Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedded Eigenvalues for Water-Waves in a Three-Dimensional Channel with a Thin Screen

We construct asymptotic expansions as ε → +0 for an eigenvalue embedded into the continuous spectrum of water-wave problem in a cylindrical three dimensional channel with a thin screen of thickness O(ε). The screen may be either submerged or surface-piercing, and its wetted part has a sharp edge. The channel and the screen are mirror symmetric so that imposing the Dirichlet condition in the middle plane creates an artificial positive cut-off-value Λ† of the modified spectrum. Depending on a certain integral characteristic I of the screen profiles, we find two types of asymptotics of eigenvalues, λ = Λ† − O(ε) and λ = Λ† −O(ε) in the cases I > 0 and I = 0, respectively. We prove that in the case I < 0 there are no embedded eigenvalues in the interval [0,Λ†], while this interval contains exactly one eigenvalue, if I ≥ 0. For the justification of these result, the main tools are a reduction to an abstract spectral equation and the use of the max-min-principle.
Review of basic Concepts involved in Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a powerful tool to get spatial information about muscles of different regions inside the body. It has the advantage of being non-invasive and being without any radiations. It is objective and quantitative tool. This review covers the basics of MRI and informs about how the image is obtained using MRI.
Centering with conjoined and iterated conditionals under coherence

There is wide support in logic, philosophy, and psychology for the hypothesis that the probability of the indicative conditional of natural language, $P(\textit{if } A \textit{ then } B)$, is the conditional probability of $B$ given $A$, $P(B|A)$. We identify a conditional which is such that $P(\textit{if } A \textit{ then } B)= P(B|A)$ with de Finetti's conditional event, $B|A$. An objection to making this identification in the past was that it appeared unclear how to form compounds and iterations of conditional events. In this paper, we illustrate how to overcome this objection with a probabilistic analysis, based on coherence, of these compounds and iterations. We interpret the compounds and iterations as conditional random quantities which, given some logical dependencies, may reduce to conditional events. We show how to extend the inference of centering for conditional events, that is inferring $B|A$ from $A$ and $B$, to compounds and iterations of both conditional events and biconditional events. Moreover, we determine the lower and upper bounds for the conclusions in the classical and extended versions of centering. We also study some other related aspects. Finally, we apply our analysis to the semantics of counterfactuals.
Bulk-Density Representations of Branched Planar Ice Crystals: Errors in the Polarimetric Radar Variables

AbstractRecent interest in interpreting polarimetric radar observations of ice and evaluating microphysical model output with these observations has highlighted the importance of accurately computing the scattering of microwave radiation by branched planar ice crystals. These particles are often represented as spheroids with uniform bulk density, reduced from that of solid ice to account for the complex, non-uniform structure of natural branched crystals. In this study, we examine the potential errors that arise from this assumption by comparing scattering calculations of branched planar crystals with those of homogeneous, reduced-density plate crystals and spheroids with the same mass, aspect ratio, and maximum dimension. Our results show that this assumption leads to significant errors in backscatter cross-sections at horizontal and vertical polarization, specific differential phase (KDP), and differential reflectivity (ZDR), with the largest ZDR errors for ice crystals with the most extreme aspect rati.
Electronic Module Renewable Energy (E-MET): Validity and Practicality Aspect

The study aims to describe the validity and practicality of E-MET. This research is research and development with the ADDIE model. The E-MET validator for this e-module consists of two people, consisting of academics and practising experts. The validation results using the E-MET validation sheet show that the validity of the e-module on renewable energy material has good criteria. The practicality of the developed E-MET is reviewed based on benefits, usability, and time efficiency as measured through a student response questionnaire. Then the study results show that the practicality of e-modules on renewable energy materials has good criteria. The research was conducted in class XI SMAN 3 Kota Ternate. Therefore, E-MET can be used for physics learning on renewable energy materials.Penelitian ini bertujuan untuk mendeskripsikan validitas dan kepraktisan E-MET. Penelitian ini merupakan penelitian dan pengembangan dengan model ADDIE. Validator E-MET ini e-modul berjumlah dua orang, terdiri dari ahli akademisi dan ahli praktisi. Hasil validasi menggunakan lembar validasi E-MET menunjukkan bahwa validitas e-modul pada materi energi terbarukan memiliki kriteria baik. Kepraktisan E-MET yang dikembangkan ditinjau berdasarkan aspek manfaat, kegunaan, dan efisiensi waktu yang diukur melalui angket respon peserta didik. Kemudian hasil penelitian menunjukkan bahwa kepraktisan e-modul pada materi energi terbarukan memiliki kriteria baik. Penelitian dilakukan pada kelas XI SMAN 3 Kota Ternate. Oleh karena itu, E-MET dapat digunakan untuk pembelajaran fisika pada materi energi terbarukan.
Psychological contract, auditor deviations and audit quality

