Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrafast anisotropic x-ray scattering in the condensed phase

The advent of x-ray free electron lasers offers new opportunities for x-ray scattering (XRS) studies of ultrafast molecular dynamics in liquids, which have so far been limited to the 100 ps resolution of synchrotrons. In particular, anisotropic XRS induced by photoselection, using a linearly polarized pump pulse, can enhance the contrast of the signal from excited molecules against the diffuse background and allows the probing of their vibrational and rotational dynamics. Here, we present a computational approach for calculating transient scattering intensities, based on molecular dynamics simulations. This is applied to the study of the excited state dynamics of molecular iodine dissolved in n-hexane. We report that at short times the transient XRS patterns reflect the evolving vibrational and rotational dynamics of I2, even when the disordered solvent environment is included. We then use these simulations to derive the anticipated signal-to-noise ratio for a large class of model diatomic systems in solution, indicating that an S/N ⩾1 will be possible from single-shot experiments in weakly scattering solvents.
Public Sentiment Analysis with Opinion Mining on Rohingya Refugee Crisis in Bangladesh

Twenty-first century, there has been moderate forced migration where it articulates human civilization. This forced migration is the identity of various territories and demography. According to this issue, Bangladesh is now the largest populated country for being stateless refugees in the world. The Rohingya community is hopeless about placing their lives, therefore, stateless refugees possessions in the southeastern border region of Bangladesh. Due to the part of Bangladesh addressing that stateless refugees and Bangladeshi peoples and other countries people have a tremendous debate on this issue. Tropically, according to these stateless refugees the victim of hate speech. This study aims to detect the daily report of negativity predicting actual analysis among machine learning approaches using hate speech features. Employed 5 classifiers like SVM, DT, KNN, RF, and NB. Necessary cleaning steps accommodate the model using preprocessing. NB shows the results outcome accuracy of 79% which is more than all other models. The approach of predicting hate speech on stateless refugees took 310 comments data which can rule as a global application.
Correlation of Delayed Onset Muscle Soreness and Inflammation Post-exercise Induced Muscle Damage

BACKGROUND: Delayed Onset Muscle Soreness (DOMS) is a common injury resulting from abnormal intensive training in athletes, mainly the result of training involving eccentric contractions. AIM: The aim of this study was to determine the correlation between the incidence of DOMS and HMGB1 as a marker of the occurrence of inflammation post Exercise Induces Muscle Damaged. METHOD: 28 male recreational students of Sports Science Department, Universitas Negeri Surabaya who met all inclusion and exclusion criteria participated in this study. Participants completed a muscle damaging exercise which consists of a 10x10 drop jump (DRP) and a bout of 40×15 m sprints with a 5 m deceleration zone (SPR) to obtain a muscle damage effect. In this study, the stretching in the exercise session was not given, this was done to get the DOMS effect after exercise. DOMS and HMGB1 was carry out 1 hour before the exercise, 12 hours after the exercise, 24 hours after the exercise and 48 hours after the exercise. RESULT: The result showed that there was a significant correlation (r=0.935, p<0.05) between DOMS and HMGB1 as a predictor of inflammation. The participants that were given EIMD eccentric exercise (DRP and SPR) showed the occurrence of DOMS and increasing of HMGB1. The result also showed that there was a correlation between DOMS and HMGB1. CONCLUSION: This study concluded that there was a correlation between DOMS and HMGB1 as a marker of inflammation as the result of the eccentric exercise of the exercise Induced Muscle Damage (EIMD).
On the optimal maintenance of systems and control of arrivals in queues

Consider a continuously operating system. A problem that arises in practice and is related to the optimal operation of the system is how to allocate limited repair resources in a most efficient manner, i.e., to maximize a measure of system performance. In this article our interest is in identifying classes of reliability systems (structures) such that optimal dynamic repair allocation policies depend on the structure only. A general structure of a system is that of a K-out-of-N system where component iis itself assumed to be a system . All suhsystenls have identical comporrents the lifetimes of which are assumed to be independent, exponentially distributed random variables. The system is maintained by a single repairman and the time it takes to repair a failed component is also an exponentially distributed random variable. Repaired components are as good as new and preemptions are allowed. Using several optimalit,y criteria, we characterize all stationary optinla1 policies for the following structures:the.
Prophet: Realizing a Predictable Real-time Perception Pipeline for Autonomous Vehicles

