Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved parameter inference in catchment models: 2. Combining different kinds of hydrologic data and testing their compatibility

Often some of the parameters of catchment models fitted to runoff data are poorly determined thereby making the task of developing useful regionalization relationships more difficult. The Bayesian methodology developed in part 1 is extended to utilize several kinds of hydrologic data in parameter inference, the goal being to improve the precision of poorly determined parameters. The concept of compatibility is developed using statistical hypothesis tests. Different kinds of data are said to be compatible if differences between their fitted parameters are not statistically significant. The pooling of incompatible data may undermine the model's ability to predict runoff and also induce bias in the parameters. A hierarchy of three levels of information is introduced to enable systematic checking for compatibility. Finally, a case study is presented. Using data on runoff, soil moisture, and interception, it is shown that substantial reductions in parameter uncertainty can be realized; also the importance of compatibility testing is demonstrated.
Variational approach to nonlinear pulse switching in a dispersion-imbalanced loop mirror

Summary form only given. Recently, a series of novel ultrashort pulse sources have been developed on the basis of the dispersion-imbalanced fiber loop mirror (DILM). However, a detailed theoretical description of the DILM has not been accomplished to date. We believe we present the first results of such a consideration, based on the variational approach.
Oxyyttrobetafite–(Y), Y2Ti2O6O, a new mineral of the pyrochlore supergroup in a pegmatite from Souri Valley, Komono, Mie Prefecture Japan

Oxyyttrobeta ﬁ te – (Y) is the ﬁ rst member in the beta ﬁ te group of the pyrochlore supergroup found in albite – rich pegmatite from Souri Valley, Komono, Mie Prefecture, Japan. This new mineral occurs as small anhedral grains with sizes of 20 to 200 µm in cylinder – shaped aggregates with a substrate of thalénite – (Y) and synchysite – (Y). Small amounts of aeschynite – (Y), thorianite, and thorite are also associated in the same occurrence with oxyyttrobeta ﬁ te – (Y), and gadolinite – (Y) is also included at the boundary between the aggregate and albite. The physical properties are: brown in color, brittle, transparent, non – ﬂ uorescent, vitreous luster, white streak with a Mohs hardness of 5, and a calculated density of 5.54 g·cm − 3 . Oxyyttrobeta ﬁ te – (Y) is an optically isometric material with brown color under the microscope with a refractive index of n = 2.3 calculated using the Gladstone – Dale relationship. The empirical formula of oxyyttrobeta ﬁ te – (Y) calculated on the basis of B = 2 with A 2 B 2 X 6 Y composition is (Y 1.58 Dy
Neural dynamics of speech perception: Phonemic restoration in noise using subsequent context.

Phonemic restoration describes a class of auditory illusions during which broadband noise replacing a deleted phoneme can cause the perceptual restoration of the deleted phoneme. Phonemic restoration exemplifies the brain’s ability to complete and understand speech and language in noisy environments. It also clarifies how both past and future acoustical events can contextually guide completion of a percept that is occluded by noise, and highlights that conscious speech is due to bottom‐up and top‐down contextual interactions that can operate across hundreds of milliseconds. This work develops a neural model that quantitatively simulates restoration phenomena, including the forward development in time of a conscious speech percept even in cases where future events control how previously presented acoustic events are heard. The model clarifies how acoustic items are stored in short‐term working memory, and how they interact reciprocally with unitized representations of item sequences, or list chunks, to gen.
Long-Term Traffic Forecasting in Optical Networks Using Machine Learning

