Miracle-dz/UniFAR-FTUs huggingface dataset:
ULTRASONIC AND SPECTROSCOPIC INVESTIGATION OF THIOUREA IN NON-AQUEOUS MEDIA -

Acoustical and thermo chemical behavior of thiourea in formamide is studied using ultrasonic technique. The Ultrasonic velocity (u), density (ρ) and viscosity (η) measurements have been carried out for the solution at 278, 288, 298, 308, 318 and 328K and at different concentrations. The results arrived from ultrasonic technique yield the various intermolecular interactions occur in the solution. Spectroscopic techniques have been used to identify the various functional groups. The results obtained from spectroscopic studies were correlated with acoustical and thermo chemical properties of the solution.
3D Semantic VSLAM of Indoor Environment Based on Mask Scoring RCNN

In view of existing Visual SLAM (VSLAM) algorithms when constructing semantic map of indoor environment, there are problems with low accuracy and low label classification accuracy when feature points are sparse. This paper proposed a 3D semantic VSLAM algorithm called BMASK-RCNN based on Mask Scoring RCNN. Firstly, feature points of images are extracted by Binary Robust Invariant Scalable Keypoints (BRISK) algorithm. Secondly, map points of reference key frame are projected to current frame for feature matching and pose estimation, and an inverse depth filter is used to estimate scene depth of created key frame to obtain camera pose changes. In order to achieve object detection and semantic segmentation for both static objects and dynamic objects in indoor environments and then construct dense 3D semantic map with VSLAM algorithm, a Mask Scoring RCNN is used to adjust its structure partially, where a TUM RGB-D SLAM dataset for transfer learning is employed. Semantic information of independent targets in scenes provides semantic information including categories, which not only provides high accuracy of localization but also realizes the probability update of semantic estimation by marking movable objects, thereby reducing the impact of moving objects on real-time mapping. Through simulation and actual experimental comparison with other three algorithms, results show the proposed algorithm has better robustness, and semantic information used in 3D semantic mapping can be accurately obtained.
Acquisition and maintenance of transient imprinted dmrs in the human placenta and their role in development

La impronta genomlca es un fenomeno eplgenetico por el que un subconjunto de genes se expresa de manera monoalelica dependiendo del origen parental de cada alelo. En general, los promotores de estos genes contienen regiones diferencfalmente metiladas (DMRs, por sus siglas en ingles), en las que el alelo no expresado se encuentra normalmente metilado. Cribados genomicos sugieren que en humanos ya han sido identificados la mayoria de genes regulados por impronta genomica de manera ubicua - asociados con DMRs presentes en todos los tejidos -. Por el contrario, se ha investigado poco sobre las regiones asociadas a este mecanismo epigenetico de manera especifica de tejido. El objetivo principal de esta tesis ha sido determinar el alcance de la regulacion por Impronta genomica en la placenta humana y como estos genes pueden Influir en el crecimiento y desarrollo Intrauterino. Durante el transcurso de este trabajo se han descrito 72 DMRs que se presentan exclusivamente en la placenta humana. Todas estas regiones heredan su alelo metllado del ovoclto y se mantienen de manera estable durante la reprogramacion embrionaria. Despues de producirse la prelmplantacion, la metilacion alelica de estas reglones se pierde en todos los tejidos somaticos. Ademas, liemos descrito la expresion monoalelica regulada por impronta genomica en 20 genes asociados a estas nuevas DMRs especificas de placenta. Esta regulacion de la expresion tambien se produce en el embrion preimplantacional, como mostramos con la expresion paterna de _ZHX3_ durante el estadio de clivaje embrionario. La desregulacion de este mecanismo especifico de placenta es probable que desempene un papel importante en el fenotipo de las molas hidatidlformes, ya que Incluye genes esenciales implicados en diferentes procesos biologicos como modificaciones eplgeneticas o procesos metabolicos. La impronta genomlca en la placenta humana es un fenomeno polimorfico en el que la metilaclon o expresion monoalelica caracteristica, puede estar ausente. En las muestras que presentan expresion blalellca de alguno de estos genes, esta expresion se correlaciona con la presencia bialellca de marcas permisivas de histonas y en algunos casos, puede ser independiente del estado alelico de la metllacion del ADN. Aunque en nuestro estudio no se observe una mayor frecuencia de metilacion pollmorfica en placentas de embarazos complicados o asociados al uso de tecnicas de reproduccion asistida, es necesaria una mayor caracterizacion, incluyendo estudios de expresion por metodos cuantitativos, para poder determinar el papel de los genes regulados por impronta genomica de manera especifica en la placenta y en el desarrollo embrionario.
Effects of Deep and Shallow Tillage with Straw Incorporation on Soil Organic Carbon, Total Nitrogen and Enzyme Activities in Northeast China

