Miracle-dz/UniFAR-FTUs huggingface dataset:
Whispering gallery optical parametric oscillators: Just a scientific oddity?

Optical parametric oscillators (OPOs) convert the frequency of laser light to almost arbitrary values. Nowadays, they serve as wavelength-agile light sources for spectroscopic applications as well as photon generators for quantum-optical experiments. Conventional OPOs are based on a nonlinear-optical crystal surrounded by a mirror cavity. Regarding the cavity, one often finds the following rule of thumb: the more waves are resonant, the lower is the oscillation threshold and the more difficult is the wavelength tuning. In whispering-gallery-resonator-based OPOs (WGR OPOs), light is guided by total internal reflection in a millimeter-sized spheroidally-shaped nonlinear-optical crystal. Thus, these devices are intrinsically triply resonant. Indeed, they provide microwatt-level oscillation thresholds, i.e., the lowest values of all OPO configurations. However, following the abovementioned rule, their applicability in fields beyond fundamental science might be questionable, because the most striking feature of an OPO, i.e., the wavelength tunability, is hampered. Nevertheless, several experimental studies revealed that the output wavelengths of WGR OPOs could be tuned in well-defined steps over hundreds of nanometers by temperature variation. Combined with strategies for mode-hop free tuning, it is possible, e.g., to tune the output wavelength in a controlled way until it meets MHz-wide resonances. This is sufficient for high-resolution spectroscopy. WGR OPOs are nowadays operated around various center frequencies, covering the visible-to-mid-infrared spectral range. These light sources - despite of their intrinsic triple resonance - might serve as compact and wavelength-agile devices for various applications.
Folsom: New Archaeological Investigations of a Classic Paleoindian Bison Kill

In the late 1920s outside a sleepy remote New Mexico village, prehistory was made. Spear points, found embedded between the ribs of an extinct Ice Age bison at the site of Folsom, finally resolved decades of bitter scientific controversy over whether the first Americans had arrived in the New World in Ice Age times. Although Folsom is justly famous in the history of archaeology for resolving that dispute, for decades little was known of the site except that it was very old. This book for the first time tells the full story of Folsom. David J. Meltzer deftly combines the results of extensive new excavations and laboratory analyses from the late 1990s, with the results of a complete examination and analysis of all the original artifacts and bison remains recovered in the 1920s - now scattered in museums and small towns across the country. Using the latest in archaeological method and technique, and bringing in data from geology and paleoecology, this interdisciplinary study provides a comprehensive look at the adaptations and environments of the late Ice Age Paleoindian hunters who killed a large herd of bison at this spot, as well as a measure of Folsom's pivotal role in American archaeology.
Scientific Approach of Prediction for Professions Using Machine Learning Classification Techniques

: Astrology is a very ancient and traditional method of prediction that increases the interest of people continuously. The globe today, there are no common guidelines or principles for astrological prediction. Rather than setting universal principles and criteria for astrological prediction, astrologers focus on providing high-quality services to individuals but there is no guarantee of accuracy. Machine learning is providing the best result for analysis and prediction on many applications by the learning of computers. Prediction and classification make it possible for any learner to work on large, noisy, and complex datasets. The main motive of the paper is to introduce a scientific approach that reduces the drawback of the traditional approach and indicates the universal rules of prediction and proves the validity of astrology by the three classification techniques, Naïve Bayes, Logistic-R, and J48. It is a part of supervision learning that operates with cross-validation 10,12, and 14fold for calculating the terms 1) correctly classified instances (CCI), erroneously categorized instances (ECI), Mean absolute error (MAE), Root mean squared error (RMSE), and Relative absolute error (RAE). 2) True Positive Rate, False Positive Rate, Precision, and F-Measure values. 3) The MCC, ROC, and PRC area values. 4) To calculate the average weight of the three-class label professor, businessman, and doctor in terms of true positive rate, false-positive rate, precision, F-measure, PRC, and ROC area, 5) finally, we calculated the accuracy of each classification technique and compare which provide the better result. For this, we have collected the date of birth, place of birth, and time of birth of 100 persons who belong to different professions. 40 data of professors, 30 data of businessmen, and 30 data of doctors, prepare the horoscope of an individual with the help of software. For analysis, we create the datasheet in . csv format and apply this data sheet in the weka tool to check various parameters and the accuracy percentage of each classifier.
Transverse instability of gravity–capillary solitary waves on deep water in the presence of constant vorticity

