Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-spectral solar telescope array V; Temperature diagnostic response to the optically thin solar plasma

The authors have developed compact soft x-ray, extreme ultraviolet (EUV), and far-ultraviolet (FUV) multilayer coated telescopes for the study of the solar chromosphere, corona, and corona/solar wind interface. Because these systems operate at short wavelengths ({approximately}40 {angstrom} {lt} {lambda} {lt} 1550 {angstrom}), the modest apertures of 40 to 127 mm allow observations at very high angular resolution (0.1 to 0.7 arcsec). In addition to permitting traditional normal incidence optical configurations to be used at soft x-ray/EUV wavelengths, multilayer coatings also allow a narrow wavelength band ({lambda}/{Delta}{lambda} {approximately} 15 {minus}100) to be selected for imaging. The resulting telescopes provide a very powerful and flexible diagnostic instrument for the study of both the fine-scale structure of the chromosphere/corona interface and the large-scale structure of the corona and corona/solar wind interface. In previous papers, the authors have described a new solar rocket payload, the Multi-spectral Solar Telescope Array (MSSTA), which is composed of 17 of these compact telescopes. In this paper, the authors report on the ability of the MSSTA payload to obtain temperature diagnostic information about the optically thin solar plasma. The authors also discuss applications of this information to studies of coronal structure.
Fabrication of Multiple Fill Tube Targets for Sandia National Laboratory

Abstract Target design for the National Ignition Facility requires either a glass or polyimide (PI) fill tube. To study the hydrodynamic effects that are introduced by a fill tube during capsule implosion, fill tube targets were fabricated for experiments at the Z-Pinch facility. Three and four fill tube targets were designed and fabricated to maximize data during each experiment. Targets were made with PI and glass fill tubes on the same capsule to study the shadowing differences between glass and plastic fill tubes. Four tube targets were fabricated with diameters ranging from 10-45 μm to study the effect diameter has on implosion characteristics. Capsules were coated with a germanium-doped layer of glow discharge polymer. Blind holes were drilled in the capsules using an excimer laser. Fill tubes were fabricated using modified capillary pullers and assembly was done on a specially designed assembly station designed for fill tube fabrication. Targets were characterized by optical microscopy and by micron resolution x-ray tomography.
Properties of Lead-Free Piezoceramics Based on Alkali Niobates

The market for piezoceramic components is dominated by lead zirconate titanate (PZT) materials containing more than 60 wt% lead. Since lead is a toxic heavy metal, it has become a great concern how to eliminate the use of PZT by replacing it by non-harmful materials while maintaining comparable piezoelectric properties. This was the objective of the European LEAF project within the GROWTH programme, ending in February 2004. In this project, alkali niobates were proposed as alternative piezoceramic materials, and special emphasis was given to potassium sodium niobate, (K,Na)NbO 3 . Among the interesting properties of this system is a low theoretical density, leading to a relatively low acoustic impedance of 24 MRa. The partners of the project have developed lead-free ceramics based on potassium sodium niobate that can be a competitive alternative to PZT for certain applications. A selection of obtained properties, examples of industrial applications and an overview of end-user considerations will be presented. Furthermore, some considerations on the origin of even harmonics in the impedance spectrum, as seen in certain KNN ceramics will be given.
Search for supersymmetry at the Tevatron using the trilepton signature

This dissertation describes a search for the associated production of the supersymmetric particles, the chargino and the neutralino, through their R-parity conserving decays to three leptons and missing energy. This search is carried out using the data collected at the CDF experiment at the Tevatron {radical}s = 1.96 TeV p{bar p} collider at Fermilab. The results are obtained by combining five independent channels with varying signal to background ratio. Overall, a total of 6.4 {+-} 1.1 background events from standard model processes and 11.4 {+-} 1.1 signal events for a particular choice of mSUGRA model parameters are expected. The observation of 7 events in data is consistent with the standard model background expectation, and the mSUGRA model is constrained. Limits are set on the cross section of Chargino-Neutralino pair production, and a limit on the mass of the chargino is extracted. A method of obtaining model-independent results is also discussed.
Existence of periodic orbits in grazing bifurcations of impacting mechanical oscillators

Grazing bifurcations are local bifurcations that can occur in dynamical models of impacting mechanical systems. The motion resulting from a grazing bifurcation can be complex. In this paper we discuss the creation of periodic orbits associated with grazing bifurcations, and we give sufficient conditions for the existence of a such a family of orbits. We also give a numerical example for an impacting system with one degree of freedom.
SKELETAL CLASS III UPPER BILATERAL CANINE ECTOPIA AND NANIC LATERAL INCISORS – A CAMOUFLAGE APPROACH

