Miracle-dz/UniFAR-FTUs huggingface dataset:
Breathing resistance in heat and moisture exchanging devices

The purpose of this study was to investigate the resistance to breathing (RES) in heat and moisture exchanging devices (HME) intended for use during physical activity in the cold. RES was investigated for seventeen HMEs, including different types of filters. In addition, the influence of headwind on RES was tested using four representative HMEs. HMEs were mounted to the face of an artificial head manufactured from ABS plastic. The HMEs were connected to a mechanical lung simulator, which delivered standardised inspiratory and expiratory air flow rates ( V · , L/s). The delta pressure (Δp, Pa) between ambient air and the air inside the HME was measured, whereupon RES was calculated. The results showed significant (p < 0.05) differences in RES between HMEs from different manufacturers, while the difference was smaller, and in some cases not significant (p > 0.05), between different models/filters within the same brand. The results also showed that RES was highly influenced by different ventilations and headwind conditions. RES increased with increased V · and, when a headwind was introduced, RES decreased during inspiration and increased during expiration. Calculations showed that the oxygen and energy cost for breathing through an HME was very small for most of the tested models. The effect of HME dead space on pulmonary gas fractions depends on the tidal volume. At large tidal volumes and ventilations, the effect of HMEs on pulmonary gas fractions becomes relatively small.
The fishes of the Bolaman Stream, Northern Turkey

In this study, the fish species inhabiting the Bolaman Stream drains to the Black Sea from the Fatsa coast (Ordu Province, Turkey) was reported for the first time. The study was caught out non-periodically by sampling from seven stations in the Bolaman Stream between July 2017 and November 2018. Fish samples were captured with an electroshock device. With this study, it was determined that the fish fauna of the Bolaman Stream is represented by 10 species in five families (Acheilognothidae, Cyprinidae, Gobiidae, Leuciscidae, and Salmonidae). These species were as follows, respectively Rhodeus amarus, Barbus tauricus, Capoeta banarescui, Neogobius fluviatilis, Ponticola turani, Alburnus derjugini, Squalius cephalus, Vimba vimba, Alburnoides fasciatus, and Salmo coruhensis.
Gaze-Head Input: Examining Potential Interaction with Immediate Experience Sampling in an Autonomous Vehicle

Autonomous vehicles (AV) increasingly allow drivers to engage in secondary tasks such as eating or working on a laptop and thus require easy and reliable interaction inputs to facilitate communication between the driver and the vehicle. However, drivers report feeling less in control when driving is no longer the primary task, which suggests that novel approaches for assessing satisfaction regarding AV decision-making are needed. Therefore, we propose an immediate experience sampling method (IESM) that learns driver preferences for AV actions. We also suggest gaze-head input (G-HI) as a novel input in an AV. G-HI provides a hands-free, remote, and intuitive input modality that allows drivers to interact with the AV while continuing to engage in non-driving related tasks. We compare G-HI with voice and touch inputs via IESM for two simulated driving scenarios. Our results report the differences among the three inputs in terms of system usability, reaction time, and perceived workload. It also reveals that G-HI is a promising candidate for AV input interaction, which could replace voice or touch inputs where those inputs could not be utilized. Variation in driver satisfaction and expectations for AV actions confirms the effectiveness of using IESM to increase drivers’ sense of control.
Magnetohydrodynamic Mixed Convection Stagnation-Point Flow of a Power-Law Non-Newtonian Nanofluid towards a Stretching Surface with Radiation and Heat Source/Sink

Two-dimensional MHD mixed convection boundary layer flow of heat and mass transfer stagnation-point flow of a non-Newtonian power-law nanofluid towards a stretching surface in the presence of thermal radiation and heat source/sink is investigated numerically. The non-Newtonian nanofluid model incorporates the effects of Brownian motion and thermophoresis. The basic transport equations are made dimensionless first and the complete nonlinear differential equations with associated boundary conditions are solved numerically by finite element method (FEM). The numerical calculations for velocity, temperature, and nanoparticles volume fraction profiles for different values of the physical parameters to display the interesting aspects of the solutions are presented graphically and discussed. The skin friction coefficient, the local Nusslet number and the Sherwood number are exhibited and examined. Our results are compatible with the existing results for a special case.
Enhancing the accuracy of in-process springback measurements of complex tube bending processes using cost-effective embedded sensors