The bifurcation of two-dimensional gravity–capillary waves into solitary waves when the phase velocity and group velocity are nearly equal is investigated in the presence of constant vorticity. We found that gravity–capillary solitary waves with decaying oscillatory tails exist in deep water in the presence of vorticity. Furthermore we found that the presence of vorticity influences strongly (i) the solitary wave properties and (ii) the growth rate of unstable transverse perturbations. The growth rate and bandwidth instability are given numerically and analytically as a function of the vorticity.
UAV Tracking Based on Correlation Filters With Dynamic Aberrance-Repressed Temporal Regularizations

As a significant research direction in remote sensing fields, unmanned aerial vehicles (UAVs) tracking has achieved rapid development in recent years. However, due to limited power and computation resources on aerial platforms, the tracking methods deployed on UAVs usually require high computational efficiency and performance. In addition, various challenges (i.e., similar object, background clutter, and occlusion) have inevitably occurred during the UAV tracking phase. Therefore, considering the above issues comprehensively, this article proposes a dynamic aberrance-repressed temporal regularized correlation filter (CF) to achieve stable tracking in UAV remote sensing videos. First, we have introduced the aberrance-repressed temporal regularizations into the discriminative CF framework. Second, a novel objective loss function is constructed to adjust the strength of each regularization for training the filter. Then, a new judgment mechanism based on the response variation is exploited to reflect the response fluctuation and applied to tune parameters of both regularizations. Finally, comprehensive experiments are done on three different UAV benchmarks, i.e., UAV123@10fps, UAVDT, and VisDrone2018, to verify the performance of our tracker and have demonstrated that our tracker achieves superior performance against other total 25 state-of-the-art trackers while reaching $\sim$35 FPS on a single CPU.
Relationship of Neural Correlates of Gait Characteristics and Cognitive Dysfunction in Patients with Mild Cognitive Impairment

Background: Some patients with mild cognitive impairment (MCI) experience gait disturbances. However, there are few reports on the relationship between gait disturbance and cognitive function in patients with MCI. Therefore, we investigated the neural correlates of gait characteristics related to cognitive dysfunction. Methods: Eighty patients diagnosed with MCI from three dementia centers in Gangwon-do, Korea, were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of 0.5 or higher, with a memory domain score of 0.5 or greater. The patients were classified as having either higher or lower MMSE and the groups were based on their Mini Mental Status Examination z-scores. Multiple logistic regression analysis was performed to examine the association between the gait characteristics and cognitive impairment. Analyses included variables such as age, sex, years of education, number of comorbidities, body mass index, and height. Results: Gait velocity, step count, step length, heel-to-heel base support, swing and stance phase duration, and support time were associated with cognitive function. A decrease in gray matter volume in the right pericalcarine area was associated with gait characteristics related to cognitive dysfunction. An increase in the curvature of gray matter in the right entorhinal, right lateral orbitofrontal, right cuneus, and right and left pars opercularis areas was also associated with gait characteristics related to cognitive dysfunction. Conclusion: Since gait impairment is an important factor in determining activities of daily living in patients with mild cognitive impairment, the evaluation of gait and cognitive functions in patients with mild cognitive impairment is important.
Revealing Their True Stripes: Mg/Ca Banding in the Paleogene Planktonic Foraminifera Genus Morozovella and Implications for Paleothermometry