The characterization of soil physicochemical properties and the resulting soil enzyme activity changes are crucial for understanding the effects of various tillage and straw management techniques on crop grain yield. In 2018–2019, we conducted a field micro–plot experiment to determine the effects of tillage depth and straw management on the soil physicochemical properties, enzyme activity, and maize grain yield. Six treatments were employed, including straw removal (CK), straw mixed with (SM), and straw buried (SB) into the soil under tillage depths of 10 (D10) and 30 cm (D30). The results demonstrated that SM and SB significantly increased the soil nitrate (NO3––N) content and decreased the ammonium (NH4+–N) content in the 0–20 cm soil layer in 2018 relative to CK. SM had greater soil urease (URE) and acid phosphatase (APH) activities in the 0–20 cm soil layer, and SB improved the soil APH activity at the 30–40 cm depth in both seasons. D30 obtained a lower penetration resistance in the 10–40 cm soil profile and higher soil organic carbon (SOC) and soil total nitrogen (STN) contents at the 30–40 cm soil depth relative to D10. The soil enzyme activity was positively related to the soil nutrient content and negatively related to the soil penetration resistance in the 0–20 cm soil layer, particularly in D30. Compared with CK, the grain yield was higher by 2.48–17.51% for SM and 7.48–24.46% for SB in 2018 and 2019, respectively. The structural equation model analysis suggested that the tillage depth mainly affected the soil penetration resistance (PR) and pH; however, straw management dominantly influenced the soil mineral N levels, leading to other soil property changes and crop production results. In conclusion, straw incorporation with deeper plow tillage might be an optimal straw return approach for soil quality improvement and sustainable maize production in northeast China.
Cloudy in the Microcalorimeter Era: Improved Energies for Kα Transitions

X-ray missions with microcalorimeter technology will resolve spectral features with unprecedented detail. In this work, we improve the H-like Kα energies for elements between 6 ≤ Z ≤ 30 for the release version of the spectral simulation code Cloudy to match laboratory energies. We update the ionization potential (I ion) for these elements and add a fourth-order polynomial to the level energy difference. This brings the release version of Cloudy into a near-perfect agreement with NIST. The updated energies are ∼15–4000 times more precise than that of the current release version of Cloudy (C17.02). These new changes will be a part of the next update to the release version, C17.03.
A predictive model for electrostatic energy harvesters with impact-based frequency up-conversion

This paper reports a predictive model for vibration-to-electrical energy harvesters based on an in-plane, gap-closing variable capacitor with frequency up-conversion triggered by the impact between the electrodes. Since the output power is proportional to the output frequency, rectifying low-frequency ambient vibrations (1–50 Hz) to high-frequency electrical signals (200–600 Hz) increases the power output. While such a device has been previously reported experimentally, this is the first time a model able to predict the experimental data has been described. The model is based on lumped approximation. The central area supporting the mobile electrodes, or the shuttle mass, is represented by a point mass suspended by springs and has its own equation of motion. The motion of the electrodes attached to the shuttle is described by a set of two equations, each associated with a distinct dynamic mode. In these equations, the electrodes are represented by an equivalent mass and spring constant. The first equation describes the separate motion of mobile and fixed electrodes. In this mode, the electrodes experience damped free vibration due to the electrostatic and air damping between them. The second equation describes the combined motion when the two set of electrodes move together. In this mode the air damping forces between the collided electrodes is eliminated and the electrostatic force is kept constant. The motion equations are solved simultaneously with Kirchhoff’s law to compute the voltage drop across a resistor in series with the variable capacitor and a DC bias voltage source. Predictions are shown to be consistent with the experimental results, and frequency up-conversion effects are observed with exponentially decaying voltage amplitude as seen in experiments. A parametric study is also carried out to identify main parameters that affect the up-conversion, laying the foundation for future design optimization to maximize the power output.
Generation Z in Indonesia: The Self-Driven Digital