This article is designed to explore the theme: “Psychological Contract, Auditor Deviation, and Audit Quality Which is reviewed from the point of view of non-public accountants. This theme was lifted from the results of research conducted at a company in Surabaya, East Java, Indonesia. Moreover, this study aims to examine the relationship between psychological contracts, Dysfunctional Auditor Behavior, and Audit Quality. This research was taken place at the Non-Big category of Public Accounting Firms or not affiliated with the Big Public Accounting Firms located in Surabaya, East Java, Indonesia. The subjects of this study were supervisory level auditors with the assumption that they had understood and experienced in implementing audit procedures and how they understood the work environment, work relations, and leadership. Researchers use psychological contract variables as independent variables, the variable Audit Quality as the dependent variable, and the Dysfunctional Auditor Behavior variable as the mediating variable. Statistical testing using simple regression to prove the three hypotheses proposed by researchers. The results shows that the psychological contract has a negative effect on dysfunctional auditor behavior and it also can negatively effect on the audit quality. In contrast, the Psychological Contract can positively influence on the audit quality.
Mössbauer Studies of Fe 57 in Orthoferrites

The hyperfine interactions of the iron nuclei in the orthoferrites were studied between 85 and 770\ifmmode^\circ\else\textdegree\fi{}K using the M\"ossbauer effect. The temperature dependence of the sublattice magnetization ${\ensuremath{\sigma}}_{s}(T)$ is compared with various statistical-mechanical theories. It obeys approximately a $\frac{1}{3}$ power law in the temperature range $0.60l\frac{T}{{T}_{N}}l0.99$, and spin-wave theory and Callen decoupling at low temperature in the range $\frac{T}{{T}_{N}}l0.5$. From ${\ensuremath{\sigma}}_{s}(T)$, it is found that the canting angle in these weak ferromagnets is temperature-independent. The exchange integral calculated from the Oguchi spin-wave theory agrees with that calculated from Rushbrook and Wood's high-temperature series expansion and the Green's-function theories, while that calculated from the molecular field and Kubo's spin-wave theories is considerably lower. The quadrupole coupling constant is in good agreement with values calculated by point-charge lattice sums. The specific heat obtained from the temperature shift at high temperature agrees with the Dulong-Petit law. The value of the isomer shift is equal to that expected for a trivalent iron ion.
Utilisation de l'algorithme de Kalman pour le traitement des séries chronologiques

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Identifying factors that promote or inhibit disability-related discussion in secondary English language arts classrooms

ABSTRACT Although disabled people encounter discrimination in almost every facet of life – such as employment, housing, education, healthcare, and transportation – disability is often missing from conversations regarding social justice. Disability-related discussion (DRD) in English Language Arts (ELA) offers an inroad to having students view disability through a social justice lens. This exploratory, qualitative study examines the factors that influence 13 secondary (6–12) ELA teachers’ decisions to lead (or refrain from leading) DRD in classrooms in the United States. Findings reveal that primary factors that helped or hindered DRD included the role of subject/curriculum, school and classroom culture, and personal factors. Participants also expressed a desire for professional development related to DRD, as well as increased curricular representation within ELA. This study represents a critical first step in solidifying disability as a component of social justice by identifying factors that secondary ELA teachers encounter when attempting to discuss disability in their classrooms.
Evaluation of the high-rate GNSS-PPP method for vertical structural motion

This study aims at the investigation of GNSS-PP method to determine the dynamic characteristics of structures. Cantilever steel bars having lengths of 70, 100 and 120 cm were tested under dynamic excitation. The GNSS was used to measure the natural frequencies and damping values of all the tested cantilever structures. The GNSS data were processed using relative GNSS positioning and PPP methods. The results obtained using these two methods were also compared with the dynamic characteristics obtained by applying the theoretical and finite element (FE) methods. Furthermore, it is investigated the impact of the stable data length before oscillation events on kinematic PPP. The study showed that the maximum difference among the experimental results in terms of natural frequencies proceeded using PPP is 0.08 Hz when compared with the theoretical and FE results. Furthermore, there is no difference between the PPP and relative GNSS positioning in determining the dynamic behaviour of structures eventhough roving GNSS antenna remains motionless for short-time, such as a few-minutes, before an event occurred.
Sampling from non-smooth distribution through Langevin diffusion