Geometrical errors due to springback are the main causes of variability in bending of thin-walled tubular profiles. This limits the process capability and determines an increase of the overall production costs due to both scrap or rework, and to the quality control operations. Despite the evolution of bending processes in the last decade, with the adoption of full-electric, highly automated CNC machines, the workpieces’ geometry is usually still verified off-line downstream from the forming stage. This paper presents an innovative on-machine, integrated measuring approach for fast in-process inspection of bent tube geometrical features through cost-effective micro-electromechanical system inertial measurement sensors. These embedded sensors are affected by systematic errors due to both measuring principle and process-related effects; therefore a methodology to correct such errors is proposed. Error compensation is applied to drift and cross-axis sensor errors, as well as to mandrel kinematics and wear effects. An additional sensing system, placed on the tube end for monitoring of the metrological performances and to enabe quick adjustments, is also presented. The results of the validation tests highlight how the proposed system can be used to measure on-machine the final workpiece angle. The final mean absolute errors, for bending angles between 15° and 90°, were, respectively, 0.03° and 0.1° for the sensors embedded in the mandrel and on the tube end depending on the configuration, which are lower than the maximum deviations actually accepted in such processes. However, the performance of the former can be further improved by the proposed periodic quick adjustment procedure. The newly developed on-machine metrology solution enables not only a shortening of the quality control chain, but also significant economic benefits, and a case study is documented.
Proton Competition and Free Ion Activities Drive Cadmium, Copper, and Nickel Accumulation in River Biofilms in a Nordic Ecosystem

Biofilms can be used as a biomonitoring tool to determine metal bioavailability in streams affected by mining and other anthropogenic activities. Surface water and biofilm were sampled over two years from rivers located in the vicinity of a mine located in a Nordic ecosystem (Nunavik, Quebec). Biofilm metal content (Cd, Cu, and Ni) as well as a variety of physicochemical properties were determined to examine relationships between metal accumulation and water quality. Among the three metals of interest, copper and nickel had the highest levels of accumulation and cadmium had the lowest. When considering the exposure levels, nickel was the most abundant metal in our sampling sites. Both exposure and accumulation levels were consistent over time. Biofilm metal content was highly correlated to the ambient free metal ion concentration for sites of circumneutral pHs for all three metals. When the surface water pH was below 6, biofilm metal content was much lower than at other sites with similar aqueous metal concentrations of exposure. This apparent protective effect of decreasing pH can be explained by proton competition with dissolved metals for uptake binding sites at the surface of the organisms within the biofilm as described by the Biotic Ligand Model principles. The relationships obtained for Cd and Cu were overlapping those observed in previous publications, indicating strong similarities in metal accumulation processes in biofilms over very large geographical areas. Although more data are needed for Ni, our results show that biofilms represent a promising metal biomonitoring tool.
Low-complexity channel estimation for time division duplex massive multi-user multi-input multi-output systems

This paper addresses the problem of minimum mean square error channel estimator for time division duplex massive multi-user multi-input multi-output systems. It is noteworthy that, the minimum mean square error has been previously proposed for multi-cell massive multi-user multi-input multi-output channel estimation. However, the minimum mean square error estimator suffers from high computational complexity due to the large dimension of the covariance matrix inversion. In this study, low-complexity channel estimator for time division duplex massive multi-user multi-input multi-output networks is designed by using the low-rank matrix approximation techniques. The proposed estimator is referred to as an approximate minimum mean square error estimator. Furthermore, the computational complexity of the proposed approximate minimum mean square error estimator is analysed and compared to the minimum mean square error and least square estimators. The normalised mean square error and the uplink achievable sum-rate performance criteria are used to evaluate the performance of the proposed estimator. Finally, the simulation results show the effectiveness of the proposed estimator under two different scenarios: noise-limited and pilot contamination. These simulation results are compared to the conventional minimum mean square error and least square estimators.
Theoretical Prediction of Ultrasonic Velocity in Binary Liquid Mixtures