Despite several similarities, Generation Z in Indonesia has specific characteristics that might differentiate them from their colleagues from other countries. Socio-cultural factors such as national values shape their behaviours in many aspects of their life. Specific significant life events in Indonesia such as inhumanity among minorities and damaging natural disasters are also believed to contribute to the development of the specific characteristics of Generation Z in this country. The aim of this chapter is to describe these characteristics as well as the behaviours of Generation Z in personal and professional contexts, including their consumer behaviours. Based on literature and publications related to the topic, it can be seen that people from this generation are realistic but confident with their abilities, especially in using technologies. However, there is a need for social interaction, especially with experts such as their superordinates particularly during difficult times. These characteristics will lead to specific behaviours from Generation Z in Indonesia.
Characteristic analysis of a new high-static-low-dynamic stiffness vibration isolator based on the buckling circular plate

The high-static-low-dynamic stiffness vibration isolator has great advantages in vibration isolation because it can decrease the natural frequency of the system while keeping the load capability, but it is usually difficult to implement because of its complex structures and installation space constraints. A high-static-low-dynamic stiffness vibration isolator composed of a buckling circular plate and a traditional linear spring is proposed in this paper. The buckling circular plate works as the negative stiffness corrector paralleled with the linear spring, which can be integrated into the sleeve. If the load is chosen properly, the static equilibrium point will be at the initial quasi-zero stiffness point. However, any changes of the load will lead the equilibrium point deviating from the initial equilibrium point. The nonlinear mathematical model of high-static-low-dynamic stiffness vibration isolator considering load imperfection is developed and its force transmissibility is analyzed with the harmonic balance method and homotopy perturbation method. The influence rule of the system parameters on it is analyzed and the corresponding results show that the force transmissibility will exhibit complicated characteristics, depending on the load imperfection, damper, and excitation force.
Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence

This paper describes the application of two artificial intelligence- (AI-) based methods to predict the 28-day compressive strength of fiber-reinforced high-strength self-compacting concrete (FRHSSCC) from its ingredients. A series of 131 data samples collected from various published literature sources were used for training, validation, and testing models. Various AI models were developed with different training algorithms and a number of nodes in the hidden layer to obtain the optimal model for the FRHSSCC data. It is shown that the performances of the artificial neural network (ANN) were better than that of the adaptive neurofuzzy inference system (ANFIS) model. Specifically, the overall coefficient of determination (R2) of the ANN and ANFIS models was 0.9742 and 0.9584, respectively. The sensitivity analysis was also conducted with the ANN model to investigate the effects of input parameters on the output. The results from the sensitivity analysis revealed that the compressive strength of FRHSSCC at 28 days was more sensitive with the changes of water by cement ratio (WCR) parameter and insensitive with varying amounts of fiber (VOF). Finally, it can be concluded that the application of artificial intelligence shows the great potential in the prediction of compressive strength of FRHSSCC.
Método aplicado aos Comitês de Bacias Hidrográficas para elaborar critérios de investimentos

The article proposes a participative method, based on agile and easy application academic techniques, in order to support the investment criteria development regarding the River Basin Committees. Concepts and methodologies are originated from Water Resources Management and Multi-Criteria Decision Aiding respectively. The general aim is to contribute with the basin committee selection improvement, considering the programs, projects, services and works (enterprises) financed by water resources estate funds. Among the main results, the method was able to recommend the enterprises aligned with the key values for the hydrographic region representative decision makers, and above all, it was valid and flexible to be replicable in the Brazilian basin committees.
Understanding performance variability in standard and pipelined parallel Krylov solvers

