Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermally tunable liquid crystal distributed feedback laser based on a polymer grating with nanogrooves fabricated by nanoimprint lithography

This work demonstrates a thermally tunable dye-doped liquid crystal (DDLC) distributed feedback (DFB) laser based on a polymer grating. The surface emitting DDLC DFB laser is supported by the second-order Bragg grating with nanogrooves of periodicity of 360 nm which is pre-fabricated using the UV nanoimprint lithography (UV-NIL) method. The lasing wavelength of the DFB laser can be tuned from 625.1 nm to 606.35 nm if the temperature increases from 10 °C to 50 °C. The tunability of the laser is attributable to the temperature-sensitive feature in the effective refractive index of the LCs. Such a tunable laser can be used in the fabrication of tunable optical sources and biosensors, and in integrated photonic circuits, optical communication, and laser displays.
A COmplex PRoportional ASsessment and Gray Relational Analysis methodology hybrid optimization of compression ignition engine distinctiveness fuelled by dual feed stock pyrolysis of Annona squamosa seed particles and Aegle marmelos pressed seed cake pyrolytic liquid‐diesel opus

The deficiency of fossil fuel resources, amplifying fuel price and its related environmental anxieties grasped great attention for finding an alternative fuel. Such alternative options can be fuels obtained from agricultural residues, plants, and wastes. The present research emphases on complex proportional assessment (COPRAS) and gray relational analysis (GRA) modeling of a diesel engine fuelled by Annona squamosa (AS) and Aegle marmelos (AM) co‐pyrolysis oil/diesel binary opus as an engine fuel to optimize the engine characteristics. Co‐pyrolysis oil is obtained from AS+AM feedstock at pyrolysis temperature of 500°C. To obtain engine data for training and testing the proposed COPRAS and GRA models were adopted for the engine control factors such as engine load (W) and compression ratio (CR) in a test engine rig through experimentation and hybrid optimization technics. From the engine output responses reveals that F2080 opus delivers an augmented brake thermal efficiency (22.01%) than diesel (21.56%) at peak load. Subsequently, F2080 fuel emits substantial lessening of CO (11.88%) and HC (5.64%) emissions as compared to diesel (F0). Based on the results, it is conclude that F2080 blend at CR of 17.5 and 100% load was delivered the greater engine distinctiveness through optimization outcomes and experimental evaluation compared to F0.
On coplanarity of most energetic cores in gamma-ray–hadron families and hadron interactions at (s)1/2 gtrsim 4 TeV

The phenomenon of coplanarity of the most energetic subcores of atmospheric nuclear-electromagnetic cascades found in X-ray? emulsion chamber experiments with gamma-ray? hadron families is considered. It is shown that the phenomenon cannot be explained with cascade development fluctuations and external fields within the framework of present-day versions of quark-gluon string models as well as without assuming the manifestation of a process in hadron interactions characterized with large transverse momenta in the Lab frame of reference at energies (s)1/2? 4 TeV.
Perceptions and implications of implicit gender bias in the hotel sector in Aruba

PurposeThis study aimed to collect data on the perception of top executive women in the Aruban hotel sector regarding implicit gender bias.Design/methodology/approachA qualitative study on the metacognitive processes of awareness, evaluation and autocorrection was utilized. Through purposive sampling women in the top two leadership levels in Aruba Hotel and Tourism Association (AHATA) member-hotels were selected.FindingsResults showed that a third of the top female executives experienced implicit gender bias career barriers. Different types of bias were identified such as: judgments regarding pregnancy, unequal pay and obstructions by the male general manager. How the women dealt with this bias depended on the type of bias and their personality. The identification of bias and its effects on the career trajectory were also influenced by characteristics of the work setting such as the size of the hotel and functional area.Research limitations/implicationsThe research limitations include the chosen scope, the impediment of the generalizability of the findings due to the nature of the study, self-perceived data and possible researcher and respondent bias.Practical implicationsThis study added to the existing body of leadership development literature with a focus on the effects of implicit bias on female leadership advancement. Some specific theoretical concepts that were combined in this study are organizational leadership, metacognition and the unconscious mind. The important role of personality was also confirmed in this study however one element that stood out in the current study was the effect of resilience in overcoming perceived barriers and attaining personal career goals. Suggestions and directions for future research are provided.Originality/valueDespite the fact that gender bias was not observed in an explicit form, participants advised to be aware of the existence and effects of the implicit form and to seek education and guidance from female mentors and to remain goal oriented when confronted with this bias. Since female under-representation in senior leadership positions in other economic sectors is not observed this advice serves as a significant practical implication for the development of female leadership in this important sector in Aruba.
An Unsupervised Classification for Fully Polarimetric SAR Data Using Cloude-Pottier Decomposition and Agglomerative Hierarchical Clustering Algorithm