Skeletal class III patients, especially adults, are best treated by orthognathic surgery and orthodontic treatment; when adding anunfavorable factor such as upper nanic incisors, the treatment difficulty increases. In this particular case, the patient and both his parentsrejected the orthognathic surgery, their main concern being the crowding of the teeth and not the physical appearance of the facialprofile. Based on the skeletal measurements, the orthodontic treatment goals were: align both arches, retrude lower arch, stabilizationof occlusion. MBT classic brackets were bonded aiming for closure of spaces in the lower arch and retrusion of lower incisors. Afterthe active treatment, 16 months, essix retainers were given to wear 12/24. The patient was instructed to be aware of any change in hisocclusion and call the clinic for any small tooth movement immediately.
A new strategy for cellulases application in high temperature industrial scenarios with syringic acid assisting

In the process of bioethanol production, more stable and active cellulase in high temperature condition is required. In this study, syringic acid was applied in cellulase hydrolysis system. At 70°C, TvEG3 activity increased 201.36%, CtBglA activity decreased 72.79% by syringic acid. With syringic acid assisting, TvEG3 thermostability was improved, CtBglA thermostability was reduced. Syringic acid scarcely affected CtCBH. In hydrolysis system with the cellulases containing TvEG3, CtCBH, and CtBglA, the reducing sugar yield improved by 28.37% with syringic acid assisting. With the molecular dynamic simulation in syringic acid system, the backbone root‐mean‐square deviation (RMSD) and the residue root‐mean‐square fluctuation (RMSF) of TvEG3, CtCBH reduced, while the RMSD and RMSF of CtBglA increased. The reduction in the number of secondary structures, especially α‐helix, caused the structure of CtBglA in the presence of syringic acid to collapse at high temperature. More secondary structures in TvEG3 and more α‐helix in CtCBH in the presence of syringic acid make them more stable at high temperatures. These means syringic acid can stabilize TvEG3 and CtCBH structure, destabilize CtBglA structure at high temperature. In summary, this study not only provides insight into cellulase hydrolysis at high temperature with syringic acid assisting but also demonstrates the promoting mechanism of syringic acid.
Novel Applications of Distributed Temperature Measurements to Estimate Zonal Flow Rate and Pressure in Offshore Gas Wells

Distributed Temperature Sensor (DTS) technology has recently developed to determine the zonal flow rate in gas/oil producing wells using the measured continuous temperature profile along the wellbore. Comapred to convenetial production logging tool (PLT), DTS has many advantages that can provide real time temperature data without any intervention. Temperature logging applications described in early researches included, location of gas entries, detection of casing leaks and fluid movement behind casing, location of lost – circulation zones, and evaluation of cement placement. Temperature logs are still used for these applications and others, but the most common use now is quanitative identification of injection or production zones. Despite the many other logs that have been developed, the temperature log remains the workhorse of the production logging stable. This is primarily because of its reliability; no matter what the wellbore flow conditions, temperature can be measured accurately, also the temperature logs tends to reflect the long term behavior of well, not just the current conditions. This paper presents a new methodology developed to allocate gas rate and associated water of each individual layer using (DTS) and the total surface production of gas and water, also the pressure along the wellbore. The physics behind this model is based on steady-state gas-water flow in the wellbore, friction loss and Joule-Thomson effect in the wellbore, contrast in the thermal and physical properties of gas and water, wellbore heat losses due to unsteady heat conduction in the earth, and the mixing of the fluid streams of contrasting temperature. The methodology allows users to run in two modes: forward simulation and flow profiling. The forward simulation mode calculates the temperature inside the wellbore at all producing layers at any given production profile to calibrate the model inputs. The flow profiling is used to estimate the production rate based on the measured temperatures using inversion technique. The implementation of the developed production allocation model is shown, in details, by using the data of two actual cases studies form Egyption offshore gaswells.
Yield and Profitability of Sweet Potato (Ipomoea batatas (L.) Lam) as a Function of Increasing Levels of Phosphorus and Varieties in Southern Ethiopia

Sweet potato is among the most important food security crops in Ethiopia. However, its productivity is constrained by poor soil fertility and a lack of improved varieties. A field experiment was conducted to evaluate the growth and yield response and profitability of three sweet potato varieties to rates of phosphorus (P) in Southern Ethiopia. Five rates of P (0, 10, 20, 30, and 40 kg ha−1) and three sweet potato varieties (Awassa-83, Kulfo, and Local) were considered as treatments that were laid out in a randomized complete block design with three replications. The vine length, internodes length, diameter, and the number of vines were significantly varied among varieties while P had a nonsignificant effect on these parameters. The tuber yield of sweet potato was influenced by the combined effect of variety and P rate. The highest marketable yield (30.22 t ha−1) was obtained at 30 kg P ha−1 from variety Awassa-83 and the lowest marketable yield (6.57 t ha−1) was obtained from Kulfo at 0 kg P ha−1. Thus, improvement of sweet potato productivity in the study area could be achieved through the use of Awassa-83 variety with P at a rate of 10 kg ha−1.
Pre-extracting boundary vectors for support vector machine using pseudo-density estimation method

