Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Optimization of a Resonant Micro-Optic Gyroscope Based on a Transmissive Silica Waveguide Resonator

In order to optimize the performance of a resonant micro-optic gyroscope, a well-designed transmissive structure, which was obtained by optimizing the transmission coefficient of a coupler was used as the core component of a planar waveguide optical gyroscope. By analyzing the relationship between the resonator’s transmission coefficient and the gyroscope’s scale factor, the optical waveguide resonator sensing element with optimal parameters for the resonant micro-optic gyroscope was obtained. A scale factor of 1.34 mV/°/s was achieved using an open-loop system, and a bias stability of 183.7 °/h over a one-hour test was successfully demonstrated.
A Quasi-Experimental Approach to Understanding Study Abroad’s Impact on Academic Success Among Community College Students

ABSTRACT The purpose of this study is to provide robust estimates of the potential link between study abroad participation and community college students’ academic outcomes, namely academic qualifications (GPA), progression toward degree (credits passed), and credential completion. Theoretically, study abroad is thought to impact students’ outcomes, academic and otherwise, through its value as an educational experience that disrupts students’ normal learning routines. Using both propensity score modeling and difference-in-differences analysis, I find limited evidence of a causal connection between study abroad participation and any of the three outcomes explored in this study. While a consistent significant positive relationship between study abroad and both GPA and percentage of credits passed was observed in propensity score matching models, this relationship was not found in difference-in-differences models, suggesting residual selection bias in the former set of models. While this study’s results are likely to be viewed as problematic by practitioners in international education who champion the benefits of international education, it is important to note that study abroad may be related to outcomes that are more proximal to the abroad experience itself (e.g., gains in intercultural competence) and that study abroad does not appear to harm students’ academic prospects.
The Relationship between Mustard Import and COVID-19 Deaths: A Workflow with Cross-Country Text Mining

We developed a workflow for the search and screening of natural products by drawing from worldwide experiences shared by online platform users, illustrated how to cope with COVID-19 with a text-mining approach, and statistically tested the natural product identified. We built a knowledge base, which consists of three ontologies pertaining to 7653 narratives. Mustard emerged from texting mining and knowledge engineering as an important candidate relating to COVID-19 outcomes. The findings indicate that, after controlling for the containment index, the net import of mustard is related with reduced total and new deaths of COVID-19 for the non-vaccination time period, with considerable effect size (>0.2).
Restoration of Geographically Isolated Wetlands: An Amphibian-Centric Review of Methods and Effectiveness

Geographically isolated wetlands provide a critical habitat for pond-breeding amphibians, a taxa of broad conservation concern. Global wetland loss and degradation has made restoration essential for amphibian conservation. Restoration goals typically include recovering the wetlands’ physiochemical, hydrological, and ecological functions. However, for pond-breeding amphibians, successful restoration should also result in sustained populations, which is difficult to assess and infrequently reported. In this paper, we review the available evidence that restoration of geographically isolated wetlands promotes pond-breeding amphibian occupancy and population persistence. We provide an overview of restoration practices addressing hydrology, vegetation, and ecological processes within these unique environments and across spatial scales. We then summarize the evidence, and discuss the limitations, for evaluating successful restoration within the context of amphibian conservation across these categories. Finally, we provide recommendations for researchers and practitioners to leverage prior successes and establish systematic data collection and dissemination. Moving restoration of wetlands for amphibian conservation forward will require more robust data collection and reporting.
Fast Underwater Optical Beacon Finding and High Accuracy Visual Ranging Method Based on Deep Learning

Visual recognition and localization of underwater optical beacons is an important step in autonomous underwater vehicle (AUV) docking. The main issues that restrict the use of underwater monocular vision range are the attenuation of light in water, the mirror image between the water surface and the light source, and the small size of the optical beacon. In this study, a fast monocular camera localization method for small 4-light beacons is proposed. A YOLO V5 (You Only Look Once) model with coordinated attention (CA) mechanisms is constructed. Compared with the original model and the model with convolutional block attention mechanisms (CBAM), and our model improves the prediction accuracy to 96.1% and the recall to 95.1%. A sub-pixel light source centroid localization method combining super-resolution generative adversarial networks (SRGAN) image enhancement and Zernike moments is proposed. The detection range of small optical beacons is increased from 7 m to 10 m. In the laboratory self-made pool and anechoic pool experiments, the average relative distance error of our method is 1.04 percent, and the average detection speed is 0.088 s (11.36 FPS). This study offers a solution for the long-distance fast and accurate positioning of underwater small optical beacons due to their fast recognition, accurate ranging, and wide detection range characteristics.
Semantic Image Segmentation: Two Decades of Research

Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer vision applications, providing key information for the global understanding of an image. This survey is an effort to summarize two decades of research in the field of SiS, where we propose a literature review of solutions starting from early historical methods followed by an overview of more recent deep learning methods including the latest trend of using transformers. We complement the review by discussing particular cases of the weak supervision and side machine learning techniques that can be used to improve the semantic segmentation such as curriculum, incremental or self-supervised learning. State-of-the-art SiS models rely on a large amount of annotated samples, which are more expensive to obtain than labels for tasks such as image classification. Since unlabeled data is instead significantly cheaper to obtain, it is not surprising that Unsupervised Domain Adaptation (UDA) reached a broad success within the semantic segmentation community. Therefore, a second core contribution of this book is to summarize five years of a rapidly growing field, Domain Adaptation for Semantic Image Segmentation (DASiS) which embraces the importance of semantic segmentation itself and a critical need of adapting segmentation models to new environments. In addition to providing a comprehensive survey on DASiS techniques, we unveil also newer trends such as multi-domain learning, domain generalization, domain incremental learning, test-time adaptation and source-free domain adaptation. Finally, we conclude this survey by describing datasets and benchmarks most widely used in SiS and DASiS and briefly discuss related tasks such as instance and panoptic image segmentation, as well as applications such as medical image segmentation.
Exact Solutions to the Fermion Propagator Schwinger-Dyson Equation in Minkowski space with on-shell Renormalization for Quenched QED

With the introduction of a spectral representation, the Schwinger-Dyson equation (SDE) for the fermion propagator is formulated in Minkowski space in QED. After imposing the on-shell renormalization conditions, analytic solutions for the fermion propagator spectral functions are obtained in four dimensions with a renormalizable version of the Gauge Technique anzatz for the fermion-photon vertex in the quenched approximation in the Landau gauge. Despite the limitations of this model, having an explicit solution provides a guiding example of the fermion propagator with the correct analytic structure. The Pad\'{e} approximation for the spectral functions is also investigated.
Predictors of adherence to prescribed antihypertensive medications among Hypertensive (15-49 years) in India: A secondary data analysis of National Family Health Survey 4

Background: Adherence to medications is one of the key determinants of therapeutic control of high blood pressure and is seen as a bottleneck in our fight against hypertension control. We have little scientific evidence from India that highlights the determinants of treatment adherence. Aim: The purpose of this study was to identify the predictor adherence to the currently prescribed antihypertensive medications. Material and Methods: We did a secondary data analysis of the National Family Health Survey, 2015-2016 datasets. As there were no direct variables to measure adherence, this was derived from the responses to the survey question: “currently taking a prescribed hypertensive medication to lower Blood Pressure” among those already diagnosed as hypertensives by the physician. The other sociodemographic and household-level variables were used as independent variables for analysis. Results: The level of awareness about their hypertensive status among the 15–49-year-olds who were subjected to blood pressure measurement was 9.34% (70,267/80,3081). Of these, 70,267 participants, 65878 with valid hypertensive individual data were included in the final analysis. Among them, 26.78% are currently adhering to antihypertensive medication. Female gender (adj OR; 95% CI: 1.17 [1.09–1.24]) and non-reserved caste ([OR] 1.24; 95% [CI]: 1.18–1.32) depicted better adherence to the current treatment. The hypertensives who preferred taking treatment from shops or at home or some other place in comparison to health facilities had a significant association with adherence (adj OR: 1.64; 95% CI: [1.43–1.88]). Conclusion: The current study reported low adherence to the current antihypertensive medication. Gender, higher age group, obesity, and place of taking the treatment were strongly associated with adherence to treatment.
PERILAKU SELF-HARM ATAU MELUKAI DIRI SENDIRI YANG DILAKUKAN OLEH REMAJA (SELF-HARM OR SELF-INJURING BEHAVIOR BY ADOLESCENTS)