Theoretical values of ultrasonic velocity in the binary mixtures of chlorobenzene with benzene have been evaluated at different temperatures from 303.15 K-323.15 K using Nomoto's relation, ideal mixture relation, Junjie's method, collision factor theory and free length theory. Theoretical values were compared with the experimental values and the validity of the theories was checked by applying the chi-square test for goodness of fit and by calculating the average percentage error (APE).
Transcriptome sequencing revealed the inhibitory mechanism of ketoconazole on clinical Microsporum canis

Background Microsporum canis is a zoonotic disease that can cause dermatophytosis in animals and humans. Objectives In clinical practice, ketoconazole (KTZ) and other imidazole drugs are commonly used to treat M. canis infection, but its molecular mechanism is not completely understood. The antifungal mechanism of KTZ needs to be studied in detail. Methods In this study, one strain of fungi was isolated from a canine suffering with clinical dermatosis and confirmed as M. canis by morphological observation and sequencing analysis. The clinically isolated M. canis was treated with KTZ and transcriptome sequencing was performed to identify differentially expressed genes in M. canis exposed to KTZ compared with those unexposed thereto. Results At half-inhibitory concentration (½MIC), compared with the control group, 453 genes were significantly up-regulated and 326 genes were significantly down-regulated (p < 0.05). Quantitative reverse transcription polymerase chain reaction analysis verified the transcriptome results of RNA sequencing. Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the 3 pathways of RNA polymerase, steroid biosynthesis, and ribosome biogenesis in eukaryotes are closely related to the antifungal mechanism of KTZ. Conclusions The results indicated that KTZ may change cell membrane permeability, destroy the cell wall, and inhibit mitosis and transcriptional regulation through CYP51, SQL, ERG6, ATM, ABCB1, SC, KER33, RPA1, and RNP genes in the 3 pathways. This study provides a new theoretical basis for the effective control of M. canis infection and the effect of KTZ on fungi.
Global trends in the performance of large wind farms based on high-fidelity simulations

Abstract. A total of 18 high-fidelity simulations of large wind farms have been performed by three different institutions using various inflow conditions and simulation setups. The setups differ in how the atmospheric turbulence, wind shear and wind turbine rotors are modeled, encompassing a wide range of commonly used modeling methods within the large eddy simulation (LES) framework. Various turbine spacings, atmospheric turbulence intensity levels and incoming wind velocities are considered. The work performed is part of the International Energy Agency (IEA) wind task Wakebench and is a continuation of previously published results on the subject. This work aims at providing a methodology for studying the general flow behavior in large wind farms in a systematic way. It seeks to investigate and further understand the global trends in wind farm performance, with a focus on variability. Parametric studies first map the effect of various parameters on large aligned wind farms, including wind turbine spacing, wind shear and atmospheric turbulence intensity. The results are then aggregated and compared to engineering models as well as LES results from other investigations to provide an overall picture of how much power can be extracted from large wind farms operating below the rated level. The simple engineering models, although they cannot capture the variability features, capture the general trends well. Response surfaces are constructed based on the large number of aggregated LES data corresponding to a wide range of large wind farm layouts. The response surfaces form a basis for mapping the inherently varying power characteristics inside very large wind farms, including how much the turbines are able to exploit the turbulent fluctuations within the wind farms and estimating the associated uncertainty, which is valuable information useful for risk mitigation.
Privacy preserving classification over differentially private data

