Miracle-dz/UniFAR-FTUs huggingface dataset:
The Challenge of Global Environmental Change: Attitudinal Trends in Teachers-In-Training

The aim of our research was to study attitudinal trends in Spanish trainee teachers regarding Global Environmental Change (GEC), in order to identify elements that should be enhanced in their education. The Scale of Global Environmental Change (SGEC) was used as a measurement instrument to explore attitudes on how to deal with GEC. A cluster analysis of the scores of the four SGEC factors (N = 950) was carried out in order to segment the cases into groups of similar response profiles. Two solutions are proposed: one made up of two clusters (Concerned and Disengaged) and the other of four clusters (Egocentric, Indifferent, Sceptical and Committed). Furthermore, we have analysed whether some of the students’ characteristics significantly influence their inclusion in one cluster or another. The results of this study show that among trainee teachers there are sceptical, self-centered and indifferent trends, which do not correspond to people capable of promoting the transformation needed to deal with GEC. Therefore, it is necessary to improve their training with new educational models that favour the recognition of the real origin of socio-environmental problems and provide them with skills to promote individual and social responsibility.
Some Features of Sentiment Analysis for Russian Language Posts and Comments from Social Networks

Sentiment analysis of different language texts is one of the very popular machine learning tasks. The complexity of its solution depends both on the characteristics of a particular language, and on the length of the evaluated texts. In our work, we consider the task of creating a sentiment analysis software tool for Russian posts and comments from the most popular social networks without any domain restriction. The features of constructing both the algorithmic and the software parts of the problem are described, some quality and performance metrics of the suggested neural network system are presented.
Validated Spectrophotometric Methods for Estimation of Telmisartan and Hydrochlorothiazide in Combined Tablet Dosage Form.

Quantitative Spectrophotometric analysis of poorly water-soluble drugs involves use of various organic solvents, solubility enhancing agents, co solvents or Buffers. Major drawbacks of organic solvents include high cost, volatility and toxicity. On the other hand use of alkali or acids may reduce the stability of analytes throughout the process of estimation. In the present investigation, co-solvency technique has been employed to solubilize the poorly water-soluble drugs. Four perspicacious spectrophotometric methods for simultaneous estimation of Telmisartan (TEL) and Hydrochlorothiazide (HCTZ) in two component solid dosage forms have been developed. The methods employed Simultaneous Equation Method and Multicomponent mode of analysis at 295nm and 273nm (absorbance maxima of Telmisartan and Hydrochlorothiazide respectively), the Absorbance Ratio (Q-analysis) method at 283.0nm (iso-absorptive point) and 293.0nm (absorbance maxima of Telmisartan), the First Order Derivative Spectroscopy method at 273.0 nm for Telmisartan (zero cross for HCTZ) and 295.0 nm for Hydrochlorothiazide (zero cross for TEL). The methods utilized Methanol: Water (1:1) as a solvent and were found to be linear in the range of 4-24 μg/ml and 2-14 μg/ml for TEL and HCTZ respectively. The procedures were successfully applied for the simultaneous determination of both drugs in laboratory mixtures and in commercial tablet formulation.
A Vehicle Guidance Model with a Close-to-Reality Driver Model and Different Levels of Vehicle Automation

This paper presents a microscopic vehicle guidance model which adapts to different levels of vehicle automation. Independent of the vehicle, the driver model built is different from the common microscopic simulation models that regard the driver and the vehicle as a unit. The term “Vehicle Guidance Model” covers, here, both the human driver as well as a combination of human driver and driver assistance system up to fully autonomously operated vehicles without a (human) driver. Therefore, the vehicle guidance model can be combined with different kinds of vehicle models. As a result, the combination of different types of driver (human/machine) and different types of vehicle (internal combustion engine/electric) can be simulated. Mainly two parts constitute the vehicle guidance model in this paper: the first part is a traditional microscopic car-following model adjusted according to different degrees of automation level. The adjusted model represents the automation level for the present and the near and the more distant future. The second part is a fuzzy control model that describes how humans adjust the pedal position when they want to reach a target speed with their vehicle. An experiment with 34 subjects was carried out with a driving simulator based on the experimental data and the fuzzy control strategy was determined. Finally, when comparing the simulated model data and actual driving data, it is found that the fuzzy model for the human driver can reproduce the behavior of human participants almost accurately.
Multiscale Feature Line Extraction From Raw Point Clouds Based on Local Surface Variation and Anisotropic Contraction