We have witnessed the broad adoption of Deep Neu-ral Networks (DNNs) in autonomous vehicles (AV). As a safety-critical system, deadline-based scheduling is used to guarantee the predictability of the AV system. However, non-negligible time variations exist for most DNN models in an AV system, even when the whole system is just running one model. The fact that multiple DNNs are running on the same platform makes the time variations issue even more severe. However, none of the existing works have thoroughly studied the root cause of the time variation issue. In the first part of the paper, we conducted a comprehensive empirical study. We found that the inference time variations for a single DNN model are mainly caused by the DNN's multi-stage/multi-branch structure, which has a dynamic number of proposals or raw points. In addition, we found that the uncoordinated contention and cooperation are the roots of the time variations for multi-tenant DNNs inference. Second, based on these insights, we proposed the Prophet system that addresses the time variations in the AV perception system in two steps. The first step is to predict the time variations based on the intermediate results like proposals and raw points. The second step is coordinating the multi-tenant DNNs to ensure the execution progress is close to each other. From the evaluation results on the KITTI dataset, the time prediction of a single model all achieve higher than 91% accuracy for Faster R-CNN, LaneNet, and PINet. Besides, the perception fusion delay is bounded to 150ms, and the fusion drop ratio is reduced from 5.4% to less than 1 percent.
Electrical bistability and negative differential resistance in single Sb-doped ZnO nanobelts/SiOx/p-Si heterostructured devices

We report the electrical bistability and negative differential resistance (NDR) in single Sb-doped ZnO nanobelts/SiOx/p-type Si heterostructured devices. The current-voltage (I-V) characteristics of the devices were discussed in terms of the energy band diagram of the devices. The origin of the electrical bistability and NDR is suggested to be associated with the electric-field-induced charge transfer. The performance of the fabricated devices can be enhanced under the ultraviolet light illumination.
Statistical theory of electromagnetic weak turbulence

The weak turbulence theory as commonly found in the literature employs electrostatic approximation and is applicable to unmagnetized plasmas only. To this date, fully electromagnetic generalization of the existing weak turbulence theory based upon statistical mechanical approach remains largely incomplete. Instead, electromagnetic effects are incorporated into the weak turbulence formalism by means of the semiclassical approach. The present paper reformulates the fully electromagnetic weak turbulence theory from classical statistical mechanical (i.e., the Klimontovich) approach.
Off-shell, maximal supersymmetry & exceptional geometry

Two lines of research are presented in this thesis, both with a focus on fundamental properties within the supersymmetric theories of high energy physics. The first features analyses based on the actions for maximal supersymmetric Yang–Mills theory and supergravity, provided by the pure spinor formalism. The second is the development of the theory of exceptional geometry. The analyses within maximally supersymmetric Yang–Mills theory and supergravity, benefitting from the pure spinor formalism, centres around the investigations of the UV divergences of the amplitude diagrams, where the case of maximal supergravity is subject to ongoing research. There is currently an interesting development in connection to the four-dimensional theory, regarding a possible finiteness, indicated in the pure spinor formalism setting of the research articles appended to this thesis. The results are contrary to the expected divergence, currently of amplitude diagrams with more than six loops. Exceptional geometry is an extension of supergravity that is constructed to incorporate U-duality. It is a geometric formulation with an extended space, in a way similar to in doubled geometry, where T-duality is the symmetry accommodated for. Constituting a rather recent area of research, the theory is under development with respect to the inherent symmetries, the tensor formalism, etc., regarding the properties affected by the extended space. Its recognised features, construction and concepts to be investigated are the objects of interest in this thesis.
The effect of microscopic turbulence on magnetosphere-ionosphere coupling

The effect of turbulence on the coupling of the magnetosphere and ionosphere has been investigated by including an effective collision frequency in the electron equation of motion. When this term is combined with the continuity equation, the ion equation of motion and Maxwell’s equations, a dispersion relation for the kinetic Alfven wave including effective collisions is found. The wave-particle interaction leads to a strong damping of the wave. Inclusion of the effects of plasma sheet kinetics yields a scale size transverse to the magnetic field which corresponds to the size of visual auroral arcs.
Mesh sharpening via normal filtering

We present a robust mesh sharpening approach to reconstructing sharp features from blended or chamfered features, even with noise and aliasing errors. Feature regions were first recognized via normal variation according to the user’s input, and then normal filtering was applied to faces of feature regions. Finally, the vertices of the feature region were gradually updated based on new face normals using a least-squares error criterion. Experimental results demonstrate that the method is effective and robust in sharpening meshes.
Minimal models in semantics and pragmatics : free choice, exhaustivity, and conditionals