Self-harm behavior is a form of behavior that done to deal with emotional distress or emotional pain by hurting him/herself without any intention of committing suicide. From various studies, adolescents are the one who have high intention of this behavior. There is still a few research for this issue because of the iceberg phenomenon. This issue rated as iceberg phenomenon because there is much number of cases that have not been revealed. This article provides a literature review on self-harm or self-injuring behavior in adolescents and the factors that have the potential to cause self-injury in adolescents. The research objective was to find out and get more information about self-harm behavior. The method that was used in this article is a literature review. The result is self-harm behavior mostly done by adolescent because adolescence is a period of time where there are full of conflicts so that they are vulnerable to doing self-harm. Potential factors to cause adolescents to injuring themself which was discussed below are loneliness, high level of difficulty in responding to negative experiences and a low level of tolerance for the problem sat hand, emotional focus coping, external and internal factors, and communication patterns/style with parents.
Strength Evaluation of Functionalized MWCNT-Reinforced Polymer Nanocomposites Synthesized Using a 3D Mixing Approach

The incorporation of carboxyl functionalized multi-walled carbon nanotube (MWCNT- COOH) into a polymethyl methacrylate (PMMA) has been investigated. The resultant tensile and flexural mechanical properties have been determined. In this paper, a novel synthesis process for a MWCNT-reinforced polymer nanocomposite is proposed. The proposed method significantly eliminates the most challenging issues of the nano-dispersed phase, including agglomeration and non-homogeneous mixing within a given matrix material, and also resolves the issues occurring in conventional mixing processes. The results of scanning electron microscopy support these claims. This 3D-mixing process is followed by an extrusion process, using a twin-screw extruder for pristine MWCNT, and a compression molding process for COOH-MWCNT, to prepare test specimens for experimentally determining the mechanical properties. The test specimens are fabricated using 0.1, 0.5, and 1.0 wt. % MWCNT, with a remaining PMMA phase. The testing is conducted according to ASTM D3039 and ASTM D7264 standards. Significant improvements of 25.41%, 35.85%, and 31.75% in tensile properties and 18.27%, 48%, and 33.33% in flexural properties for 0.1, 0.5, and 1.0 wt. % COOH-MWCNT in PMMA, respectively, compared to non-functionalized MWCNTs, were demonstrated. The highest strength was recorded for the nanocomposite with 0.5 wt. % f-MWCNT content, indicating the best doping effect at a lower concentration of f-MWCNT. The proposed CNT-PMMA nanocomposite may be found suitable for use as a scaffold material in the domain of bone tissue engineering research. This type of research possesses a high strength requirement, which may be fulfilled using MWCNT. Furthermore, this analysis also shows a significant amount of enhancement in flexural strength, which is clinically required for fabricating denture bases.
The relative contribution of glottal pulse rate and vocal tract length in size discrimination judgements. P59

FIGURE 5: The inferred size-surface (colour), with contours of constant size (solid lines). The gradients inferred previously from the experiment are shown in red again with their error-bars (red ellipses). The analysis routine fits an nth order polynomial to the partial derivatives at the centre of each ellipse. In this case a 5th order polynomial was used. The gradients of this surface are shown at each sample point (blue arrows) for comparison.
New Essays on the Knowability Paradox