Privacy preserving data classification is an important research area in data mining field. The goal of a privacy preserving classification algorithm is to protect the sensitive information as much as possible, while providing satisfactory classification accuracy. Differential privacy is a strong privacy guarantee that enables privacy of sensitive data stored in a database by determining the ratio of sensitive information leakage with respect to an ɛ parameter. In this study, our aim is to investigate the classification performance of the state‐of‐the‐art classification algorithms such as C4.5, Naïve Bayes, One Rule, Bayesian Networks, PART, Ripper, K*, IBk, and Random tree for performing privacy preserving classification. To preserve privacy of the data to be classified, we applied input perturbation technique coming from differential privacy, and observed the relationship between the ɛ parameter values and accuracy of the classifiers. To our best knowledge, this article is the first study that analyzes the performances of the well‐known classification algorithms over differentially private data, and discovers which datasets are more suitable for privacy preserving classification when input perturbation is applied to provide data privacy. The classification algorithms are compared by using the differentially private versions of the well‐known datasets from the UCI repository. According to the experimental results, we observed that, as ɛ parameter value increases, better classification accuracies are achieved with lower privacy levels. When the classifiers are compared, Naïve Bayes classifier is the most successful method. The ɛ parameter should be greater than or equal to 2 (i.e., ɛ ≥2) to achieve cloud server is malicious and untrusted, sensitive data will satisfactory classification accuracies.
Volatile Constituents of Camu-camu (Myrciaria dubia (HBK) McVaugh) Leaves

Abstract The chemical composition of the leaf oil of camu-camu (Myrciaria dubia (HBK) McVaugh) was studied by GC and GC/MS. One hundred and fifteen components of the oil were identified, of which α-pinene (74.3%) and limonene (10.8%) were the major constituents. The composition of the leaf oil was characterized by its richness in monoterpene and sesquiterpene hydrocarbons and the presence of many esters and unsaturated aldehydes
Theoretical Study of the Adsorption Behavior of L-amino Acids on the Iron Surface

This research evaluates the inhibitory effect of L-amino acids (AAs) with different side chain lengths on Fe surface implementing Monte Carlo (MC) simulation. A quantitative and qualitative description of the adsorption behavior of AAs on the iron surface has been carried out. Calculations have shown that the absolute values of the adsorption energy of L-amino acids increase with side chain prolongation; they are also determined by the presence of heteroatoms. AAs from nonpolar and basic groups have the best adsorption ability to the iron surface, which indicates their highest inhibitory efficiency according to the results of MC simulation.
Low-energy catalytic methanolysis of poly(ethyleneterephthalate)

Methanolysis is a chemical pathway for depolymerizing post-consumer PET plastic waste into monomeric feedstock, which can be utilized as a starting component to produce polymer materials with the same quality as the original polymer or other valuable products. In general, conventional methanolysis is carried out at a high reaction temperature under high pressure, demanding high capital and operating costs and in turn leading to an adverse effect on the environment from CO2 emissions. In this study, we developed a low-energy catalytic route for methanolysis to convert PET resin to dimethyl terephthalate (DMT). Potassium carbonate (K2CO3), which is an inexpensive and nontoxic salt, was used as a catalyst, and the effects of cosolvents on the catalytic performance were investigated to develop a new decomposition pathway towards DMT at ambient temperature. Compared to existing methanolysis processes, the overall reaction rate of the proposed system was relatively slow and steady, but the PET resins were completely decomposed into monomers within 24 hours. Intriguingly, a high selectivity of DMT was obtained at a mild temperature range of 20–35 °C. The yield of DMT, obtained by methanolysis at 25 °C, was 93.1% as the molar ratios of methanol, dichloromethane and K2CO3 to PET repeating units were 50, 50, and 0.2, respectively. In this experimental setup, the initial molar ratio of moisture to PET repeating units was adjusted to be 0.4. 2-Hydroxyethyl methyl terephthalate and monomethyl terephthalate were the major by-products created during the process. It was demonstrated that the ideal conversion of PET into DMT could be achieved by controlling the moisture level. In addition to several analytical methods for product characterization, we performed a parametric study to probe the most likely reaction steps and to observe the reaction behaviour of PET methanolysis. Based on the proposed mechanism, a kinetic model was developed and compared with the experimental data to estimate kinetic parameters. In the reaction system, PET depolymerization apparently proceeded through two series of reaction steps, and the degradation of PET had a relatively low activation energy of 66.5 kJ mol−1, which was accountable for catalytic methanolysis of PET at ambient conditions.
Faktor Risiko Terjadinya Kecacingan pada Anak Usia Sekolah Dasar