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Physical properties of Hastelloy® C-276™ at cryogenic temperatures

In recent years, the Ni–Mo–Cr superalloy Hastelloy® C-276™ has been used as a substrate material for fabricating superconducting tapes such as YBCO and MgB2 coated conductors. With increasing piece length, these coated conductors are within reach of large scale commercial applications. However, data on the physical properties of Hastelloy C-276 at temperatures relevant for these applications are not yet available. In this work, physical properties including magnet succeptibility, specific heat, electrical resistivity, and the Seebeck coefficient are measured from 2to300K and thermal conductivity from 2to200K. Our results show that Hastelloy C-276 exhibits Curie paramagnetism between 4 and 300K with a Curie constant C=0.091K. A spin-glass-like behavior is observed below 3K. The electrical resistivity has a minimum at ∼12K, and shows a linear weak T dependence at higher temperatures. The specific heat Cp between 15 and 40K follows Cp=γT+AT3. Below ∼10K, an upturn in Cp∕T with decreasing T is interpreted by .
Decoupling and coefficient assignment for (A, B, C, D) time-delay systems

Using V as the time-delay operator, a linear invariant time-delay system is expressed by a quadruple (A(δ)), B(δ) C(V) D(V)) with the matrices over a polynomial ring in V. This paper studies the decoupling and coefficient assignment of such a system. For a class of time-delay systems non-controllable over the polynomial ring in V but controllable over the field of rational functions in V, we present sufficient conditions under which the system characteristic polynomial may be determined arbitrarily by feasible control laws. Two examples are investigated to illustrate the theory.
A clustering algorithm for machine cell formation in group technology using minimum spanning trees

Abstract I address the machine cell part family formation problem in group technology. The minimum spanning tree (MST) For machines is constructed from which seeds to cluster components are generated. Seeds to cluster machines are obtained from component clusters. The process of alternate seed generation and clustering is continued until feasible solutions are obtained. Edges are removed from the MST to identify alternate starting seeds for clustering. The algorithm is tested with matrices available in the literature. The results compare favourably with existing methods.
Hubble Space Telescope Space Telescope Imaging Spectrograph Observations of the Bipolar Jet from RW Aurigae: Tracing Outflow Asymmetries Close to the Source

We have observed the bipolar jet from RW Aur A with STIS on board the Hubble Space Telescope. After continuum subtraction, morphological and kinematic properties of this outflow can be traced to within 0. ″1 from the source in forbidden emission lines. The jet appears well collimated, with typical FWHMs of 20-30 AU in the first 2'' and, surprisingly, does not show a separate low-velocity component, in contrast to earlier observations. The systemic radial outflow velocity of the blueshifted lobe is typically 50% larger than that of the redshifted one with a velocity difference of about 65 km s-1. Although such asymmetries have been seen before on larger scales, our high spatial resolution observations suggest that they are intrinsic to the "central engine" rather than effects of the star's immediate environment. Temporal variations of the bipolar jet's outflow velocities appear to occur on timescales of a few years. They have combined to produce a 55% increase in the velocity asymmetry between the two lobes over the past decade. In the red lobe, estimated mass flux (j) and momentum flux (j) values are around one-half and one-third of those for the blue lobe, respectively. The mass outflow to mass accretion rate is 0.05, the former being measured at a distance of 0. ″35 from the source.
Complementary chiral metamaterials with giant optical activity and negative refractive index

A complementary bilayer cross-wire chiral metamaterial is proposed and studied experimentally and numerically. It exhibits giant optical activity and a small circular dichroism. The retrieval results reveal that a negative refractive index is realized for right circularly polarized waves due to the strong chirality. Our numerical results show that the mechanism of the chiral behavior at the resonance of lower frequency can be interpreted as the coupling effects between two sets of mutually twisted virtual magnetic dipoles, while the resonance of higher frequency shows complicated nonlocal features.
Model uncertainty, data mining and statistical inference