In this work, we collect data from runs of Krylov subspace methods and pipelined Krylov algorithms in an effort to understand and model the impact of machine noise and other sources of variability on performance. We find large variability of Krylov iterations between compute nodes for standard methods that is reduced in pipelined algorithms, directly supporting conjecture, as well as large variation between statistical distributions of runtimes across iterations. Based on these results, we improve upon a previously introduced nondeterministic performance model by allowing iterations to fluctuate over time. We present our data from runs of various Krylov algorithms across multiple platforms as well as our updated non-stationary model that provides good agreement with observations. We also suggest how it can be used as a predictive tool.
Implementasi Algoritma Fuzzy C-Means Pada Aplikasi Seleksi Karyawan Digital Talent di PT Telekomunikasi Indonesia

Digital talent is currently needed along with increasing demand for digital application projects in PT. Telekomunikasi Indonesia. The manual recruitment process is a constraint to provide the needs of digital talent. To facilitate the recruitment process is required recruitment system which implements data mining techniques to cluster candidate based on level. Fuzzy c-means is the clustering method that will be implemented on this system. The system is designed to support recruitment process and predict candidate levels. With the recruitment system, the process is expected to be faster and more accurate than before. The digital talent employees data will be used as training data with the attributes last education, certification and work experience in Information Technology. Based on the results of the study, there are 4 job-level clusters employees, namely basic, junior, medium and senior cluster.
pH effect on the synthesis of different size silver nanoparticles evaluated by DLS and their size-dependent antimicrobial activity

ABSTRACT This paper reports citrate-stabilized silver nanoparticles (AgNPs) synthesized by nitrate ion chemical reduction with sodium borohydride, at different pHs (2–9). The AgNPs synthesized by this method exhibited size distribution from 5 to 249 nm, depending on pH, as determined by dynamic light scattering, and morphology spherical, as determined by transmission electron microscopy. In pH range 3–7 occurred aggregation of the nanoparticles. The size distribution depending on pH was determined by dynamic light scattering. The zeta potential was determined, and the colloidal stability was correlated with nanoparticles aggregation at different pHs. The size-dependent antimicrobial activity was evaluated for two solutions, wherein both samples exhibited antimicrobial activity, although the smallest AgNPs without agglomeration have enhanced antimicrobial properties.
Effect of Hot-Air and Freeze-Drying on the Quality Attributes of Dried Pomegranate (Punica granatum L.) Arils During Long-Term Cold Storage of Whole Fruit

This study investigated the effect of hot-air and freeze-drying on the physicochemical, phytochemical and antioxidant capacity of dried pomegranate arils during long-term cold storage (7 ± 0.3 °C, with 92 ± 3% relative humidity) of whole fruit over a single experiment. Extracted arils were processed at monthly intervals during 12 weeks of cold storage of whole fruit. After the 12-week storage period, hot-air and freeze-dried arils showed the least (3.02) and highest (23.6) total colour difference (TCD), respectively. Hot-air dried arils also contained 46% more total soluble solids (TSS) than freeze-dried arils. During the storage of pomegranate fruit, total phenolic content (TPC) steadily increased from 20.9 to 23.9 mg GAE/100 mL and total anthocyanin content (TAC) increased from 6.91 to 8.77 mg C3gE /100 mL. Similarly, an increase in TPC and TAC were observed for hot-air (9.3%; 13%) and freeze-dried arils (5%; 5%), respectively. However, the radical scavenging activity (RSA) reduced by 8.5 and 17.4% for hot-air and freeze-dried arils, respectively, after 12 weeks of cold storage. Overall, the parameters such as colour, TPC and TAC as well as the lower degradation in RSA stability during storage showed distinct differences in quality when using the freeze-drying method, which is, therefore, recommended.
Adversarial Learning-based Bias Mitigation for Fatigue Driving Detection in Fair-Intelligent IoV