Support vector machines (SVMs) have become useful and universal learning machines. SVMs construct a decision function by support vectors (SVs) and their corresponding weights. The training phase of SVMs definitely uses all training samples, which leads to a large computational complexity for a large scale sample set. Moreover support vectors could not be found until a quadratic programming (QP) problem is solved. Actually we know only SVs play a role in the decision function. Hence, pseudo density estimation (PDE) is presented to extract a set of boundary vectors (BVs) which may contain SVs. The PDE method is a variant of Parzen window method. Hyperspheres are considered as the window functions. In our method, for each sample we construct a hypersphere with an unfixed radius. The ratio of the number of samples contained in the hypersphere of a sample to the total training samples can be taken as the pseudo density of the corresponding sample. The set of BVs is taken as the training input to SVMs. In doing so, it speeds the training procedure of SVMs. It is convenient for PDE to determine its parameter. The experiments show that SVMs using PDE have the similar generalization performance to SVMs.
Incomplete Simultaneous Discrete Response Model with Multiple Equilibria

A bivariate simultaneous discrete response model which is a stochastic representation of equilibria in a two-person discrete game is studied. The presence of multiple equilibria in the underlying discrete game maps into a region for the exogenous variables where the model predicts a nonunique outcome. This is an example of an incomplete econometric structure. Economists using this model have made simplifying assumptions to avoid multiplicity. I make a distinction between incoherent models and incomplete models, and then analyse the model in the presence of multiple equilibria, showing that the model contains enough information to identify the parameters of interest and to obtain a well defined semiparametric estimator. I also show that the latter is consistent and √n normal. Moreover, by exploiting the presence of multiplicity, one is able to obtain a more efficient estimator than the existing methods. Copyright 2003, Wiley-Blackwell.
A classification procedure for highly imbalanced class sizes

This article develops an effective procedure for handling two-class classification problems with highly imbalanced class sizes. In many imbalanced two-class problems, the majority class represents “normal” cases, while the minority class represents “abnormal” cases, detection of which is critical to decision making. When the class sizes are highly imbalanced, conventional classification methods tend to strongly favor the majority class, resulting in very low or even no detection of the minority class. The research objective of this article is to devise a systematic procedure to substantially improve the power of detecting the minority class so that the resulting procedure can help screen the original data set and select a much smaller subset for further investigation. A procedure is developed that is based on ensemble classifiers, where each classifier is constructed from a resized training set with reduced dimension space. In addition, how to find the best values of the decision variables in the proposed classification procedure is specified. The proposed method is compared to a set of off-the-shelf classification methods using two real data sets. The prediction results of the proposed method show remarkable improvements over the other methods. The proposed method can detect about 75% of the minority class units, while the other methods turn out much lower detection rates.
AdaptiveFinite Element Methodsfor the Unsteady Maxwell's Equations

In this paper we present a posteriori error estimates, and stability estimates for the time-dependent Maxwell system of electromagnetics. We use the weak formulation of Lee-Madsen and Monk, for which there is an a priori convergence theorem derived by Monk. We then discretise the problem using a standard Galerkin method, and we show that this method is stable. We derive the Galerkin orthogonality properties, which together with some interpolation properties for the finite element solution, Friedrich div-curl inequality, and the strong stability estimates for the adjoint problem (which we also derive) enable us to prove an a posteriori error estimate in the H 1-norm that forms the basis for the adaptive algorithm. Acknowledgements The author would like to thank Professor Endre Suli at Oxford University, who in 1998 acted as supervisor to the author during his work with his M.Sc. dissertation, from which this paper originates. The author would also like to thank Professor Claes Johnson at Chalmers University for allowing him the opportunity to go to Oxford and work with Professor Suli.
New improved massive gravity

We derive the field equations for topologically massive gravity coupled with the most general quadratic curvature terms using the language of exterior differential forms and a first-order constrained variational principle. We find variational field equations both in the presence and absence of torsion. We then show that spaces of constant negative curvature (i.e. the anti de-Sitter space AdS3) and constant torsion provide exact solutions.
Finite element based investigation on vibrational performance of a sandwich system