An unsupervised classification method is proposed for fully polarimetric SAR data.The total backscattering power SPAN combined with the entropy H,the α angle and the anisotropy A is used to initialize the polarimetric SAR data.An agglomerative hierarchical clustering algorithm is introduced to reduce the number of clusters.The experimental results show that the SPAN has the additional information that is not contained in the H/α/A,and this information is important for the initialization.It is also shown that the proposed classification algorithm provides better performance than the general Wishart H/α/A classification.
Expansions in Series of Legendre Functions

The Legendre functions\(P_\nu ^\mu (x)\)occurring in this paper are sometimes called modlfied Legendre functions, or Legendre functions on the cut. They are defined in [2, p.143, eq. (6)] as $$P_{v}^{x}(x) = \frac{1}{{\Gamma (1 - \mu )}}{{\left( {\frac{{1 + x}}{{1 - x}}} \right)}^{{\frac{1}{2}\mu }}}F\left( { - v;1 + v;1 - \mu ;\frac{{1 - x}}{2}} \right) $$ (5.1) for -1 < x < 1, where F is Gauss’s hypergeometric function and μ and v are real or complex parameters. They satisfy the recurrence relation $$ (\nu - \mu + 1)P_{{\nu + 1}}^{\mu }(x) + (\nu + \mu )P_{{\nu - 1}}^{\mu }(x) = (2\nu + 1)xP_{\nu }^{\mu }(x) $$ (5.2) .
Electron Effective Masses of InAs and GaAs as a Function of Temperature and Doping

The electron effective masses of several GaAs and InAs samples at room and liquid nitrogen temperatures have been determined from Faraday rotation and infrared reflectivity measurements. An increase in effective mass with increasing carrier concentration has been found in both materials. This increase can be quantitatively interpreted in InAs in terms of the nonparabolic nature of the conduction band. In GaAs the increase in effective mass with doping suggests the existence of another set of conduction band minima above the lowest (000) minimum. The measured temperature variation of the effective mass can be attributed to two mechanisms: the increase in effective mass produced by the spread in the Fermi distribution because of the nonparabolic shape of the band, and the variation in the band structure produced by the thermal expansion of the lattice.
EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS EMSA: Hybrid Metaheuristic based on Genetic Algorithms, Simulated Annealing and Deterministic Swapping

This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Meta-heuristic for the multi-objective optimization of combinatorial prob- lems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the com- binatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Sales- man Problem (TSP) from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor). The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%.
The Determination of Sample Sizes in the Comparison of Two Multinomial Proportions from Ordered Categories

Summary We consider sample size determination for ordered categorical data when the alternative assumption is the proportional odds model. In this paper the sample size formula proposed by Whitehead (Statistics in Medicine, 12, 2257–2271, 1993) is compared with the methods based on exact and asymptotic linear rank tests with Wilcoxon and trend scores. We show that Whitehead’s formula, which is based on a normal approximation, works well when the sample size is moderate to large but recommend the exact method with Wilcoxon scores for small sample sizes. The consequences of misspecification in models are also investigated.
Meaning in life through work: A cognitive-experiential self-theory (CEST) perspective

This article explores existential meaning-making from work using the cognitive-experiential self-theory (CEST). To start with, we use the tenets of CEST to elaborate on how the cues from archetype work environments—a realization facilitating work environment (RfWE) and justification facilitating work environment (JfWE)—are interpreted by information-processing systems to imbue meaning in life (MiL) as internal or external manifestations of coherence, purpose, and significance. Next, we explain how individual differences in work centrality and proactive meaning-crafting ability moderate the impact of JfWE, but not of RfWE, on MiL. Finally, we create a nomological network of existential meaning states emerging from the simultaneous presence or absence of RfWE and JfWE. In summary, by applying the information-processing lens of CEST, we develop an integrated model that explains how work drives MiL, elucidates the resultant existential states, and assesses the role of individual differences in meaning-making. Plain Language Summary This article develops an integrated model that outlines how work environments can augur human well-being by fostering a sense of meaning in life (MiL). Based on the cognitive-experiential self-theory (CEST), expounding parallel-competitive processing of information through the working of the experiential and rational system, we explore how the cues from archetype work environments—a realization facilitating work environment (RfWE) and justification facilitating work environment (JfWE)—influence the varied flavors of MiL and meaninglessness in life. We build the argument that RfWE activates the functioning of the experiential system to induce a feeling of internal MiL as internal coherence, internal purpose, and internal value significance. At the same time, JfWE triggers the functioning of the rational system to construct a judgment of external MiL as external coherence, external worthy purpose, and external value significance. However, the interaction between RfWE and JfWE can result in intricate scenarios, including favorable states such as holistic meaning, positive existential feelings, and positive existential narratives. Still, it can also lead individuals into meaninglessness in life through existential fatigue, existential cocoon, or existential futility. Nonetheless, individual differences in work centrality and proactive behavior to craft meaning can act as moderators to alter the intensity of work’s impact on MiL in a JfWE but not in an RfWE.
A Variational Method for Real-Time Retrieval of Three-Dimensional Wind Field from Multiple-Doppler Bistatic Radar Network Data