Latar belakang: Kecacingan merupakan masalah kesehatan yang banyak menyerang anak-anak terutama anak usia sekolah dasar. Infeksi ini dapat mengakibatkan terjadinya anemia, gangguan pertumbuhan dan penurunan fungsi kognitif. Banyak faktor yang mempengaruhi terjadi kecacingan pada anak. Tujuan penelitian ini untuk mengetahui hubungan tingkat pengetahuan anak, personal hygiene anak, sanitasi lingkungan rumah dan tingkat pendidikan orang tua dengan terjadinya kecacingan. Metode: Penelitian ini menggunakan cross sectional design. Sampel berjumlah 51 anak sekolah dasar Alue Naga Banda Aceh serta ibu nya. Data kecacingan diperoleh dari pemeriksaan feses di laboratorium, sedangkan data pengetahuan dan tingkat Pendidikan diperoleh dengan wawancara, serta sanitasi lingkungan mengggunakan observasi. Analisis yang digunakan adalah analisis univariat dan bivariat yaitu uji Fisher’s Exact Test. Hasil: Penelitian ini menunjukkan 11,8% siswa positif kecacingan, terdapat hubungan antara tingkat pengetahuan anak dengan terjadinya kecacingan (p = 0.000), terdapat hubungan antara personal hygiene dengan terjadinya kecacingan (p = 0.011), tidak terdapat hubungan antara sanitasi lingkungan rumah dengan terjadinya kecacingan (p = 0.556) dan terdapat hubungan antara tingkat pendidikan orang tua dengan terjadinya kecacingan (p = 0.034). Kesimpulan:Tingkat pengetahuan anak, personal hygiene anak, tingkat pendidikan orang tua berhubungan dengan terjadinya kecacingan.
Ecological uniqueness of species assemblages and their determinants in forest communities

Beta diversity can be partitioned into the contributions of individual sampling units to overall beta diversity, which are comparative indicators of the ecological uniqueness of species assemblages in the sampling units. Yet, what determines ecological uniqueness has rarely been examined. Here, we investigated the determinants of ecological uniqueness in species assemblages in forest communities.
Molecular Dynamics Simulations of Intrinsically Disordered Proteins in Human Diseases

Recent structural and genomic studies have clearly shown that many proteins contain long regions that do not adopt any globular structures under native conditions. These regions are termed intrinsically disordered or unstructured, and the proteins with intrinsically disordered regions are called intrinsically disordered proteins (IDPs). Current studies estimate that one third of eukaryotic proteins contain stretches of at least 30 contiguous disordered residues, the predictions are even higher in cancer-associated and signaling proteins (80% and 67%, respectively). IDPs play crucial roles in many aspects of molecular and cell biology and numerous IDPs are associated with human diseases such as cancer, cardiovascular disease, amyloidoses, neurodegenerative diseases, diabetes and others. IDPs such as tumor suppressor P53, BRCA1, Parkinsons protein α-synuclein, Alzheimer disease protein tau and many other diseaseassociated hub proteins represent attractive targets for drugs modulating protein-protein interactions. The structures and dynamics of the disordered proteins are the basis for the novel drug discovery. IDPs are lack of stable tertiary and /or secondary structure under physiological conditions in vitro. It is difficult to obtain accurate experimental measurements for the structures and dynamics of the disordered proteins. Molecular dynamics simulations provide available powerful tools to calculate the structures and their related dynamics of IDPs. In this paper, we focus on structural and dynamics insights of disease-associated disordered proteins by molecular dynamics simulations.