Recent 3-D scanning techniques can produce various kinds of digitized 3-D data. Most of these scanned data are in a format of unstructured point clouds. Such low-level representation of 3-D data usually contains only geometric properties (point positions), while lacking higher level structure cues, for example, feature lines. Feature lines can be defined as a visually prominent characteristic of the shape, including edges, ridges, and valley lines in multiple scales, which can support a lot of downstream applications, such as shape reconstruction and analysis. We present a two-phase algorithm for extracting line-type features on point clouds. To extract both large-scale and shallow feature lines, we first define a statistical metric to detect all potential feature points while immune to the noise to some extent. Then, for correctly reconstructing the feature lines from these identified coarse feature points, we introduce an anisotropic contracting scheme to force feature points lying on the underlying real feature lines. To illustrate the reliability of our method, various experiments have been conducted on both synthetic and raw data. Both visual and quantitative comparisons show that our method is robust to noise and can correctly extract multiscale feature lines. In addition, our method is generally applicable to robotic picking. Note to Practitioners—This article was motivated by the problem of the feature line extraction for real scanned point clouds. Feature lines, as one kind of the most important structure information, depict the basic shape of the real object in our life. Extracting this kind of shape features from the unstructured point clouds can facilitate a variety of downstream practical applications, such as product design, workpiece manufacturing, and robotic grasping. Existing approaches to detect features either heavily rely on differential quantities, which are sensitive to the noise, or need an elaborately designed local descriptor but fail to recognize small-scale features. These challenges motivate us to design a new approach aiming at extracting multiscale feature lines while keeping robustness to heavy noise. The technique developed in this work can produce high-quality feature points and feature lines, which would serve as higher level structural information and facilitate many applications. Additional applications in 6-degree-of-freedom (6-DoF) pose estimation demonstrate the potential of our method for robotic picking.
Scalable Electrochemical Synthesis of Novel Biogenic Silver Nanoparticles and Its Application to High-Sensitive Detection of 4-Nitrophenol in Aqueous System

This study reports a scalable green electrochemical synthesis of novel biogenic silver nanoparticles colloid (biogenic AgNPs) in large scale up to 5 liters using the bulk silver bar and the green tea leaves (Camellia sinensis) extract (GTE) as reducing agent during the electrochemical process. Under a direct-current voltage source, the biomolecules in GTE can release electrons to promote the reducing process of Ag+ to Ag0. More interestingly, the formation of the intermediate complex helps to cap on the nanoparticles, which leads to stabilizing AgNPs. The as-synthesized biogenic AgNPs with the size of 34 nm exhibit the outstanding electrochemical properties due to the presence of biomolecules on the biogenic AgNPs surface, which facilitates the effective attaching of AgNPs on the carbon surface of the screen-printed carbon electrode (SPE) through the formation of the strong C-O coordinate bonds between O atom of oxygen functional groups and C atom of SPE. The electrochemical properties of the biogenic AgNPs-modified SPE are enhanced significantly in comparison with bare SPE and pure AgNPs-SPE. The biogenic AgNPs-SPE is applied successfully to the detection of 4-nitrophenol (4-NP). The electrochemical sensor using biogenic AgNPs can reliably detect 4-NP in the linear range from 0.1 to 25 μM with the sensitivity about 6.69 μA μM-1 cm-2. The present work reveals, as the greener synthesis method with ultra-large scalable ability, high purity, and excellent electrochemical properties of biogenic AgNPs is very promising for technological applications in high-sensitive electrochemical chemosensors, nanopharmaceuticals, and other fields.
Analysis of Transvascular Transport Phenomena in the glomerular and peritoneal microcirculation