— Knowledge about future traffic in backbone optical networks may greatly improve a range of tasks that Communications Service Providers (CSPs) have to face. This work proposes a procedure for long-term traffic forecasting in optical networks. We formulate a long-terT traffic forecasting problem as an ordinal classification task . Due to the optical networks’ (and other network technologies’) characteristics, traffic forecasting has been realized by predicting future traffic levels rather than the exact traffic volume. We examine different machine learning (ML) algorithms and compare them with time series algorithms methods. To evaluate the developed ML models, we use a quality metric, which considers the network resource usage. Datasets used during research are based on real traffic patterns presented by Internet Exchange Point in Seattle. Our study shows that ML algorithms employed for long-term traffic forecasting problem obtain high values of quality metrics. Additionally, the final choice of the ML algorithm for the forecasting task should depend on CSPs expectations.
Investigation of simplified thermal expansion models for compressible Newtonian fluids applied to nonisothermal plane Couette and Poiseuille flows

In this paper six different theories of a Newtonian viscous fluid are investigated and compared, namely, the theory of a compressible Newtonian fluid, and five constitutive limits of this theory: the incompressible theory, the limit where density changes only due to changes in temperature, the limit where density changes only with changes in entropy, the limit where pressure is a function only of temperature, and the limit of pressure a function only of entropy. The six theories are compared through their ability to model two test problems: (i) steady flow between moving parallel isothermal planes separated by a fixed distance with no pressure gradient in the flow direction, and (ii) steady flow between stationary isothermal parallel planes with a pressure gradient. The incompressible theory admits solutions to these problems of the plane Couette/Poiseuille flow form: a single nonzero velocity component in a direction parallel to the bounding planes, and velocity and temperature varying only in the direct.
SPECIAL SECTION: SEXUAL HEALTH IN GAY AND BISEXUAL MEN Neighborhood-Level Associations with HIV Infection AmongYoung MenWhoHave Sex withMen in Chicago

The rising incidenceofHIV infectionamongyoung men who have sex with men (YMSM) is a substantial public health concern.Traditional researchonHIVamongYMSMhas focused largely on individual-level predictors and infrequently accounts for contextual or neighborhood-level factors such as ethnic composition and socioeconomic status. This study used neighborhood-level data from the US Census and other public sources, and individual-level data from a longitudinal cohort of YMSM in Chicago (Crew 450). Of the original 450 YMSM in the cohort, 376 reported living in Chicago (83.6%) and were included in the analytic sample.A clustering approachwas used togroupthe77communityareas togetherbycommoncharacteristics, resulting in the identification of 11 distinct clusters. An unconditional model of individual HIV status indicated a significant amountofvarianceexistedbetweenneighborhoodclusters (v=21.66; p=0.006). When individual-level variables were added to themodel, only having anHIV-positive sex partner (OR=6.41; CI 2.40, 17.1) and engaging in exchange sex in the past 6months (OR=3.25; 95% CI 1.33, 7.93) were significant predictors of HIV status. Clusters with higher Walk Scoreswere less likely to containHIV-positive individuals (OR= 0.94; 95% CI 0.90, 0.98). Conversely, clusters with a larger proportionofvacant buildingsweremore likely to containHIVpositive individuals (OR= 1.19; 95%CI1.07, 1.33). Future researchamongYMSMneeds to investigate themechanismsby which neighborhood of residence might influence engagement in risk behaviors or acquisition of HIV.
Optimal sensor placement based on substructure sensitivity

Optimal sensor placement is key issues of structures health monitoring (SHM). In study of sensor placement, the main achievement focus on optimal criterions of sensor locations based on modal test, while optimal criterions of sensor locations based on damage identification, optimal method of sensor locations and optimal sensor number should be investigated further. In this study, a novel optimal sensor placement strategy based on sensitivity is proposed. Optimal sensor placement based on sensitivity analysis is an alternation method to consider damage identification. The basic idea of the proposed methodology is that influence range of different damage parameters is different. First, damage sensitivities in every element based on modal parameters are calculated. Then the elements that are sensitive to damage are selected. According to the detection of damage sensitivity in these elements, minimums number can be found by sensitivity. At last, the elements that are not selected are considered as not sensitive to modal parameters and would be placed the strain sensors. Numerical simulation of a three-dimensional truss structure is implemented to evaluate the minimum sensor number of different damage parameters according to the above methods. Moreover, damage location can be detected under singledamage situation and the element with most severe damage can be identified in multi-damage case using the proposed sensor placement.
An Enhanced Version of Delayed Detached-Eddy Simulation Based on the v 2 − f Model