The Mg/Ca ratio of foraminiferal calcite is a widely used empirical proxy for ocean temperature. Foraminiferal Mg/Ca‐temperature relationships are based on extant species and are species‐specific, introducing uncertainty when applying them to the fossil tests of extinct groups. Many modern species show remarkable heterogeneity in their intra‐test Mg distributions, typically due to the presence of high Mg bands, which have a biological origin. Importantly, banding patterns differ between species, which could affect Mg/Ca‐temperature relationships. Few studies have looked at intra‐test variability in Mg/Ca ratios in extinct species of foraminifera, despite the obvious implications for paleothermometry. We used electron probe microanalysis (EPMA) to investigate intra‐test Mg distributions in the fossil tests of two species of planktonic foraminifera from the extinct muricate mixed‐layer‐dwelling genus Morozovella, commonly used in Paleogene sea surface temperature reconstructions. Both M. aragonensis and M. crater show striking Mg banding patterns with multiple high and low Mg/Ca band pairs throughout the test wall in all chambers. The intra‐test Mg variability in M. aragonensis and M. crater is similar to that in modern species widely used in paleoclimate reconstructions and banding patterns are consistent with published growth models for modern forms, albeit with subtle differences. The presence of Mg bands supports the application of Mg/Ca‐palaeothermometry in extinct Morozovella species as well as the utility of EPMA for examining preservation of foraminifera tests in paleoclimatological studies. However, we emphasize the importance of rigorous assessments of inter‐ and intra‐test Mg variability when using microanalytical techniques for foraminiferal Mg/Ca paleothermometry.
Research on point cloud simplification algorithm for ring forgings based on joint entropy evaluation

There are numerous redundant points in the point cloud model of ring forgings obtained by 3D laser scanner. How to remove the redundant points while keeping the model characteristics unchanged is a critical issue. This paper proposes a point cloud simplification algorithm based on the joint entropy evaluation theory. Firstly, the K-D tree is used to search for the K-neighbors of the sampled points. Secondly, a surface is fitted to the spatial neighborhood of the sampled points using the least squares method. The curvature operator of the sampled points is derived on the fitted surface using Riemannian geometry theory. After that, an energy operator is defined by using the normal vectors and distances of the sampled points and their neighborhood points. The joint entropy values of all points in the model are determined based on the probability distributions of these two operators in the local neighborhood. Finally, the data points are sorted by entropy value. Data points with high entropy values are put into the data set U1. Data points with low entropy values are clustered through the K-Means algorithm of swarm optimization. The redundant points outside the cluster centers are removed, and the cluster centers are put into the data set U2. The final simplification results are obtained by integrating data sets U1 and U2. The experimental results show that the point cloud simplification algorithm proposed in this paper is effective and feasible.
An algebraic version of the active disturbance rejection control for second-order flat systems

An algebra-based active disturbance rejection control approach for uncertain second-order flat systems, perturbed by a matching perturbation, is presented. This approach consists of proposing an online algebraic estimator for the uncertain system, together with an algebraic reconstructor for the unknown velocity. To assess the efficiency of the approach, numerical simulations to control an uncertain longitudinal vehicle system were carried out.
Optimal Path Planning on the Three-Input Six-Dimensional Brockett’s Canonical System

This paper addresses an optimal path planning problem on the three-input six-dimensional Brockett’s canonical system. This class of systems can be applied to control the position and orientation of a rigid body in SE, such as spacecraft, aerial vehicles, or underwater vehicles, using only three inputs. Since the number of inputs is less than the total number of degrees of freedom, it raises non-trivial technical issues in finding the actual time sequence of control inputs. Here we show that the shortest paths connecting two points are parametrized as helix paths by introducing the input quadratic norm as a Riemannian metric. In addition, we present a quasi-analytical procedure to determine the optimal helix path for any given target point. The characteristic feature of our method is that the optimal paths are parametrized as an explicit function on the state space, which enables the solution paths to be derived without multidimensional iterations. The approach was validated by numerical computations in two aspects: matching for arbitrary target points and covering known optimal paths as special cases. The result that the shortest paths are represented by helices may also help as guidance for solving more general problems numerically, for example, as an initial solution or as a measure on the state space.
JSE Delisted Companies' Use of Impression Management Practices in the Chairman’s Statement and Audit Committee Report Preceding Delisting from the 2016-2021 Period