Abstract A variational method for the retrieval of the 3D wind field from bistatic multiple-Doppler radar network data is developed, and its performance is evaluated. This bistatic network consists of one S-band weather radar and two passive low-gain receivers at remote sites. To allow for measurement error, the method uses the Doppler velocities of the three receivers as weak constraints and uses the continuity equation as a strong constraint in a cost function in which the two horizontal wind components are the control variables. Improvements are brought to the classical upward integration of the continuity equation, using a weighted combination of upward and downward integrations and its adjoint. A unique characteristic of a bistatic network is that all Doppler velocity measurements from individual resolution volumes are collected simultaneously, which minimizes the errors on the vertical wind component arising from the local evolution of the airflow. However, the time required to sample a complete wea.
Comparative Study of Frequency of Alveolar Osteitis, with and without using Platelet-Rich Fibrin in Mandibular Third Molar Surgery

Introduction Alveolar ostitis (AO) is the dissolution of blood clot due to enhanced local fibrinolysis and is caused by trauma to the jaw (direct) or because of bacterial involvement (indirect), which result in the activation of plasminogen pathway. Platelet-rich fibrin (PRF) is a platelet concentrate that comprises numerous autologous growth factors, and immune cells hence has the potential to expedite the healing process. The objective of the study was to determine the efficacy of PRF in the surgically extracted third molar in the context of its potential progress to AO. Materials and Methods A total of 180 patients of 18–65 years with unilateral painful mandibular third molars due to caries, failed endodontics treatment, and pericoronitis were included in the study. Exclusion criteria were patients who were medically compromised, smokers, alcoholic, poor oral hygiene, third molar having associated periapical pathology, and receiving antibiotic regime in the last 2 weeks. Before starting surgical procedure, patients were randomly divided into two groups using lottery method. Group I received PRF in the extraction socket, while in Group II, the extraction site was left for normal healing as practiced in a standard procedure. Pain was assessed in terms of pain score, and it was recorded on a 10 mm visual analog scale on the first and third postoperative days. Results Mean age of the patients was 41.35 ± 9.87 years. The mean age in Group I was 42.84 ± 10.52 years, and in Group II, it was 40.54 ± 9.52 years. Out of 180 patients, 90 (50.0%) were male and 90 (50.0%) were female, with a male-to-female ratio of 1 : 1. Frequency of AO following mandibular third molar surgery in Group I receiving PRF was 2.22% and in non-PRF group 12.22% (p-value = 0.010). Conclusion The incidence of AO following mandibular third molar surgery was lower when PRF was used.
Development and Evaluation of Japanese Clause Boundaries Annotation Program

従来の文分割研 究において,文 の分割点 として利用 されてきたのは,「節」 の境界で ある. し か しなが ら,実 際に文の分割点 として用い られる節境界 はごく一部の種類の ものに限 られてお り,文 に含 まれる節境界 を網羅的に検 出す る手法は考え られてこな かった. 我 々は,日 本語の文 に含 まれる節境界 の位置 を網羅的に検出 し,そ の種類 を 特定するプログラム"CBAP(Clause Boundaries Annotation Program)"を 開発 した. CBAPは,形 態素解析 の結果 を入力 とし,局 所的な形態素の連接 を対象 としたパ タン マ ッチによって,147種 類の節境界 を検 出する. CBAPを 性質の異 なる5種 のコーパ ス に適用 した ところ,い ずれの コーパスで も97%以 上の検 出性能が確認 された. こ の検 出結果を利用することによ り,言 語学的 に意味のある文の分割点を特定すること がで き,従 来の手法 よりも柔軟 に文分割 を行なうことができる. ま た,1~3形 態素 と いう非常 に局所的な範囲のみか ら節境界 を検出で きるため,発 話 に追従 して処理を進 めてい く漸進的構文解析や同時通訳 システム,ま た,句 点 を含 まない音声 コーパスを 対象 とした発話分割処理などに有用である. 本 稿では,CBAPに よる節境界の検出手 法 を示 し,節 境界 を用いて文分割 ・発話分割処理を行なった事例 を もとに,節 境界検 出の有用性 を述べ る.
Application of the random choice method to shallow water equations