To overcome the scale discontinuity of the Delayed Detached-eddy simulation (DDES) based on the v 2 − f Reynolds-averaged Navier-Stokes (RANS) model developed by Jee and Shariff (International Journal of Heat and Fluid Flow 46(2014) 84), an improvement is proposed in the present work. For the new DDES formulation, the scale discontinuity is avoided in the transition region and the RANS mode is correctly recovered for the shielded region. However, the numerical stability of the new DDES formulation is poor, and the relaxation factor in some locations is extremely large. To improve the numerical stability, the underlying v 2 − f RANS model is modified. Besides, a damping function is introduced to damp the RANS region when the grid resolution is fine enough and the flow is filled with an abundance of turbulence. Numerical simulations are carried out for some typical wall-bounded flows and special attention is paid to distinguish the effect of the damping function to the resolution capability of the flowfields.
Microwave Dielectric Properties of V2O5–Doped (1-x)La(Mg0.5Sn0.5)O3-xCaTiO3 Ceramic System

The microwave dielectric properties of V2O5–doped (1-x)La(Mg0.5Sn0.5)O3-xCaTiO3 ceramic system prepared by the conventional solid-state method were investigated with a view to their potential for mobile communication. The X-ray diffraction peaks of (1-x)La(Mg0.5Sn0.5)O3-xCaTiO3 shifted to higher angles as x increased from 0.4 to 0.7. The X-ray diffraction patterns of the 0.4La(Mg0.5Sn0.5)O3–0.6CaTiO3 revealed no significant variation of phase with sintering temperatures. The average grain size of the 0.4La(Mg0.5Sn0.5)O3–0.6CaTiO3 increased from 3.1 to 8.6 μm as the sintering temperature increased from 1400 to 1550°C. The dielectric constant increased from 28.5 to 48.7 and the quality factor (Q × f) decreased from 46,800 to 22,900 GHz for (1-x)La(Mg0.5Sn0.5)O3-xCaTiO3 as x increased from 0.4 to 0.7 that were sintered at 1550°C for 4h. The average value of temperature coefficient of resonant frequency (τf ) increased from −56 to +46 ppm/°C as x increased from 0.4 to 0.7.
CYCLOPS: CYCLICAL DEVELOPMENT TOWARDS OPERATIONALIZING ML MODELS FOR HEALTH

Open source software that enable research and development of machine learning (ML) models for clinical use cases are fragmented, poorly maintained and fall short in functionality. CyclOps is a software framework designed to address this gap and help accelerate the development of ML models for health. In this paper, we describe the architecture, APIs and implementation details of CyclOps, while providing benchmarks on example clinical use cases. We emphasize that CyclOps is developed to be researcher friendly, while providing APIs for building end-to-end pipelines for model development as well as deployment. We adopt software engineering and ML operations (MLOps) best practices, while providing support for handling large volumes of health data. The design of the framework is centered around the notion of iterative and cyclical development of the overall ML system, which consists of data, model development and monitoring pipelines. The core CyclOps package can be installed through the Python Package Index (PyPI) and the source code is available at https://github.com/VectorInstitute/cyclops.
What are we learning with Yoga: a text mining approach to literature

Techniques used in yoga existed long before science as we know it. However, with Yoga westernization, the proliferation of scientific studies addressing the subject is exponential. Even though the literature presents thousands of related articles, many studies are considered flimsy - the diversity of methods, areas of interest, and focus cause it to become a complex environment without general guidelines for the researcher. This status may represent one of the impediments to the field's evolution. This study aims to elaborate a global structure of the literature on Yoga to open the door for multidisciplinary collaboration and bring new light to some relevant aspects. Due to its complexity, we understand that techniques to model complex domains are necessary. Contemporary methods of Artificial Intelligence have promoted advances in Bioinformatics, including text mining to scientific literature. Through the vector representation of texts, we got semantic abilities and could organize data in a way that allowed us to acquire a global vision of this literature. Additionally, we made the platforms available to Yoga researchers to enable them to evaluate our findings and make their forays into the literature. Besides better understanding why we study Yoga, we discovered that the literature offers insights into the relationships in broader aspects.
Scoping Review of Methods and Annotated Datasets Used to Predict Gender and Age of Twitter Users