In this paper, we propose proximal splitting-type algorithms for sampling from distributions whose densities are not necessarily smooth nor log-concave. Our approach brings together tools from, on the one hand, variational analysis and non-smooth optimization, and on the other hand, stochastic diﬀusion equations, and in particular the Langevin diﬀusion. We establish in particular consistency guarantees of our algorithms seen as discretization schemes in this context. These algorithms are then applied to compute the exponentially weighted aggregates for regression problems involving non-smooth priors encouraging some notion of simplicity/complexity. Some popular priors are detailed and implemented on some numerical experiments.
T. Catappa confers an antioxidant effect to electrospun polyvinyl alcohol nanofibers

In this study, the healing process of full-thickness skin wounds induced in Wistar rats (n = 75) was evaluated, divided into 5 treatments: negative control, PVA nanofiber film, and PVA nanofiber film added in concentrations of 3%, 6% and 10% with lyophilized extract of T. catappa. After euthanasia of 5 animals from each of the groups, at times 7, 14 and 21 days, samples were evaluated for the presence of oxidative stress markers reduced Glutathione (GSH) and levels of lipoperoxidation (LPO), and for the histological characteristics of tissues stained with hematoxylin-eosin and azan. The results showed that, in addition to remaining on the surface of the wounds for an acceptable period, the nanofiber membrane was able to deliver the extract of T. catappa to the bed of the treated wounds and, despite not producing statistically relevant histological changes, it was observed significant antioxidant effect by reducing LPO and increasing GSH in a dose dependent manner. Thus, it is concluded that the PVA nanofiber film associated with the T. catappa extract has an antioxidant effect and can assist in wound healing
Hyperspectral Image Denoising by Fusing the Selected Related Bands

Hyperspectral images (HSIs) convey more useful information than RGB or gray images, which are widely used in many remote sensing tasks. In real scenarios, HSIs are inevitably corrupted by noise because of sensors’ imperfectness or atmospheric influence. Recently, many HSI denoising methods have been proposed to utilize the interband information between different spectral bands. However, these methods regard the HSI as a whole and treat the different spectral bands with the same noise level. In fact, the noise levels in different bands are different. Especially, only few certain bands are corrupted by noise, named the target noised bands. Under this circumstance, an HSI denoising method is proposed by considering the band relationship and different noise levels. The target noised bands are adaptively denoised by fusing some selected bands. Specifically, some related but quality superior bands are selected according to the target noised bands. Then, the target noised bands can be denoised by fusing the selected related bands. Experimental results show that the proposed method achieves considerable performances in comparison with several state-of-the-art hyperspectral denoising methods.
Assessment of Lung Efficiency of Individuals Exposed to Various Foundry Industries in Satara City

The airborne dust as pollutants plays a major role in the overall atmospheric pollution. Silica is a chemical term for silicon dioxide (SiO2). The term crystalline silica refers to a crystallized form of SiO2 known as quartz, crystobalite or tridymite; it is the most abundant compound on the earth’s crust capable of causing silicosis and lung cancer upon inhaling large doses in course of occupational exposure. The present study was aim to evaluate the lung efficiency of individuals who worked in various foundry industries in Satara city. Around 300 individuals were enrolled. From selected three locations, 100 individuals were enrolled. All the individuals from the test were given a pulmonary function test. Before the test, a questionnaire was given to them to collect their basic information. Their age, height and weight were also entered in the spirometer. The spirometer gives two values; one is the expected value and the other is actual value. The predicted values are based upon the age, height and weight of the person while the actual values are dependent upon the maximal inspiration and expiration of the person. All the parameters, i.e. FVC, SVC and MVV showed impairment in the large industry workers compared to other two industries workers. A significant difference (p < 0.01) in the actual and expected values was observed in the pulmonary function test individuals of all the three selected industries. The percentage efficiency for all parameters for small industry workers, i.e. FVC (96.42 %), SVC (95.71 %) and MVV (88.69 %) was also good as compared to large and medium industries. At large industry, MVV efficiency was very less (59.66 %) as compared to the medium industry (68.61 %) and small industry (88.69 %) workers. In the SVC also, a large industry worker (69.72 %) showed less value as compared to the medium industry (79.99 %) and small industry (95.71 %) workers. Restrictive defect was 14 %, 36 %, 33 % and 17 % in the large industry workers which was normal, mild, moderate and severe, respectively. These values were very low as compared to small industry workers. Individuals exposed to heavy load of pollutants in air are susceptible for many respiratory disorders. Decrease in the FVC, MVV and SVC parameters were observed in the individuals of large industry assz compared to medium and small industry. This impairment in the pulmonary test parameters are indications of an accumulation of pollutants in the airways, which intern reduces inhalation and exhalation force. So, the people exposing continuously to such silica or particulate matter pollution should be made aware about pulmonary disorders.
Logarithmic Incremental Parameter Tuning of Support Vector Machines for Human Activity Recognition