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto. fi Author Petteri Peltonen Name of the publication Application of the random choice method to shallow water equations Publisher School of Engineering Unit Department of Applied Mechanics Series Aalto University publication series SCIENCE + TECHNOLOGY 17/2015 Field of research Marine Technology Abstract The Random Choice Method is applied to the one-dimensional shallow water equations with operational splitting to take into account forced domain motion. The Random Choice Method is based on randomly sampling exact Riemann solutions and thus the Riemann solution for the shallow water equations plays a key role in applying the method. The details of the application are presented and the methods accuracy and applicability is discussed through comparison to experimental results as well as literature review. Furthermore, the possible extension of the method to two dimensions is discussed. Since much of the physics of the flow is neglected in assumptions made in the derivation of the shallow water equations, it is clear that phenomena such as wave breaking and turbulence effects can not be captured with the method. However, the results obtained here show that the method can be applied to solve the shallow water motion under domain excitation, as long as the excitation frequency is relatively low. With higher frequencies of excitation the results show error in the conservation of mass.The Random Choice Method is applied to the one-dimensional shallow water equations with operational splitting to take into account forced domain motion. The Random Choice Method is based on randomly sampling exact Riemann solutions and thus the Riemann solution for the shallow water equations plays a key role in applying the method. The details of the application are presented and the methods accuracy and applicability is discussed through comparison to experimental results as well as literature review. Furthermore, the possible extension of the method to two dimensions is discussed. Since much of the physics of the flow is neglected in assumptions made in the derivation of the shallow water equations, it is clear that phenomena such as wave breaking and turbulence effects can not be captured with the method. However, the results obtained here show that the method can be applied to solve the shallow water motion under domain excitation, as long as the excitation frequency is relatively low. With higher frequencies of excitation the results show error in the conservation of mass.
3-D modeling of electromagnetic fields in application to electromagnetic launchers

A mathematical model for a homogeneous (over regions of distinctly different electrophysical properties) simulation of phenomena in a railgun launcher is constructed. The necessity of the use of three-dimensional (3-D) approximation is shown. The algorithm for defining boundary conditions is developed, so that a given total launcher current is equal to the current through a region of simulation. Numerical calculations with different ways of specifying boundary conditions are compared. The results of 3-D numerical simulation of railguns of different configurations are presented. Particularly, the muzzle-fed railgun is described in detail.
Asymptotics for High Dimension, Low Sample Size data and Analysis of Data on Manifolds

SUNGKYU JUNG: Asymptotics for High Dimension, Low Sample Size data and Analysis of Data on Manifolds. (Under the direction of Dr. J. S. Marron.) The dissertation consists of two research topics regarding modern non-standard data analytic situations. In particular, data under the High Dimension, Low Sample Size (HDLSS) situation and data lying on manifolds are analyzed. These situations are related to the statistical image and shape analysis. The first topic is an asymptotic study of the high dimensional covariance matrix. In particular, the behavior of eigenvalues and eigenvectors of the covariance matrix is analyzed, which is closely related to the method of Principal Component Analysis (PCA). The asymptotic behavior of the Principal Component (PC) directions, when the dimension tends to infinity with the sample size fixed, is investigated. We have found mathematical conditions which characterize the consistency and the strong inconsistency of the empirical PC direction vectors. Moreover, the conditions where the empirical PC direction vectors are neither consistent nor strongly inconsistent are revealed, and the limiting distributions of the angle formed by the empirical PC direction and the population counterpart are presented. These findings help to understand the use of PCA in the HDLSS context, which is justified when the conditions for the consistency occur. The second part of the dissertation studies data analysis methods for data lying in curved manifolds that are the features from shapes or images. A common goal in statistical shape analysis is to understand variation of shapes. As a means of dimension reduction and visualization, there is a need to develop PCA-like methods for manifold data. We propose flexible extensions of PCA to manifold data: Principal Arc Analysis and Analysis of Principal Nested Spheres. The methods are implemented to two important types of manifolds. The sample space of the medial representation of shapes, frequently used in image analysis to parameterize the shape of human organs, naturally forms curved manifolds, which we characterize as direct product manifolds. Another type of manifolds we consider is the landmark-based