Real World Data (RWD) has been identified as a key information source in health and social science research. An important, and readily available source of RWD is social media. Identifying the gender and age of the authors of social media posts is necessary for assessing the representativeness of the sample by these key demographics and enables researchers to study subgroups and disparities. However, deciphering the age and gender of social media users can be challenging. We present a scoping review of the literature and summarize the automated methods used to predict age and gender of Twitter users. We used a systematic search method to identify relevant literature, of which 74 met our inclusion criteria. We found that although methods to extract age and gender evolved over time to utilize deep neural networks, many still relied on more traditional machine learning methods. Gender prediction has achieved higher reported performance, while prediction of age performance lags, particularly for more granular age groups. However, the heterogeneous nature of the studies and the lack of consistent performance measures made it impossible to quantitively synthesize results. We found evidence that data bias is a prevalent problem and discuss suggestions to minimize it for future studies.
Piezoelectric response of thin films determined by charge integration technique : Substrate bending effects

Unexpectedly high-longitudinal piezoelectric coefficients have recently been reported in c-axis oriented Pb(Zr,Ti)O3 thin films with morphotropic phase boundary composition [Fu et al., Appl. Phys. Lett. 80, 3572 (2002)]. Our analysis and experimental results show that, in comparison with other methods commonly used to investigate piezoelectric response of thin films, the charge integration technique used by Fu et al. may lead to an order of magnitude higher apparent piezoelectric coefficients if the substrate on which the film was deposited is bent. When this is the case, the large response is due to the transverse piezoelectric effect caused by the substrate bending.
The Feasibility of a Primary Care Based Navigation Service to Support Access to Health and Social Resources: The Access to Resources in the Community (ARC) Model

Introduction: We established a patient centric navigation model embedded in primary care (PC) to support access to the broad range of health and social resources; the Access to Resources in the Community (ARC) model. Methods: We evaluated the feasibility of ARC using the rapid cycle evaluations of the intervention processes, patient and PC provider surveys, and navigator log data. PC providers enrolled were asked to refer patients in whom they identified a health and/or social need to the ARC navigator. Results: Participants: 26 family physicians in four practices, and 82 of the 131 patients they referred. ARC was easily integrated in PC practices and was especially valued in the non-interprofessional practices. Patient overall satisfaction was very high (89%). Sixty patients completed the post-intervention surveys, and 33 reported accessing one or more service(s). Conclusion: The ARC Model is an innovative approach to reach and support a broad range of patients access needed resources. The Model is feasible and acceptable to PC providers and patients, and has demonstrated potential for improving patients’ access to health and social resources. This study has informed a pragmatic randomized controlled trial to evaluate the ARC navigation to an existing web and telephone navigation service (Ontario 211).
Non-linear piezoelectric resonance analysis using burst mode: a rigorous solution

The burst mode experiment is commonly used to measure non-linear piezoelectric material properties. However, the theory that is often employed is highly simplified, making use of linear results. Here we represent a more rigorous theory based closely on the underlying non-linear partial differential equations. Since time domain solutions are not available analytically, the approach is in two parts: the PDE is solved in the frequency domain, then an auxilliary non-linear ordinary differential equation is solved in the time domain. Comparison of the two yields the material parameters. Also, we suggest the excitation portion of the I(t) curve be studied rather than the decay part normally used since the former contains more features, has a well-defined initial condition (current and charge both zero) and is less susceptible to experimental artefacts.
Interactive Feature Extraction on 3D Meshes