The current work is devoted entirely to the study of passive transport phenomena, or more specifically, the more simple diffusion, electric migration and filtration of solute matter and water over glomerular and peritoneal capillary walls. The driving forces behind such trans-capillary transport phenomena have long been assumed to be simple gradients of concentration, hydrostatic pressure and electric potential. Despite decades of research, the relative importance of these different transport mechanisms remains a highly controversial subject. In Study I we explore the subject of charge selectivity in the glomerular filtration barrier (GFB). The results of this study indicate that electrical charge may be of less importance in the hindrance of charged molecules in the GFB than previously thought.In Study II, we construct a distributed two-pore model and use it to analyze experimental data (θ vs. SE-radius). The results indicate that the wide distribution obtained in the data analysis may be due to a variation in solute size rather than a true variation in pore size. In addition, several theoretical results are presented such as Poiseuille’s law for a distributed pore population. Study III: One of the many unresolved questions regarding the GFB is the reason behind the marked difference in permeability between albumin and Ficoll. In this study, the distributed two-pore model is extended by introducing size distributions on the solute molecules. Experimental data from the rat glomerulus and from precision-made nanopore membranes are analyzed. We show that a variation of only 16% in the size of the solute molecule is sufficient to explain the difference in permeability between albumin and Ficoll. Study IV: The three-pore model is a widely applied model of peritoneal dialysis. Here an extended version of the classical model is used to optimize automated peritoneal dialysis for a wide range of different scenarios. The results show that large reductions (>20%) in glucose absorption are possible by using optimized (bi-modal) regimes. (Less)
Pereskia aculeata vibrational model by Raman characterization and DFT method

Raman scattering was used to obtain vibrational modes in a Pereskia aculeata sample. The obtained spectrum was compared with quercetin's theoretical spectra, kaempferol, isorhamnetin, rutinose, caffeic, and tartaric acid, generated from the density functional theory (DFT) method, which used structures of the known composition present in the sample. Among the main compounds, phenolic acids and flavonoids are mentioned. Vibrational signatures, designated as CO and CH group modes, are abundant and bands in the region between 800 and 1800 cm-1. This showed that the theoretical and experimental results had good correspondence between the flavonoids. Statistical observations of correlation and principal component analysis (PCA) were used, which helped in the process of correlation between sample and data obtained. Theoretical spectra have been corrected by a single scale factor of 0.961, and vibrational contributions by the molecular group were via VEDA software.
PDMS membranes containing ZIF-coated mesoporous silica spheres for efficient ethanol recovery via pervaporation

The design of functional micro- and mesostructured composite materials is significantly important for separation processes. Mesoporous silica is an attractive material for fast diffusion, while microporous zeolitic imidazolate frameworks (ZIFs) are beneficial for selective adsorption and diffusion. In this work, ZIF-71 and ZIF-8 nanocrystals were grown on the surface of mesoporous silica spheres (MSS) via the seeding and regrowth approach in order to obtain monodispersed MSS–ZIF-71 and MSS–ZIF-8 spheres with a particle size of 2–3 μm. These MSS–ZIF spheres were uniformly dispersed into a polydimethylsiloxane (PDMS) matrix to prepare mixed matrix membranes (MMMs). These MMMs were evaluated for the separation of ethanol from water via pervaporation. The pervaporation results reveal that the MSS–ZIF filled MMMs substantially improve the ethanol recovery in both aspects viz. flux and separation factor. These MMMs outperforms the unfilled PDMS membranes and the conventional carbon and zeolite filled MMMs. As expected, the mesoporous silica core allows very fast flow of the permeating compound, while the hydrophobic ZIF coating enhances the ethanol selectivity through its specific pore structure, hydrophobicity and surface chemistry. It can be seen that ZIF-8 mainly has a positive impact on the selectivity, while ZIF-71 enhances fluxes more significantly.
SEQUENTIAL ANAEROBIC AND AEROBIC TREATMENT OF PULP AND PAPER MILL EFLUENT

