Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectroscopic and laser properties of Nd/sup 3+/ in BIGaZLuTMn fluoride glass

The optical properties of Nd/sup 3+/-doped fluoride BIGaZLuTMn glass have been investigated by using steady-state and time-resolved laser spectroscopy. Laser action has been obtained for the first time in this glass by flashlamp pumping. The influence of site-dependent effects on fluorescence lifetime and time-resolved stimulated emission has been proved. >
Comparing the spatial content of thematic maps

Measures of categorical association can be used to assess the degree of similarity between two thematic maps, having regard to the spatial distribution of map classes but not to the identity of the classes. Such measures can be used, for example, to compare maps that use different classification schemes, or to identify misregistration between maps. The theory of these measures and their relationship to measures of categorical agreement are discussed. Three representative measures of categorical association are investigated quantitatively using various categorical maps, including maps generated by classification of satellite images, of a study area in the Russian north. On the basis of this investigation, it is suggested that Cramér's V statistic provides a simple but effective measure of the similarity in the spatial content of maps.
Three-Dimensional Bioconjugated Liquid-Like Solid (LLS) Enhance Characterization of Solid Tumor - Chimeric Antigen Receptor T cell interactions

Cancer immunotherapy offers lifesaving treatments for cancers, but the lack of reliable preclinical models that could enable the mechanistic studies of tumor-immune interactions hampers the identification of new therapeutic strategies. We hypothesized 3D confined microchannels, formed by interstitial space between bio-conjugated liquid-like solids (LLS), enable CAR T dynamic locomotion within an immunosuppressive TME to carry out anti-tumor function. Murine CD70-specific CAR T cells cocultured with the CD70-expressing glioblastoma and osteosarcoma demonstrated efficient trafficking, infiltration, and killing of cancer cells. The anti-tumor activity was clearly captured via longterm in situ imaging and supported by upregulation of cytokines and chemokines including IFNg, CXCL9, CXCL10, CCL2, CCL3, and CCL4. Interestingly, target cancer cells, upon an immune attack, initiated an “immune escape” response by frantically invading the surrounding microenvironment. This phenomenon however was not observed for the wild-type tumor samples which remained intact and produced no relevant cytokine response. Single cells collection and transcriptomic profiling of CAR T cells at regions of interest revealed feasibility of identifying differential gene expression amongst the immune subpopulations. Complimentary 3D in vitro platforms are necessary to uncover cancer immune biology mechanisms, as emphasized by the significant roles of the TME and its heterogeneity.
DIFFERENTIAL EQUATIONS FOR CUBIC THETA FUNCTIONS

We show that the cubic theta functions satisfy two distinct coupled systems of nonlinear differential equations. The resulting relations are analogous to Ramanujan's differential equations for Eisenstein series on the full modular group. We deduce the cubic analogs presented here from trigonometric series identities arising in Ramanujan's original paper on Eisenstein series. Several consequences of these differential equations are established, including a short proof of a famous cubic theta function identity derived by J. M. Borwein and P. B. Borwein.
Uniform approximation for bifurcations of periodic orbits with high repetition numbers

The semiclassical contribution of a periodic orbit to the quantum density of states diverges when the orbit bifurcates. In this case one has to apply approximations which are uniformly valid both in and a parameter which describes the distance to the bifurcation. The form of the approximation depends on the repetition number m of the orbit that bifurcates. In a two-dimensional system, the approximations are different for m = 1 up to m = 5, and for they have the same form as for m = 5. In this article, we consider the case which occurs first when an integrable system is perturbed. A uniform approximation for the contribution to the spectral density is derived, which in the limit of large reduces to a sum of semiclassical contributions of isolated periodic orbits.
Multi-label Classification using BERT and Knowledge Graphs with a Limited Training Dataset

This paper provides a new approach combining BERT and Knowledge Graphs (KGs) to solve a multi-label classification problem with limited training data. The paper introduces a method of using taxonomies and a dataset with 518 entries and 340 concepts to fine-tune BERT. It also introduces a new data augmentation technique called Perfect Binary Tree (PBT)-Flow to deal with limited or imbalanced training data. The proposed approach obtained a recall@10 of 61.12%, a precision@10 of 11.86% and F1score@10 of 18.83%. While these results seem low, they are promising because of the simple architecture of the model used (BERT+2xFC), the limited size of the training data, and the large number of output concepts.
Comments on "An improved approximation for settling time of second-order linear systems"

The paper is based on the assertion that the formula for the settling time of linear underdamped second-order systems, using the exponential envelope of the response, is unconservative. This is incorrect: the envelope formula yields an upper bound on the settling time. We also show how the envelope formula can be approximated by a truncated McLaurin series, yielding a practical design formula that is consistent with current formulas, and more general than the one proposed by Bert.
Classification of visible point sources using hyperspectral chromotomosynthetic imagery