This paper takes a broad, pragmatic view of statistical inference to include all aspects of model formulation. The estimation of model parameters traditionally assumes that a model has a prespecified known form and takes no account of possible uncertainty regarding the model structure. This implicitly assumes the existence of a 'true' model, which many would regard as a fiction. In practice model uncertainty is a fact of life and likely to be more serious than other sources of uncertainty which have received far more attention from statisticians. This is true whether the model is specified on subject-matter grounds or, as is increasingly the case, when a model is formulated, fitted and checked on the same data set in an iterative, interactive way. Modern computing power allows a large number of models to be considered and data-dependent specification searches have become the norm in many areas of statistics. The term data mining may be used in this context when the analyst goes to great lengths to obtain a good fit. This paper reviews the effects of model uncertainty, such as too narrow prediction intervals, and the non-trivial biases in parameter estimates which can follow data-based modelling. Ways of assessing and overcoming the effects of model uncertainty are discussed, including the use of simulation and resampling methods, a Bayesian model averaging approach and collecting additional data wherever possible. Perhaps the main aim of the paper is to ensure that statisticians are aware of the problems and start addressing the issues even if there is no simple, general theoretical fix.
A high galactic latitude pulsar survey of the Arecibo sky

The results of a 1355 square degree survey of high galactic latitudes conducted from 1990 to 1995 with the Arecibo radio telescope are presented. The majority of the survey was performed at 430 MHz with a 32 channel 250 kHz lter-bank sampled at 4 kHz. A 7 sensitivity of 1 mJy was obtained for pulsars with periods down to 3 ms. This survey yielded 5 millisecond or recycled pulsars and 14 slow period pulsars. In addition, one millisecond pulsar and 4 slow period pulsar candidates have been identiied, but are as yet unconnrmed. One of the new slow period pulsars appears to be associated with the supernova remnant S147 located towards the galactic anti-center.
A cosmic virial theorem

A new type of cosmic virial theorem is derived, representing a relation among the two-point and three-point galaxy correlation functions and the mean square relative peculiar velocity 〈v2(r)〉 averaged over pairs of galaxies separated by distancer. The two correlation functions seem to be fairly well known, but 〈v2(r)〉 at best is only very roughly estimated from available data. It might be possible to improve the estimate through a systematic program of redshift measurements in sample areas. If so, the cosmic virial theorem might yield an interesting measure of the mean mass density due to galaxies.
A Bayesian Inference and Stochastic Dynamic Programming Approach to Determine the Best Binomial Distribution

In this research, we employ Bayesian inference and stochastic dynamic programming approaches to select the binomial population with the largest probability of success from n independent Bernoulli populations based upon the sample information. To do this, we first define a probability measure called belief for the event of selecting the best population. Second, we explain the way to model the selection problem using Bayesian inference. Third, we clarify the model by which we improve the beliefs and prove that it converges to select the best population. In this iterative approach, we update the beliefs by taking new observations on the populations under study. This is performed using Bayesian rule and prior beliefs. Fourth, we model the problem of making the decision in a predetermined number of decision stages using the stochastic dynamic programming approach. Finally, in order to understand and to evaluate the proposed methodology, we provide two numerical examples and a comparison study by simulation. The results of the comparison study show that the proposed method performs better than that of Levin and Robbins (1981) for some values of estimated probability of making a correct selection.
A search for shock-excited molecular hydrogen knots in Chamaeleon I very low mass YSOs

We have obtained narrow-band images of three selected areas of the Chamaeleon I dark cloud which harbor very low mass young stars, centered on the H 2 and Br γ lines and neighboring continuum as well as on the broad band K s . One region is located in the northern part of the cloud, roughly coinciding with the densest area. The other two regions are in the southern section of the cloud. Our aim is to search for H 2 outflows associated with these objects. In the northern region, we found seven new H 2 knots, five of which are aligned in the direction of a previously known 12 CO molecular bipolar outflow. Further evidence that the class I low mass stellar object ISO-ChaI 192 is the driving source of the molecular flow is given by the presence of a 960 AU long elongated structure at 2.2 μ m emanating from this star and oriented parallel to the bipolar structure. Another pair of H 2 knots, although lying relatively nearby, is not aligned with the outflow direction. They are located on opposite sides of C1–6, a low mass class II object in the northern part of the Chamaeleon I dark cloud. In contrast, we fail to detect any H 2 emission object brighter than our sensitivity limit (~$6 \times 10^{-32}$ W/m 2 Hz arcsec 2 ) in the two southern areas of the cloud that also harbor several very low mass stars, including two transition stellar/sub-stellar objects. This negative result is probably not surprising in view of the extremely low accretion rates measured for brown dwarfs ($\dot{M} \sim 10^{-12} {-}10^{-9} ~ M_{\odot}$ yr -1 ). Deeper H 2 observations are required to better constraint the outflow event in sub-stellar objects.