Fatigue driving is one of main causes of traffic accidents. To avoid such traffic accidents, divers’ fatigue detection has been used in Intelligent Internet of Vehicles (IIoV). IIoV usually dynamically allocate computing resources according to drivers’ fatigue degree to improve the real-time of fatigue detection model. However, the traditional fatigue detection model may have bias on certain groups, which would further cause unfair resource allocation. To solve the problem, this paper proposes an improved IIoV framework, named Fair-Intelligent Internet of Vehicles (FIIoV). Compared with IIoV, we improve two layers in FIIoV, i.e., the detection layer and the normalization layer. The detection layer uses Convolutional Neural Network (CNN) to detect drivers’ fatigue degree, and then uses adversarial network to achieve fairness of detection models. The normalization layer achieves the distribution of different sensitive feature values from historical detection results generated in the detection layer, and then uses the distribution to normalize the output of the detection layer to improve the fairness and accuracy of fatigue detection models. Simulation results show that both accuracy and fairness of FIIoV is improved compared with the original IIoV.
ROBOMINERS – Developing a bio-inspired modular robot-miner for difficult to access mineral deposits

Abstract. Within the ROBOMINERS project an innovative technology for the future exploitation of small and difficult to access mineral deposits is being studied. The project has two main objectives. First, the development of a bioinspired reconfigurable robotic miner prototype, able to navigate, explore and mine selectively with a certain degree of autonomy. The robot-miner will be able to work under different conditions, making the exploitation of many mineral deposits economically feasible, while reducing social and environmental impacts associated with conventional mining methods. The second objective is the creation of a vision of a new mining ecosystem, its function, parts, research roadmaps and visions for years 2030 and 2050, including creation of novel ideas from other sectors, particularly robotics. The robotic ecosystem concept will be tested in representative sites across Europe with simulations, showcasing the different mining environments and conditions where it can be applied.
Probiotic Potential of Lactobacillus Strains on the Adipogenesis of 3T3-L1 Cells

Obesity is the most common health problem in developed countries and is considered a significant risk factor for many major human diseases. This study aimed to evaluate the inhibitory effect of lactic acid bacteria isolated from the human vagina on adipocyte differentiation in 3T3-L1 preadipocytes. We screened 26 strains of lactic acid bacteria to test their effects against obesity. Among the tested strains, Lactobacillus gasseri MG2855 exhibited a lipase inhibitory activity of 11.84% and inhibited relative lipid content of 3T3-L1 cells (96.21%) at a concentration of 1,000 μg/mL. The survival rate of L. gasseri MG2855 in 0.3% bile salt was 88.47%, and the survival rate after incubation for 3 h in pH 3.0 was 78.64%. L. gasseri MG2855 showed higher sensitivity to erythromycin, chloramphenicol, tetracyclin, and cephalothin in 16 antibiotic sensitivity tests. These results demonstrate that L. gasseri MG2855 can be employed as a potential probiotic with anti-obesity effects. Probiotic Potential of Lactobacillus Strains on the Adipogenesis of 3T3-L1 Cells
Fat in the Leg: Function of the Expanded Hind Leg in Gasteruptiid Wasps (Hymenoptera: Gasteruptiidae)

Abstract Among some of the most unusual traits of the gasteruptiid wasps is their unique hovering flight and the expansion of their hind tibiae.Tibial expansions in female parasitoid hymenopterans often involve an enlarged sensory structure for vibration detection, the subgenual organ, thus enabling refined substrate-borne detection of concealed hosts. In the present paper, we utilize a combination of microscopy, chemical analysis, gene expression, and behavior to explore the function of the expanded hind tibia of gasteruptiid wasps. We find that the expanded hind tibia of gasteruptiids is filled largely with fat body, a cell cluster thought not typically to occur in insect legs. Based on its position relative to flexible tibial structures and the subgenual organ, the gasteruptiid tibial fat body may function to amplify vibrational signals. We show the tibial fat body to be filled with both trophocytes and, depending on gasteruptiid lineage, oenocytes.Transcriptomics reveals enrichment for fat-related genes more than expected in an insect leg and raises several additional possibilities for functions of fat in the leg including detoxification. Finally, our flight observations support the hypothesis that this structure may also function in balance and maneuvering in the unusual leg-dangling flight behavior of this wasp.