Abstract. A hyperspectral chromotomosynthetic imaging (CTI) system is used to detect and classify a collection of 21 scattered, spectrally diverse point-like sources. The instrument operates in the visible to near IR (400 to 800 nm) and has the potential to collect spectral imagery at great than 10 Hz. A two-dimensional wideband spatial image of the target scene is used to detect and spatially characterize the targets leading to optimization of the three-dimensional (3-D) spatial/spectral reconstruction of the hyperspectral image cube. The instrument is assessed by directly comparing results to spatial data collected by a wideband image and hyperspectral data collected using a liquid crystal tunable filter (LCTF). Target classification using k -means clustering of observed spectra yielded 5 to 6 target classes for each methodology, indicating information obtained using CTI was similar to that collected by the LCTF. The wide-band spatial content of the scene reconstructed from the CTI data is of same or better quality in terms of background noise and target intensities as a single frame collected by the undispersed imaging system with projections taken at every 1 deg. Performance is dependent on the number of projections used, with projections at 5 deg producing adequate results in terms of target characterization. The CTI has 2 to 4 times the spectral resolution of the LCTF. The data collected by the CTI system can simultaneously provide spatial information of equal quality as a the bandpass imaging system, provide high-frame rate slitless one-dimensional spectra, and generate 3-D hyperspectral imagery which can be exploited to provide the same results as a traditional multiband spectral imaging system.
Regression Analysis in Sample Surveys

Abstract Models are proposed as a basis for unbiased and biased estimation from sample survey data of a regression relation. Unbiased estimates of the variances and covariances of estimates of the regression coefficients are obtained for certain cases but do not appear to exist for all cases. It is suggested that past surveys, conducted mostly to obtain efficiently estimates of means and totals, be analyzed to yield estimates of regression relations, to obtain information needed in designing future surveys, and to test the adequacy of the proposed models.
Texture classification system using colour space fusion

A novel colour texture classification system is presented based on an ensemble of independent classifiers each assigned to a different colour representation model. Gaussian Markov random fields features are used in a study to illustrate this previously unexplored approach and its potential to combine information from different colour spaces to improve accuracy. Experimental results illustrate that colour space information fusion results in significant improvements in accuracy.
Fostering a Lively and Tenacious Web of Data

While the Web of Data continues to mature, it can still suffer from inertia (being slow to change) and impermanence (losing track of the past). Addressing these two flaws in a meaningful way requires additional work to better understand and harness dynamics on the Web of Data, not only in terms of data, but also in terms of queries, links, websites, definitions, demands, etc. In this paper, we highlight key challenges relating to dynamics on the Web of Data. We outline issues for the Web of Data that may arise if such challenges are left neglected: stale or forgotten data, incorrect results, unchecked vandalism, biased conclusions, etc. We discuss research lines to address such challenges relating to representations, modelling, prediction, etc. Within these research lines we identify key trade-offs, a better understanding of which may help us to transition towards a more lively and tenacious Web of Data that is better equipped to serve a changing world.
Pressure‐enhanced solid phase epitaxy of germanium

We have measured the effect of pressure on the solid phase epitaxial growth rate of Ge(100) into self‐implanted amorphous Ge by using in situ time‐resolved infrared interferometry in a high‐temperature, high‐pressure diamond anvil cell. In the temperature range 300–365 °C, a rate enhancement of more than a factor of 100 over that at ambient pressure has been observed due to hydrostatic pressures of up to 5.2 GPa (52 kbar). The pressure enhancement is characterized by a negative activation volume of −6.2±0.6 cm3/mol (−45% of the atomic volume), which is of the same sign but greater in magnitude than we found in Si. We conclude that the defects controlling the solid phase epitaxy of Ge cannot be vacancies in the crystal, that mechanisms based on other point defects migrating to the interface from either phase are unlikely, and that mechanisms based on point defects residing in the interface are plausible.
Kinetic equations for low frequency instabilities in inhomogeneous plasmas

Kinetic equations for low frequency, short perpendicular wavelength, electromagnetic perturbations in an inhomogeneous, magnetically confined plasma are developed. The analysis makes use of the recently developed high toroidal mode number expansion to reduce the lowest‐order system of equations to a set of ordinary (along the field line) integro‐differential equations. Included in these equations are the effects of finite Larmor radius, magnetic shear, trapped particles, and nonuniform magnetic curvature drifts. Perturbed fields are represented by a scalar potential and two components of the vector potential. Thus, the effects of the compressional component of the perturbed magnetic field are retained and the equations are valid for arbitrary values of the plasma pressure. The extension of the high toroidal mode number expansion to nonaxisymmetric configurations is discussed.
Entropy Generation in a Heat Exchanger

