There are large discrepancies of snow albedo, snow grain size, and light-absorbing particle-induced snow albedo reduction between ELM and the MODIS products, attributed to uncertainties in the aerosol forcing data, snow aging processes in ELM, and remote sensing retrievals. Against UA and SNODAS, ELM has a mean bias of −20.7 mm (−35.9 %) and −20.4 mm (−35.5 %), respectively, for spring, and −13.8 mm (−27.8 %) and −10.2 mm (−22.2 %), respectively, for winter. ELM shows a relatively high correlation with SNOTEL SWE, with mean correlation coefficients of 0.69 but negative mean biases of −122.7 mm. Compared to the snow phenology of STC-MODSCAG and SPIReS, ELM shows delayed snow accumulation onset dates by 17.3 and 12.4 d, earlier snow end dates by 35.5 and 26.8 d, and shorter snow durations by 52.9 and 39.5 d, respectively. This study underscores the need for diagnosing model biases and improving ELM representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Total and Effective Colors of 501 Galaxies in the Cousins VRI Photometric System

Total color indices (VR)r, (VJ)r and effective color indices (VR) , , (V-1) , in the Cousins VRI photometric system are presented for 501 mostly normal galaxies. The colors are computed using a procedure outlined in the Third Reference Catalogue of Bright Galaxies (RC3) whereby standard color curves approximated by Laplace-Gauss integrals are fitted to observed photoelectric rnultiaperture photometry. 11 sources of such photometry were used for our analysis, each source being assigned an appropriate weight according to a rigorous analysis of residuals of the data frorn the best-fitting standard color curves. Together with the integrated B V and U B colors provided in RC3, our analysis widens the range of wavelength of homogeneously defined colors of normal galaxies of all Hubble types. We present color-color and color-type relations that can be modeled to understand the star formation history of galaxies.
X-ray bumps, iron K-alpha lines, and X-ray suppression by obscuring tori in Seyfert galaxies

We investigate the X-ray spectral properties of unobscured type 1 and obscured type 2 Seyferts as predicted by the unified Seyfert scheme. We consider the reprocessing of X-ray photons by photoelectric absorption, iron fluorescence, and Compton downscattering in the obscuring tori surrounding these active nuclei, and compute by Monte Carlo methods the reprocessed spectra as a function of the viewing angle. Depending on the optical depth and shape of the torus, and on the viewing angle, the X-ray flux can be suppressed by substantial factors when our line of sight is obscured. We show that an immediate consequence of the existence of an obscuring thick torus is the production in the spectra of type 1 Seyfert galaxies of a bump in the continuum above 10-20 keV and an Fe K-alpha line with significant equivalent width. In those type 2 Seyferts for which the hard X-ray spectrum has been substantially suppressed, the equivalent width of the Fe K-alpha line in the transmitted spectrum can be very large.
Diffraction-limited light collection: promises and challenges of a 50-m ELT

Programmes driving ELT design are discussed. The nature and evolution of circum-stellar shells and planetary discs are attractive, while the small angular sizes place basic properties, asymmetry and warps, beyond VLT capability. An ELT is neeed to reveal the conversion processes shell - disc - planets, planetary systems, Earth-like planets, habitability and life signatures. Formation and evolution of massive stars are dicussed as are stellar rotation and shape, surface spatial and temporal resolution and evolution. Stellar clusters are discussed as probes of galactic evolution, resolving CMDs for Virgo and Fornax cluster galaxies. High-resolution studies of AGNs are discussed as are supernovae with bearing on early star formation, galactic activity and cosmology. Finally, the requirements defined from the prime science drivers are confronted with technical realities.
Modeling a force‐free flux transfer event probed by multiple Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft

[1] A flux transfer event (FTE) was encountered by all five Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft just outside the dusk magnetopause on 20 May 2007. In the present paper, we fit the magnetic field observations from multiple satellites to a flux rope model in order to obtain the critical geometric parameters of this FTE. The model used includes both electromagnetic force and pressure gradient force and reduces to a force-free model when the magnetic tension is balanced mainly by the magnetic pressure gradient. The cross-sectional scales of the FTE were estimated to be 0.6 × 1.3 RE. The core field direction is found to differ only slightly from the results of the minimum variance analysis and the Grad-Shafranov technique. The maximum electric current density within the FTE was ∼100 nA/m2 and the total current was 0.3 MA, which is comparable with the current per RE flowing on the local magnetopause. The magnetic flux inside the FTE was ∼4 × 105 Wb. Magnetic field data and plasma data show that this FTE was fully embedded in the boundary region between the magnetosheath and the magnetosphere. The magnetic configuration and the flow distribution around the FTE suggest that X lines were present both ahead of and behind the FTE, but we cannot determine whether these X lines formed synchronously. Our observations favor the conclusion that multiple X line models are the candidate mechanisms for the generation of this FTE, and some of the FTE's features cannot be understood in the frame of any single X line FTE model.
Latent Representation Self-Supervised Pose Network for Accurate Monocular Pipe Pose Estimation

Accurate pipe pose estimation plays a pivotal role in the automatic assembly of pipelines. Recently, data-driven deep neural networks have been proven capable of estimating pose. Nonetheless, a large number of labeled datasets are required during the training process. One effective solution is to estimate pose using self-supervised learning. However, existing algorithms are difficult to deal with textureless objects (like pipes), and they avoid the occlusion problem. To this end, in this article, we propose a latent representation self-supervised pose network (LSPN) for accurate monocular pipe pose estimation. We train our network with synthetic RGB (Red, Green, Blue) data, where only a few labeled samples are used to establish the latent pose space, whereas a large number of structured unlabeled samples are used to learn latent pose representation in self-supervised learning. Experiments demonstrate that LSPN achieves excellent performance on real data and is robust to different environments, such as illumination changes and self-occlusion.
Developing supply chain resilience through integration: An empirical study on an e‐commerce platform

The outbreak of the COVID-19 pandemic has disrupted supply chains and increased the uncertainties faced by firms. While firms are struggling to survive and recover from the pandemic, Chinese e-commerce platforms have demonstrated resilient supply chains. We develop a framework that investigates the impacts of integration between an e-commerce platform and suppliers on supply chain resilience and the moderating effect of the suppliers' product flexibility. An analysis of data from a Chinese e-commerce platform using operational indicators finds that integration between the e-commerce platform and suppliers in terms of information sharing, joint planning and logistics cooperation has positive impacts on supply chain resilience, while procurement automation has the opposite effect. Furthermore, product flexibility positively moderates the impacts of information sharing, joint planning and logistics cooperation. The results enhance current understandings of the factors that contribute to the development of supply chain resilience and reveal that the relationship between integration and resilience should be examined within a contingency framework. The findings also provide guidelines for managers taking measures to mitigate the negative influences of supply chain disruptions. © 2022 Association for Supply Chain Management, Inc.
HEAT WATCH/WARNING SYSTEMS SAVE LIVES Estimated Costs and Benefits for Philadelphia 1995-98

Abstract The Philadelphia, Pennsylvania, Hot Weather–Health Watch/Warning System was initiated in 1995 to alert the city's population to take precautionary actions when hot weather posed risks to health. The number of lives saved and the economic benefit of this system were estimated using data from 1995 to 1998. Excess mortality in people 65 yr of age and older was defined as reported mortality minus mortality predicted by a historical trend line developed over the period of 1964–88. Excess mortality during heat waves was explained using multiple linear regression. Two variables were convincingly associated with mortality: the time of season when a particular heat wave started, and a warning variable indicating whether or not a heat wave warning had been issued. The estimated coefficient of the warning variable was about −2.6, suggesting that when a warning was issued, 2.6 lives were saved, on average, for each warning day and for 3 days after the warning ended. Given the number of warnings issued over t.
Invariant metrics of positive scalar curvature on $S^1$-manifolds

We prove existence results for invariant metrics of positive scalar curvature on certain non-semi-free $S^1$-manifolds. As a result after inverting two there is only one obstruction against such metrics on these manifolds. For free actions of even type on spin manifolds this obstruction coincides with the $\hat{A}$-genus of the orbit space of the action.