This work aims at estimating and comparing the frequency and loss factor of a mild steel sandwich shaft disc system containing viscoelastic, electro-rheological fluid (ERF), and magneto-rheological fluid (MRF) core materials with mild steel as the facing layers. Because the structure is axisymmetric, a semi-analytical finite element method was implemented to study the frequency and loss factor values of the mild steel sandwich shaft disc system. The effects of an electric field for the ERF material and a magnetic field for the MRF material on the vibration behavior of the mild steel sandwich shaft disc system were studied. A quantitative study identified the combination of mild steel facing with a viscoelastic core shaft disc system that produced the highest frequency and loss factor values. In addition, the effect of an electric field and a magnetic field on ERF and MRF core improves the damping performance of the structure.
Religious beliefs and food waste prevention practices: mechanisms of divine and environmental awareness

ABSTRACT Under the crisis of food and energy shortage caused by the COVID-19 pandemic, it is emergently important to emphasize food waste prevention in the tourism and hospitality industry because people around the world have started traveling in the post-pandemic era. Based on norm activation model and individualism-collectivism, this study proposes a perspective of religious beliefs to conceptualize divine awareness (i.e. divine retribution and divine rewards) and environmental awareness (i.e. resource scarcity and eco-friendly) on the formation of food waste prevention practices. A total of 571 samples from Taiwan and 483 samples from the United States was collected. Both countries showed that religious beliefs improved divine retribution, divine rewards, and religious food waste prevention practices. Divine rewards enhanced tourists’ awareness of resource scarcity and eco-friendly, and resource scarcity led to religious food waste prevention practices. Interestingly, the effects of divine retribution on resource scarcity and eco-friendly were significant only in Taiwan.
The effect of multiple anchors on the distribution of responses

Abstract Anchoring studies generally use high and low numerical estimates, or prompts, (identified as anchors) to introduce bias in the subsequent responses of those questioned. In this study, 700 students attending a university were equally divided into a control (no-anchor) group and six anchor groups. The numerical range of estimates (reference points) given to the anchor groups prior to their response was based on the responses of the control (no-anchor) group, which had been set at the 25, 50, 75, 85, 87, and 88 percentiles. With each increase in the prompts given to the anchor groups, there was a prominent increase in the central tendency (median) of their responses. In addition, there was an exponential increase in the spread as measured by the distance between the 75th percentile (i.e., third quartile, Q3) and the 25th percentile, (i.e., first quartile, Q1) of their responses. It is recommended that future anchor studies include a wide range of anchor percentiles and report the spread of the resulting distributions.
Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE) algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.
Fragmentation in a rotating protostar - A comparison of two three-dimensional computer codes

The collapse of an isothermal protostellar cloud with pressure, gravity and rotation included is followed with two independent computer codes. For the initial condition, a nonaxisymmetric perturbation of mode m=2 and 50% amplitude is introduced into a cloud of 1 M/sub sun/ with a mean density of 1.44 x 10/sup -17/ g cm/sup -3/ and a uniform angular velocity of 1.6 x 10/sup -12/ rads s/sup -1/. The collapse is followed through an increase in density of over four orders of magnitude to the point where a binary protostar forms. The agreement between the results of the two calculations is good.
Bayesian generalized method of moments

We propose the Bayesian generalized method of moments (GMM), which is particularly useful when likelihood-based methods are di-cult. By de- riving the moments and concatenating them together, we build up a weighted quadratic objective function in the GMM framework. As in a normal density function, we take the negative GMM quadratic function divided by two and ex- ponentiate it to substitute for the usual likelihood. After specifying the prior dis- tributions, we apply the Markov chain Monte Carlo procedure to sample from the posterior distribution. We carry out simulation studies to examine the proposed Bayesian GMM procedure, and illustrate it with a real data example.
Students Mathematical Literacy Viewed from Cognitive Style: Systematic Literature Review

This study aims to describe the results of research on students' mathematical literacy analyzed based on cognitive styles. This study used Systematic Literature Review (SLR) method. The sample in this study were 11 articles regarding students' mathematical literacy viewed from cognitive styles which were published in 2018 to September 2022 and were located in Indonesia. The results of this study will be reviewed based on the year of publication, level of education, research location, and to find out the description towards students mathematical literacy viewed from cognitive style. By using the SLR method, it was found research on students' mathematical literacy viewed from cognitive styles got a lot of attention every year, most of this research was conducted at the senior high school (SMA) education level, and most of this research was carried out in the Java island. In addition, by synthesizing the results of research on students' mathematical literacy viewed from cognitive style with the help of Atlas.ti, it was found that cognitive style influences students characteristic in using their mathematical literacy