Paper mill is one of the major sources of pollution causing industry with intensely coloured effluent. The effluent is rich in lignocellulosic materials and other chemicals used during manufacturing which results in high Bio-chemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Due to its high toxic and mutagenic nature when discharged untreated there is a growing demand to treat the effluent before discharge. Biological treatment is a promising technique as it greatly reduces colour, BOD and COD. Various fungal and bacterial species are capable of degrading the lignocellulosic materials present in the effluent. In the present study characterization of the paper mill effluent and identification of the degradation efficiency of lignin degrading fungal species - Pleurotus species and Rhizopus stolonifer and bacterial species – Pseudomonas aeruginosa and Bacillus subtilis in laboratory scale was done. Here sequential anaerobic and aerobic treatment was carried out in two bioreactors in series. The study indicated that anaerobic treatment gave a reduction of colour (18%), lignin (25%), COD (36%), BOD (28%) in 5days. The anaerobically treated effluent was then separately given to the aerobic reactors containing the fungal and bacterial species. Data obtained indicated that the Rhizopus showed good reduction in colour (71%), lignin (77%), COD (68%) and BOD (70%) in 5days whereas Pleurotus, Pseudomonas and Bacillus species showed reduction in colour (68%, 31%, 18%), lignin (64%, 43%, 44%), COD (58%, 42%, 43%) and BOD (60%, 40%, 42%) respectively in 5days. Thus Rhizopus was identified as the microbe with better degradation capacity.
Applying patent analytics to understand technological trends of smart tourism destinations

ABSTRACT Over the past decades, technological advances have deeply affected business practices and strategies of most economic sectors worldwide, including travel and tourism. Therefore, with the widespread adoption of digital technologies, the concept of smart tourism destination (STD) has become a promising approach in response to the fierce competition among tourism destinations. In general, the STD concept refers to special cases of smart cities initiatives, which builds upon the emerging technological infrastructure to enhance tourists’ experience. Since patent documents offer an ample source of knowledge about technical progress and innovative activity, this specific type of data has been used by scholars to perform in-depth temporal and comparative analyses. Hence, we retrieved patent documents addressing STD technologies from the European Patent Database, named ESPACENET. Based on the analysis of patent information, our study provides robust empirical evidence concerning the characteristics of potential innovations specifically designed for STD initiatives. Therefore, this study offers the following contributions: a longitudinal analysis of patent applications, their geographical concentration, tourism technology developers’ profile, and technology thematic dispersion. More specifically, the data demonstrates that Asian countries are responsible for the majority of STD patent applications and, therefore, are likely to lead STD technology development in the coming years.
Informal Payments in Public Hospitals of Malawi - A Case of Kamuzu Central Hospital

Background: Informal payments in public health facilities act as a barrier to accessing quality healthcare services especially for the poor people. There is growing evidence that in most low-income countries, most poor people are unable to access quality health care services due to demands for payments for services that should be accessed for free. This research was aimed at investigating informal payments for health care services at Kamuzu Central Hospital, one of the referral public hospitals in Malawi. Results of this study provide evidence on the magnitude and factors influencing informal payments in Malawi so that relevant policies and strategies may be made to address this problem. Methods: The study employed a mixed methods research design. The quantitative study component had a sample size of 295 patients and guardians at Kamuzu Central Hospital (KCH). The qualitative study included 7 in-depth interviews with key informants (health workers) and 3 focus group discussions with guardians. Each FGD had 10 people. Thus, in total the whole qualitative sample constituted 52 participants. Quantitative data was analyzed using Excel and STATA. Qualitative data was analyzed using thematic content analysis approach. Results: 80% of patients and guardians at KCH had knowledge of informal payments. About 47% of the respondents admitted paying informally to access health care services at KCH and 87% of the informal payments were made at the request of a health worker. The study identifies lack of knowledge, fear and desperation by patients and guardians, low salary for health workers and lack of effective disciplinary measures as some of the key factors influencing informal payments in the public health sector in Malawi. Conclusion: Informal payments exacerbate inequality in the access of health care services that should be provided for free. Specifically, poor people have limited access to quality health care services when informal payments are demanded. This practice is unethical and it infringes on people’s rights to universal access to health care. There is need to strengthen the public health care system in Malawi by formulating deliberate policies that will deter informal payments.
Treatment of Phenolic and Aromatic Amino Compounds in Polluted Waters by Photocatalytical Oxidation