The study examined whether Johannesburg Stock Exchange (JSE Ltd) delisted companies used impression management in the chairman’s statements and audit committee's reports preceding delisting from 2016 to 2021. There is a concerning trend of delisting from JSE, which may be voluntary or compulsory. The chairman’s statement is highly ranked as the most read voluntary narrative disclosure statement. Furthermore, as assurance providers and governance structure, the audit committee is expected to assure the organisation as a whole. The study uses quantitative content analysis on integrated reports of the JSE-delisted companies from 2016 to 2021. Impression management is examined for length, use of passive voice, and the use of personal references in the chairman’s statement and audit committee report. The study examined and provided insight into impression management practices used by delisted companies and ascertains whether there is a systematic difference in the use of impression management between profitable and unprofitable in the year preceding delisting. The study shows that delisted companies used impression management on the verge of delisting and this opportunistic behavior was used by both boards of directors and audit committees. This study contributes to the novelty of knowledge on impression management. It is the first of its kind.
Aging and the media in Spain: Reinforcement of ageism in times of COVID-19

The COVID-19 pandemic has made older adults one of the main foci of media. This article explores age-related language through a comparative analysis of headlines in the five highest-circulation Spanish newspapers during the first and second waves of the 2020 pandemic and the 2 years before the pandemic. The results show a decrease in the frequency of headlines that represent older people as subjects of an action associated to positive affection, as well as an increase in representation of older adults as a homogenous group in a negative way, and an increase in ageist terms, especially “elders. ” We discuss to what extent the COVID-19 pandemic can reinforce ageism and the possible repercussions.
Naked Oat and Fusarium culmorum (W.G.Sm.) Sacc. Responses to Growth Regulator Effects

The antioxidant defense system can be stimulated by growth regulators in plants when they are under stress, such as exposure to pathogens. There are a lot of natural growth regulators on the market, but no research has been carried out yet to determine how effective they are. This field and laboratory study examines the impact of two commonly used Russian growth regulators, Crezacin and Zircon, along with artificial infection with Fusarium culmorum on the antioxidant system of naked oat. The results show that, compared to the control, Crezacin-treated plants had higher contents of low molecular weight fructose and nonenzymatic antioxidants like proline, phenolic compounds, and flavonoids. Zircon-treated plants had a lower content of proline, carbohydrates, and lower total antioxidant activity than the control plants. The obtained data show that Crezacin treatment mainly affected nonenzymatic systems of the antioxidant defense. This treatment was more successful than the Zircon application, which did not show any appreciable effectiveness and was typically associated with an improvement in oat productivity. The treatment with growth regulators and a fungal suspension performed at the flowering phase provided the best effect on the biochemical parameters and productivity of naked oats. Moreover, oat treatment with the pathogen promoted the reproductive capabilities of the plants, while growth regulators helped in avoiding infectious stress.
SERS with Flexible β-CD@AuNP/PTFE Substrates for In Situ Detection and Identification of PAH Residues on Fruit and Vegetable Surfaces Combined with Lightweight Network