Introduction I. EARLY HISTORY 1. Referee Reports on Fitch's "A Definition of Value" 2. A Logical Analysis of Some Value Concepts 3. Knowability Noir: 1945-1963 II. DUMMETT'S CONSTRUCTIVISM 4. Fitch's Paradox of Knowability 5. The Paradox of Knowability and the Mapping Objection 6. Truth, Indefinite Extensibility, and Fitch's Paradox III. PARACONSISTENCY AND PARACOMPLETENESS 7. Beyond the Limits of Knowledge 8. Knowability and Possible Epistemic Oddities IV. EPISTEMIC AND TEMPORAL OPERATORS: ACTIONS, TIMES AND TYPES 9. Actions That Make us Know 10. Can Truth Out? 11. Logical Types in Arguments about Knowability and Belief V. CARTESIAN RESTRICTED TRUTH 12. Tennant's Troubles 13. Restriction Strategies for Knowability: Some Lessons in False Hope 14. Revamping the Restriction Strategy VI. MODAL AND MATHEMATICAL FICTIONS 15. On Keeping Blue Swans and Unknowable Facts at Bay: a Case Study on Fitch's Paradox 16. Fitch's Paradox and the Philosophy of Mathematics VII. KNOWABILITY RECONSIDERED 17. Performance and Paradox 18. The Mystery of the Disappearing Diamond 19. Invincible Ignorance 20. Two Deflationary Approaches to Fitch-Style Reasoning 21. Not Every Truth Can Be Known (at least, not all at once)
Estimating the Mass of the Milky Way Using the Ensemble of Classical Satellite Galaxies

High precision proper motion (PM) measurements are available for approximately 20% of all known dwarf satellite galaxies of the Milky Way (MW). Here we extend the Bayesian framework of Patel et al. to include all MW satellites with measured 6D phase-space information and apply it with the Illustris-Dark simulation to constrain the MW’s mass. Using the properties of each MW satellite individually, we find that the scatter among mass estimates is reduced when the magnitude of specific orbital angular momentum (j) is adopted, rather than their combined instantaneous positions and velocities. We also find that high j satellites (i.e., Leo II) constrain the upper limits for the MW’s mass and low j satellites, rather than the highest speed satellites (i.e., Leo I and Large Magellanic Cloud), set the lower mass limits. When j of all classical satellites is used to simultaneously estimate the MW’s mass, we conclude the halo mass is 0.85+0.23−0.26 × 1012 (including Sagittarius dSph) and 0.96+0.29−0.28 × 1012 (excluding Sagittarius dSph), cautioning that low j satellites on decaying orbits like Sagittarius dSph may bias the distribution. These estimates markedly reduce the current factor of two spread in the mass range of the MW. We also find a well-defined relationship between host halo mass and satellite j distribution, which yields the prediction that upcoming PMs for ultra-faint dwarfs should reveal j within 5 × 103–104 kpc km s−1. This is a promising method to significantly constrain the cosmologically expected mass range for the MW and eventually M31 as more satellite PMs become available.
Interplay of order-disorder phenomena and diffusion in rigid binary alloys: Monte Carlo simulations of the two-dimensional ABV model

Transport phenomena are studied for a binary (AB) alloy on a rigid square lattice with nearest-neighbor attraction between unlike particles, assuming a small concentration $c_v$ of vacancies $V$ being present, to which $A(B)$ particles can jump with rates $\Gamma_A (\Gamma_B)$ in the case where the nearest neighbor attractive energy $\epsilon_{AB}$ is negligible in comparison with the thermal energy $k_BT$ in the system. This model exhibits a continuous order-disorder transition for concentrations $c_A,c_B=1-c_A-c_V$ in the range $c_{A,1}^{crit}\leq c_A \leq c_{A,2}^{crit}$, with $c_{A,1}^{crit}=(1-m^*-c_V)/2$, $c_{A,2}^{crit} =(1+m^*-c_V)/2$, $m* \approx 0.25$, the maximum critical temperature occurring for $c*=c_A=c_B=(1-c_V)/2$, i.e. $m^*=0$. This phase transition belongs to the $d=2$ Ising universality class, demonstrated by a finite size scaling analysis. From a study of mean-square displacements of tagged particles, self-diffusion coefficients are deduced, while applying chemical potential gradients allow the estimation of Onsager coefficients. Analyzing finally the decay with time of sinusoidal concentration variations that were prepared as initial condition, also the interdiffusion coefficient is obtained as function of concentration and temperature. As in the random alloy case (i.e., a noninteracting ABV-model) no simple relation between self-diffusion and interdiffusion is found. Unlike this model mean field theory cannot describe interdiffusion, however, even if the necessary Onsager coefficients are estimated via simulation.
Living innovation machines: modelling innovation in time and space variable-geometry territorial units using machine learning