Objectives: In machine learning based human activity monitoring, the algorithm needs to produce a prediction model with a high accuracy. Support vector machine is one of the leading machine learning algorithms. Methods/Statistical Analysis: We propose an optimization approach of support vector machines that optimizes its regularization parameter to further improve its prediction accuracy in a human activity recognition application. In order to implement an efficient support vector machines predictive model of a particular dataset that would generalize well and have a good prediction performance, a suitable regularization parameter has to be applied in the regularization part of the equation. Findings: In order to empirically evaluate the effectiveness of our proposed approach, we show the results of our implementation and discuss the results of our proposed approach explained in the previous section on support vector machines models. From our experiments, we can see that we got fabulous results when the regularization parameter is 1000. For the accuracy on train/test dataset pair, we got a sufficiently high percentage for regularization parameter values of 10, 100 and 1000. And, the best cross validation accuracy is 98.8575, which is corresponding to a regularization parameter value of 1000. Additionally, we can also notice that the relation between the classification accuracy and the cross validation accuracy is proportional, and that is obvious in the accuracies responding to the regularization parameter of 0.0001, because both accuracies are significantly low. Improvements/Applications: Our idea was to replace the parameter value with a vector of parameter values and compare their results. It shows more improved and promising performance improvement but if we can apply parallel programming.
The root cluster after percolation on preferential attachment trees

The class of linear preferential attachment trees includes recursive trees, plane-oriented recursive trees, binary search trees, and increasing $d$-ary trees. Bond percolation with parameter $p$ is performed by considering every edge in a graph independently, and either keeping the edge with probability $p$ or removing it otherwise. The resulting connected components are called clusters. In this extended abstract, we demonstrate how to use methods from analytic combinatorics to compute limiting distributions, after rescaling, for the size of the cluster containing the root. These results are part of a larger work on broadcasting induced colorings of preferential attachment trees.
Photonic crystal microring resonators for Raman signal enhancement in NIR spectral range

We report on a compact, on-chip, and inexpensive Raman spectrometer platform that provides 6 orders of magnitude enhancement of Raman signal in the near-IR spectral range of 0.7-1. 2μm with a laser excitation of 785 nm. It is based on microring resonators integrated with sinusoidal photonic crystal (MRR-SPC) both in the ring-resonator and in the bus waveguide. A low-loss Si3N4 waveguide is chosen to meet the requirements of high index contrast and ultracompact design. The proposed MRR-SPC can find its applications in bio/chemical ware fare sensing, chemical sensing, lab-on-a-chip systems for mobile and portable devices.
Fuzzy autoencoder for multiple change detection in remote sensing images

Abstract. This paper establishes the fuzzy autoencoder (FAE) to detect multiple changes between two one-dimensional multitemporal images. Different from the traditional approaches based on the pixel intensity, FAE includes a multilayer structure through self-reconstruction to extract the feature from an image. Due to the existence of noise in the images, the raw data tend to be corrupted and fail to detect the real changes. Therefore, the fuzzy number is introduced to the autoencoder to establish the FAE which is able to suppress the noise and learn robust features. In this way, the information in the fuzzy domain is introduced into the input, and in practice the fuzzy domain is discretized to facilitate the calculation. In addition, the weighted Frobenius norm is used to establish the loss function which can be minimized to achieve the optimal parameters. The framework is highlighted by the newly designed FAE. As the fuzzy number is introduced into the autoencoder, more information concerning the fuzzy domain is taken into consideration and thus the impact brought by the noise is relieved to a large extent. Hence, the FAE can generate robust features, enhancing its performance on deep feature representation learning. Several tests on three datasets show us the proper parameter settings, and the experimental results from the FAE framework and the other compared approaches demonstrate its effectiveness and robustness in terms of accuracy and elapsed time.
Toward Sustainable Intelligent Transportation Systems in 2050: Fairness and Eco-Responsibility

The Paris Agreement set global energy conservation and emission reduction standards in 2016, and the ambitious goal of carbon neutrality must be achieved by 2050. However, the conflicts between environmental protection, economic development and social fairness constrain the development of sustainable transportation systems. At the same time, the automotive industry believes that large-scale application of autonomous driving technology is expected by 2050. The development and application of autonomous driving technology can provide a new solution to improve the sustainability of the transportation system. Meanwhile, autonomous vehicles can significantly enhance the mobility of people with disabilities and seniors and reduce the transportation cost for poverty people, improving the transportation fairness of the entire society. This letter discusses the impact of autonomous driving technology on sustainable transportation systems from the perspectives of social fairness and economic responsibility, as a brief summary of the third part of Distributed/Decentralized Hybrid Workshop on Sustainability for Transportation and Logistics (DHW-STL).