The entropy generation (irreversibility) concept founded on the second law of thermodynamics may be applied in heat exchanger analysis. In this paper the quantity termed enthalpy exchange irreversibility norm (EEIN) is the measure of the internal heat exchanger irreversibilities. The behavior of EEIN as a function of the heat exchanger thermal size is discussed for an arbitrary flow arrangement and more precisely for two characteristic limiting cases: cocurrent and countercurrent heat exchangers.
Convergence properties of infinitesimal perturbation analysis

Infinitesimal Perturbation Analysis IPA is a method for computing a sample path derivative with respect to an input parameter in a discrete event simulation. The IPA algorithm is based on the fact that for certain parameters and any realization of a simulation, the change in parameter can be made small enough so that only the times of events get shifted, but their order does not change. This paper considers the convergence properties of the IPA sample path derivatives. In particular, the question of when an IPA estimate converges to the derivative of a steady state performance measure is studied. Necessary and sufficient conditions for this convergence are derived for a class of regenerative processes. Although these conditions are not guaranteed to be satisfied in general, they are satisfied for the mean stationary response time in the M/G/1 queue. A necessary condition for multiple IPA estimates to simultaneously converge to the derivatives of steady state throughputs in a queueing network is determined. The implications of this necessary condition are that, except in special cases, the original IPA algorithm cannot be used to consistently estimate steady state throughput derivatives in queueing networks with multiple types of customers, state-dependent routing or blocking. Numerical studies on IPA convergence properties are also presented.
Effects of a Decaying Cosmological Term on the Formation of Molecules and First Objects

We investigate formation of molecules and first objects in a model with a decaying cosmological term (DCT). In particular, we show how the formation of important molecules such as H2 and HD is influenced during the epoch of the redshift z from 104 to 1. We find that for a phenomenological DCT molecular formation is significantly shifted to the earlier epoch by Δz ~ 103 compared to the case in the standard big bang cosmology, as a result of the rapid decrease in the matter temperature. The mass of first objects is estimated using the timescales relevant to their formation. We suggest that the formation scenarios of the objects studied so far could be revised if a DCT is taken into account.
Conjoint measurement approach for machine-part grouping in manufacturing cell formation

In order to measure the joint effects of a set of independent variables on the ordering of a dependent variable, conjoint measurement is used. In this paper the underlying principle is applied to clustering machine-part for cellular manufacturing. Assuming machines (parts) as products and parts (machines) as attributes of the products and elements of the incidence matrix as levels of attributes, the utilities of the machine (parts) have been calculated. The method is found to produce consistently good results when applied to a wide range of problems reported in literature.
Flow visualization of Dean vortices in a curved channel with 40 to 1 aspect ratio

Results from a flow visualization study of Dean vortex flow are presented. These were obtained over a range of Dean numbers from 40 to 220 using a transparent channel with mild curvature, an aspect ratio of 40 to 1, and an inner to outer radius ratio of 0.979. Observations and photographs show evidence of pairs of counter‐rotating Dean vortices indicated by mushroom‐shaped smoke patterns for Dean numbers greater than 64 and angular positions at least 85° from the start of curvature. Photographs showing nonsymmetric Dean vortices with rocking motion are presented and believed to be evidence of a twisting mode of oscillations. Dean vortices with oscillations mostly in the radial direction are also observed, which are believed to strongly depend on the small amplitude disturbances that trigger initial vortex development. Photographic evidence of small secondary vortex pairs, and vortices with simultaneous radial and spanwise oscillations are also given along with a domain map showing the experimental conditi.
Bulk polymerization of ε-caprolactone: Rheological predictive laws

The rheological behavior during bulk polymerization of e-caprolactone with titanium tetrapropoxide as the initiator was studied in connection with the kinetics of the reaction (conversion rate and molecular weight variations). The viscoelastic properties of the melt polycaprolactone performed by this reactive system was predicted reasonably well using phenomenological models such as the Yasuda–Carreau or relaxation spectrum models and a molecular dynamic model based on a blending law of the relaxation function. The evolution of these viscoelastic properties during bulk polymerization was calculated by combining these viscoelastic models with the kinetic laws of the system. By taking into account the dilution effect caused by the presence of a monomer, a global rheological predictive model was then achieved. It was shown to give a reasonably good depiction of the viscoelastic properties [‖η*(t)‖, G′(t) and G″(t)] whatever the processing conditions (temperature, frequency, initiator concentration, etc.) are.
Mobile Edge NLU with On-device Inference for Humanitarian Assistance during Disasters