Abstract Improper handling of rocket fuel residues at abandoned military bases has resulted in heavy pollution of the soil and groundwater with aromatic amino compounds. A similar phenomenon is observed with ash dumps in which solid waste from oil shale thermal treatment is disposed: the ash dump leachate is heavily polluted with phenolic and other compounds, resistant to biological treatment. Experimental research of photocatalytical oxidation (PCO) of both classes of substances and polluted waters was undertaken. The influence of different parameters - pH, concentration of substances to be oxidised, character of substances formed during the PCO, presence of inorganic admixtures, effect of OH•-radical generators and scavengers - on the PCO of solutions of phenolic and aromatic amino compounds was determined. The role of OH•-radicals was found to be important in determining both the PCO rate and the character of the oxidation by-products. The PCO of organic pollutants was also investigated using a catalyst immobilised onto the surface of buoyant hollow glass micro-spheres. Attached titanium dioxide showed lower photocatalytical activity than its slurry, although it allows waters to be treated in simple shallow ponds without intensive stirring. The toxicity of aqueous solutions and polluted waters decreased as PCO proceeded and the biodegradability increased. The energy consumed by PCO of phenolic compounds in phenolic wastewater under solar radiation was estimated to be smaller than the energy consumed by oxidation with ozone.
Remote Photoplethysmography With an EEMD-MCCA Method Robust Against Spatially Uneven Illuminations

Remote photoplethysmography (rPPG) is an attractive video-based technique to monitor heart rate (HR) information in telehealth screening. The subjects are required to stay stationary in the remote screening scenario and ambient lights become the main interference source of measuring HR with rPPG. In this paper, we introduce a novel approach robust against spatially uneven illumination interference in rPPG by combining ensemble empirical mode decomposition (EEMD) with multiset canonical correlation analysis (MCCA). We adopt the following procedures to ensure that the pulses dominate the correlations across multiple signal sets while the illumination noises are as diverse as possible. Specifically, a group of optimal regions of interest (ROIs) are selected according to the quality indicators defined from the green channel in each candidate ROI. A multi-channel signal set is then constructed by decomposing the green signal with EEMD. Only those intrinsic mode functions (IMFs) with the dominant frequencies falling into the interested HR range are utilized as the input of MCCA. The canonical variables (CVs) with the highest cross correlations are derived as the underlying candidate pulses. Finally, fast Fourier transform (FFT) is employed to calculate the dominant frequency and the target HR is determined based on both the quasi-periodic property and the continuity of HR. The proposed EEMD-MCCA method is validated on both the in-house BSIPL-RPPG and the public COHFACE databases, which achieves superior performance over several typical rPPG methods. This study will provide a promising tool for realistic rPPG applications in telehealth screening.
Opposite phenomenon to the flying ice cube in molecular dynamics simulations of flexible TIP3P water

An opposite phenomenon to the flying ice cube where kinetic energy is drained from the high frequency vibrational motion to the low frequency translational motion and rotational motion (Harvey et al., J Comput Chem 19:726-740, 1998) is reported in molecular dynamics simulations of the flexible TIP3P water. It is found that kinetic energy is drained from the low frequency transla- tional motion and rotational motion to the high frequency vibrational motion of the flexible TIP3P water. In addition, the equipartition theorem is not applicable to the flexible TIP3P water, but applicable to the rigid TIP3P water. However, the Maxwell-Boltzmann velocity distribution is satisfied for cases even the equipartition theorem is not applicable.