ABSTRACT This paper investigates the innovative intensity (iMID effect) in the local production systems (LPSs) using dynamic territorial units that modifies their geographical boundaries and specialization over time. The paper is based on the idea that the local communities are the real unit of generation of innovation and that they are constantly changing, behaving like a ‘living innovation machine’. To explore this dynamic relationship, the paper applies the Marshallian industrial district (MID) as an approach to industrial change. Then, it focuses on the Marshallian industrial districts (MIDs) as a type of LPS and asks how the innovation effect changes in MIDs and other types of LPSs when dynamic territorial units are used. The differences in innovation intensity between the different types of LPSs are explained for Spain in the period 1991–2014 using new methods of analysis that combine causal analysis, a variable and adaptive geometry of territorial units and industrial specialization, and machine learning methods. The results show that the transformation of an LPS into another type of LPS does not automatically imply a change in innovative capacity, and the type of LPS of origin continues to be relevant in explaining current innovation processes.
CCD photometry and the stellar content of the central region of IC 1805

Images of the central region of the open cluster IC 1805 were made with a 2033 x 2044 Kodak CCD imager using broad-band filters corresponding closely to the standard B, V, R, I, system of Johnson. Calibrated magnitudes were measured for 136 stars in the cluster, and temperatures and masses were estimated for 115 of these. A mass function was derived as defined by Scalo (1986) and is compared with an earlier determination for this cluster. The mass function also is compared with that of a similar star-forming region in Cygnus and with the initial mass function of field stars. A brief overview of CCD design and operation is included, along with some specifics about the R.I. T. camera, image reduction, and photometry procedures.
Drag reduction characteristics of small amplitude rigid surface waves

The possibility of reducing drag by using rigid, wavy surfaces is investigated both analytically and experimentally. Although pressure drag for rigid sine-wave surfaces can be predicted empirically, viscous drag for even shallow waves was poorly predicted by state-of-the-art turbulent boundary layer calculation procedures. Calculations for the effects of geometric and fluid variables on total wave drag are presented under the philosophy that trends will be nearly correct even though levels are probably incorrect. Experiments by the present authors indicate that a total drag reduction with wavy walls is possible.
Orbital order in La0.5Sr1.5MnO4: beyond a common local Jahn-Teller picture

The standard way to find the orbital occupation of Jahn-Teller (JT) ions is to use structural data, with the assumption of a one-to-one correspondence between the orbital occupation and the associated JT distortion, e.g., in O${}_{6}$ octahedron. We show, however, that this approach can be incorrect, e.g., for layered systems. Using the layered manganite La${}_{0.5}$Sr${}_{1.5}$MnO${}_{4}$ as an example, we found from our x-ray-absorption measurements and electronic structure calculations that the type of orbital ordering strongly contradicts the standard local distortion approach for the Mn${}^{3+}$O${}_{6}$ octahedra, and that the usually ignored long-range crystal-field effect and anisotropic hopping integrals are actually crucial for determining the orbital occupation.
Studying the Development of Navigation Using Virtual Environments

ABSTRACT Research on spatial navigation is essential to understanding how mobile species adapt to their environments. Such research increasingly uses virtual environments (VEs) because, although VE has drawbacks, it allows for standardization of procedures, precision in measuring behaviors, ease in introducing variation, and cross-investigator comparability. Developmental researchers have used a wide range of VE testing methods, including desktop computers, gaming consoles, virtual reality, and phone applications. We survey the paradigms to guide researchers’ choices, organizing them by their characteristics using a framework proposed by Girard (2022) in which navigation is reactive or deliberative, and may be tied to sensory input or not. This organization highlights what representations each paradigm indicates. VE tools have enriched our picture of the development of navigation, but much research remains to be done, e.g., determining retest reliability, comparing performance on different paradigms, validating performance against real-world behavior and open sharing. Reliable and valid assessments available on open-science repositories are essential for work on the development of navigation, its neural bases, and its implications for other cognitive domains.