The detection of polycyclic aromatic hydrocarbons (PAHs) on fruit and vegetable surfaces is important for protecting human health and ensuring food safety. In this study, a method for the in situ detection and identification of PAH residues on fruit and vegetable surfaces was developed using surface-enhanced Raman spectroscopy (SERS) based on a flexible substrate and lightweight deep learning network. The flexible SERS substrate was fabricated by assembling β-cyclodextrin-modified gold nanoparticles (β-CD@AuNPs) on polytetrafluoroethylene (PTFE) film coated with perfluorinated liquid (β-CD@AuNP/PTFE). The concentrations of benzo(a)pyrene (BaP), naphthalene (Nap), and pyrene (Pyr) residues on fruit and vegetable surfaces could be detected at 0.25, 0.5, and 0.25 μg/cm2, respectively, and all the relative standard deviations (RSD) were less than 10%, indicating that the β-CD@AuNP/PTFE exhibited high sensitivity and stability. The lightweight network was then used to construct a classification model for identifying various PAH residues. ShuffleNet obtained the best results with accuracies of 100%, 96.61%, and 97.63% for the training, validation, and prediction datasets, respectively. The proposed method realised the in situ detection and identification of various PAH residues on fruit and vegetables with simplicity, celerity, and sensitivity, demonstrating great potential for the rapid, nondestructive analysis of surface contaminant residues in the food-safety field.
Stabilisation of state-and-input constrained nonlinear systems via diffeomorphisms: A Sontag's formula approach with an actual application

In this work, we provide a new and constructive outlook for the control of state-and-input constrained nonlinear systems. Previously, explicit solutions have been mainly focused on the finding of a barrier-like Lyapunov function, whereas we propose the construction of a diffeomorphism to map all the trajectories of the constrained dynamics into an unconstrained one. Careful analysis has revealed that only some foundations of differential geometry and a technical assumption are necessary to construct the proposed methodology based on the well-established theories of control Lyapunov functions and Sontag's universal formulae. Altogether, it allows us to obtain an explicit solution that even includes bounded constraints in the control action, giving the designer a way to decide (to some extent) the trade-off between control saturations and robustness. Moreover, this approach does not rely on the own structure of the system dynamics, therefore covering a broad class of nonlinear systems. The main advantage of this approach is that the use of a diffeomorphism allows the splitting of the mathematical treatment of the constraint and the Lyapunov controller design. The result has been successfully applied to solve the dynamic positioning of an actual ship, where the nonlinear state constraints describe a strait. This approach enabled us to design a control Lyapunov function and thereby use Sontag's formula to solve the stabilisation problem. Realistic simulations have been executed in a real scenario on the simulator owned by an international shipbuilding company.
Soil Characterization and P-Y Curve Development for Loess

Lateral loads on drilled shafts are often the controlling factor in their design. These lateral loads are transferred to the surrounding soil or rock, and estimation of the capacity of the shaft to resist lateral loads is a critical part of the design. The lateral load-deformation relationship of a drilled shaft and its supporting soil is commonly modeled using the p-y curve method. P-y curves vary with soil type, deposition characteristics and depth, but general curves have been developed to represent common soils. Unfortunately, no p-y curves have been developed to represent the behavior of loess, cemented silt that is common throughtout much of Kansas. This lack of available p-y relationships has meant that less applicable curves, normally those for sandy soils, must be used. The purpose of this research was to define the significant engineering properties of Kansas' loessal soils through a literature review, laboratory tests, and in situ tests and to determine the soil-structure response by performing full scale lateral load tests on six drilled shafts. Laboratory testing included saturated and unsaturated triaxial, direct shear, consolidation and collapse testing. Field tests included standard penetration tests (SPT), cone penetration tests (CPT), vane shear, and pressuremeter testing. Two pairs of shafts with diameters of 30 and 42 in. were tested under static loading. A third pair of 30 in. shafts was tested under repeated loading. Shaft deflections were measured using inclinometer soundings and correlated with the CPT cone tip resistance (q sub c). A hyperbolic model was developed to correlate ultimate soil resistance (P sub uo) to the CPT cone tip resistance (q sub c) for both static and repeated loading at any given depth and was used to develop a family of p-y curves unique to loess. This model may be entered into the commercially available software package LPILE for design of laterally loaded drilled shafts constructed in loess.