Feature lines, curves on a surface along which the surface bends sharply, convey specific 3D shapes. In this paper, we present an interactive method for extracting feature lines on 3D meshes. Our method first estimates the principal curvatures and principal directions on local neighborhoods. Then we compute an initial approximation of the feature lines on the global meshes by using a threshold. The threshold controls the number of feature points to keep the most important shapes for the global surface. To capture the interesting features accurately, we finally use an interactive method based on regional meshes. Some examples are presented to illustrate the usefulness of our method. Compared with other automatic methods, our method possesses the advantage of convenience to capture the feature points.
Concordance between TIRADS and Cytology in Thyroid Nodule

Introduction: Palpable thyroid nodules are stated in 4 to 7% of individuals. This study was designed to evaluate the relation of Thyroid Imaging Reporting and Data System (TIRADS) and fine-needle aspiration (FNA) based cytology reports in patients with thyroid nodules. Materials and Methods: In this retrospective cross-sectional study, individuals with thyroid nodules who were selected for ultrasonographic-guided FNA enrolled in this study. Demographic data, radiologic assessment, and cytology report were gathered based on hospital medical records. TIRADS grading of the nodules was assessed for each nodule. Cytology was performed on all samples. Sensitivity and specificity were calculated by comparing cytology with ACR-TIRADS and also cytology with TIRADS 4-5 cut-off point as a radiologic malignant lesion. Results: 172 patients were studied, 151 of whom were female and 21 were male. The mean age of the patients was 49.46 years. Most of the patients had TIRADS 4 (53.5%) followed by 3 (31.4%), and 5 (11.6%). 151 patients (87.8%) had a benign lesion in cytology. Of them, 118 had colloid nodules. There was a statistically significant relation between TIRADS and cytology (p-value<0.001). Sensitivity, specificity, AUC, and positive and negative predictive value for ACR-TIRADS classification were 76.19%, 47.54%, 0.619, 20.00%, and 92.06%, respectively. These values for cut-off “4-5” classification was 86.36%, 38.00%, 0.622, 16.96%, and 95.00%. Conclusions: According to the significant concordance between TIRADS and cytology, as shown in the results of our study, it seems that TIRADS could be used to decrease the amount of unnecessary FNA in individuals with thyroid nodules.
The Antioxidant Activities of Ethanolic, Methanolic, Ethyl Acetate, and Aqueous Extracts of the Endemic Species, Lavandula mairei Humbert (A Comparative Study between Cold and Hot Extraction)

Background Medicinal plants have been used for therapeutic purposes and have shown important biological properties. This study aimed to evaluate for the first time the antioxidant activities, total flavonoid, and total phenolic contents of Lavandula mairei Humbert. The ethanol, methanol, ethyl-acetate, and water extracts were used for this purpose. Methods The antioxidant activities were assessed in vitro by free radical scavenging activity against 2,2-diphenyl-1-picrylhydrzyl (DPPH), ferric reducing antioxidant power (FRAP), and total antioxidant capacity (TAC). The total flavonoid and phenolic contents were determined spectrophotometrically with gallic acid and Quercetin as standards. Results In either Soxhlet or maceration methods, the flavonoids and the total phenolic contents were significantly higher in the methanolic extract (P<0.05) compared to other extracts. The total flavonoid content of L. mairei ranged between 119 and 224.6 mg QE/g DW for Soxhlet extracts and from 111.8 to 148.51 mg QE/g DW for maceration extracts. While the total phenolic content was between 35.12 and 99.37 mg GAE/g DW for Soxhlet extracts and 27.63 to 58.99 mg GAE/g DW for maceration extracts. In either the Soxhlet or maceration method, the highest total antioxidant capacity (TAC) was obtained using the ethanolic extract, while the aqueous extract had the highest antioxidant activity for DPPH and FRAP assays. Conclusion These results showed that Lavandula mairei Humbert has great potential to be a promising candidate for natural plant sources of antioxidants.