Natural language understanding (NLU) models allow computers to help disaster response teams in understanding requests spoken in different languages. Multilingual assistants can automatically translate messages spoken in a detected language into a language understood by the NLU model, prior to translating the extracted information back to the response team. The success of humanitarian assistance during disasters depends largely on the performance and dependability of the assistants, especially in a resource-limited situation. Recent works have successfully pushed natural language computation to special-purpose AI edge nodes, the computing devices located at the edge of a network, to achieving availability and resilience to network loss. However, limited works have offloaded the natural language workload to process on mobile devices and quantify the resource requirement.Thus, this work proposed a use case of mobile devices connected as an NLU edge computing node for understanding disaster response messages. Its resource requirement has been measured based on a transformer-based Thai-English translation model. The results show that the model achieve an acceptable performance in language translation and classification of needed humanitarian supplies. Moreover, using the cloud AI-as-a-Service, we could extract key essences of the disaster response messages in acceptable response time.
Transition Radius from Cooling-Dominated to Advection-Dominated Regimes in Two Temperature Disks

Optically thin advection-dominated flows are known to be unable to extend outward beyond a certain critical (transition) radius in disk accretion. Outside of the radius, the disks are cooling-dominated. The advection-dominated self-similar steady flows cannot join thermally to the cooling-dominated steady standard disks, unless there is some external heating at the transition zone. We examine, under the condition of no such heating, the radius rtr of the transition analytically when the advection-dominated inner flows are two-temperature ones. The results are almost the same as those obtained by Honma (1996, AAA 65.067.241) to a one-temperature disk: i.e., rtT/rs ~ 5.5 x 10 (a/m), where a is the viscosity parameter and m is the mass accretion rate normalized by the critical accretion rate defined by the Eddington luminosity. This coincidence with the one-temperature case comes from the fact that the transition occurs after the ion temperature in the advection-dominated region decreases sharply outwards.
Comparative Study of Linbo3 and ALN Based Saw Temperature Devices

Wireless and real-time monitoring are in great demand for harsh environments or cases that are difficult or dangerous to use wire-connected monitoring. In this work, we present a comparative study of SAW devices for wireless temperature monitoring. The operating frequency and sensitivity have been investigated based on two kinds of SAW devices, which are fabricated using LiNbO3 crystal and Aluminum Nitride (AlN) thin film on silicon substrate, respectively. In order to predict the temperature behavior of devices, simulations based on the two-dimensional finite element method (2D-FEM) model are performed in COMSOL. Temperature measurement experiments characterized devices in a temperature range from room temperature to 200°C. The temperature coefficient of frequency (TCF) values of LiNbO3 and AlN devices are measured as -137.33ppm/°C and -31.14ppm/°C. The resonance frequency variation with temperature shows a good linearity.
Disturbance-Observer-Based Second-Order Sliding Mode Controller for Speed Control of PMSM Drives

This paper explicitly proposes a novel second-order sliding mode (SOSM) controller based on disturbance observer (DOB) to optimize the disturbance rejection property of the permanent magnet synchronous motor (PMSM) system. Firstly, to tackle the inevitable chattering problem in conventional first-order sliding mode controllers, a new type of SOSM control technique is designed for the speed loop of PMSM system by retaining the discontinuous switching function in the derivative of the actual controller. The proposed controller can not only provide the strong anti-disturbance performance, but also significantly attenuate the potential chattering problem. Then, a DOB constructed based on the auxiliary system is further adopted to compensate the adverse effect generated by the disturbance to enhance dynamical performance. Finally, comprehensive experimental results are provided to verify the effectiveness of the proposed method.
Mobile Networks Classification Based on Time-Series Clustering

With the increasing complexity of network architecture, the classification of mobile network cells become more important in network operation and maintenance. However, the previous classification method based on manual annotation of scene labeling is inefficient and biased. In this paper, we focus on proposing a data-driven classification method to eliminate the drawbacks of manual annotation. The proposed method extracts the patterns of mobile network on temporal shape and statistical features, and then calculates the fused distance matrix from these two feature sets, K-medoids is leveraged to get the classification labels. We design a series of experiments and analyses to demonstrate the validity of the proposed method, which is based on hourly real data sampled from 9454 mobile cells. The experiments demonstrate that the proposed method achieves good performance on the cell classification of two O&M (Operations and Maintenance) scenarios, and significantly improves the work efficiency.
Investigation on MLP, CNNs and Vision Transformer models performance for Extracting a Human Emotions via Facial Expressions

One of the difficult challenges in AI development is to make machine understand the human feeling through expression because human can express feeling in various ways, for example, through voices, facial actions or behaviors. Facial Emotion Recognition (FER) has been used in interrogating suspects and being a tool to help detect emotions in people with nerve damage or even in the COVID-19 pandemic when patients hide their timelines. It can be applied to detect lies through micro expression. In this work will mainly focus on FER. The results of Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Vision Transformer were compared. Human emotion expressions were classified by using facial expression datasets from AffectNet, Tsinghua, Extended Cohn Kanade (CK+), Karolinska Directed Emotional Faces (KDEF) and Real-world Affective Faces (RAF). Finally, all models were evaluated on the testing dataset to confirm their performance. The result shows that Vision Transformer model outperforms other models.