Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of statistical physics tools to intracellular transport

Most processes in our daily life are far from equilibrium. The prime example is a cell and the transport occurring within. In this thesis intracellular transport is modeled by means of stochastic processes. For this, two different approaches are applied: the explicit mod- eling of active particles with internal degrees of freedom with characteristics as they were determined experimentally. And secondly, the collective effects occurring in many particle systems are studied in a phenomenological way by means of exclusion processes.In the explicit model one important result is given by the fact that force fluctuations are essential to capture the relevant motion characteristics. Further, the influence of the cellular environment creates counter-intuitive effects, like a possible inversion of the bias. The motion characteristics can be represented in a coarse-grained manner as an exclusion process for particles with internal states. Due to the resulting disorder in the hopping rates a density-dependent condensation occurs.In a second part, a two-lane exclusion model is studied. Two species in a tubular geometry inspired by filamentous fungi are considered.This can be seen as a minimal model exhibiting a phase transition from a low density phase to an intriguing phase with periodically changing particle densities.
Methodological procedure of diagnosing behavioural stereotypes resilience of different language cultures representatives

This paper represents the methodological procedure of diagnosing behavioural stereotypes resilience of different language cultures representatives. The methodological procedure is aimed at compiling a typology of narrative codes of stereotypes resilience of four language cultures representatives and it involves the implementation of six successive stages that will help: 1) to compile a list of personal characteristics of respondents involved in the survey; 2) to compile stimulus lists, i.e. markers of expressive narratives (by keywords); 3) to enter the compiled stimuli lists into the Google Forms with corresponding guidelines for respondents; 4) to perform a free associative experiment with the British, French, Germans and Ukrainians of different social groups through electronic communication; 5) to do the computer processing of the obtained results with the involvement of the information-analytical service STIMULUS; 6) to differentiate the degree of stereotypes resilience of separate social groups of each studied linguoculture in situations of expressive narratives, and differentiate linguistic cultures according to three types of their resilience and their degrees of adaptation to stressful phenomena.
Spatiotemporal seed transfer zones as an efficient restoration strategy in response to climate change

Restoration of wild plant populations in a changing environment is not a simple task, and it becomes increasingly complex and challenging in the context of climate change. In the present study, a spatiotemporal approach was used to delimit provisional seed transfer zones (STZs), for restoration activities involving two wild perennial grasses in Argentina. Ecogeographical land characterization maps were built specifically for the two species of Trichloris genus for the present bioclimatic conditions to define the different STZs; then, they were projected for two future climate scenarios (2050 and 2070). This allowed us to identify populations occurring in cells that underwent changes in ecogeographical categories, potential future beneficiaries of germplasm, and populations that could be used as corresponding source populations under the present conditions. Finally, the conservation status of populations was surveyed and a germplasm collection for future restoration activities was proposed. For the 2050 scenario, for Trichloris crinita, 32 potential beneficiary populations belonging to nine changing categories were identified, whereas for Trichloris pluriflora, four changing categories determined seven beneficiary populations. The number of changing categories and, consequently, the beneficiary populations increased in the 2070 scenario in both species. Several potential seed source populations are already stored in Argentine germplasm banks, but there is little representation of potential beneficiary populations. Spatial locations of still non-conserved populations, both seed sources and beneficiaries, were prioritized for future germplasm collecting missions. This novel approach used for Trichloris spp. can also be adopted for other species for collection and/ or restoration purposes in the light of climate change.
Adaptive Neuro Fuzzy Interface System Based Short Circuit Fault Diagnoses in a Three Phase Induction Motor Drive System

Induction motors are commonly used in different industrial, housing and medical applications, such as air conditioners, transportation, elevators and others. These motors are rugged, reliable and economical. Generally, the reliable operation of the motor and its drive system is very important in industry so that any expected fault must be detected immediately by a monitoring system. This paper reviews and simulates a three-phase induction motor model and different types of faults that may happen in the drive system. Due to short circuit severity on the overall drive system, this study focuses only on short circuit faults, e.g., when any Insulated Gate Bipolar Transistor (IGBT) is shorted out and DC link capacitor is shorted out. Also, an Adaptive Neuro Fuzzy Interface System (ANFIS) algorithm is programmed to detect different types of faults and classify them. The ANFIS system takes two parameters as input from the motor: the first one is the load torque whereas the second one is the stator current. Whereas, the previously published works analyze only the motor's stator current. MATLAB is used to train the ANFIS system and also to analyze samples. Additionally, LTSpice is used simulate the drive system. The ANFIS system shows very high accuracy in short circuit fault detection and classification.
CHARACTERISATION OF LACTIC ACID BACTERIA ISOLATED FROM KEFIR MILK MADE FROM DAIRY AND NON-DAIRY SOURCES AND THEIR SENSORY ACCEPTANCE

Kefir is fermented milk obtained by fermenting milk with kefir grains. Chemical composition from dairy and non-dairy sources may affect the growth and characterisation of lactic acid bacteria (LAB). In this study, different sources of milk (cow milk) and non-dairy milk (soymilk and coconut milk) were used as fermentation media for kefir products. The objectives of the study were to isolate and characterise LAB from Kefir drink using dairy and non-dairy milk. LAB were isolated using different cultural methods such as MRS Agar, MRS with 0.8% CaCO3 and M17 Agar. The characteristics of LAB isolates were determined using morphological, biochemical tests and API 50 CHL Kit. Sensory evaluation of the sample of kefir drinks was also determined. Results confirmed that the isolates identified were Lactobacillus buchneri, Lactobacillus brevis 1, Leuconostoc mesenteroides, Lactobacillus acidophilus 3 and Lactobacillus plantarum 1. The L. buchneri, L. brevis, Leu. mesenteroides and L. acidophilus are heterofermentative bacteria, whereas, L. plantarum is homofermentative bacteria. Four LAB isolates have the potential to be used as probiotic strains due to their high resistant to pH and bile salt. The sensory score of these products in the range of 5.00 to 8.00 in nine point hedonic scale. Most of the sensory panelists preferred cow milk (p < 0.05) than coconut milk kefir and soy milk kefir in the sensory evaluation in all attributes. Meanwhile, the preference between coconut milk kefir and soy milk kefir was similar (p>0.05) in all attributes. Therefore, this study will provide benefits to probiotic manufacturers to produce alternative probiotic drink using dairy and non-dairy milk.
Parametric study of NCl(a1Δ, NCl(b1Σfrom the reaction of Cl/Cl2/He + HN3/He

By means of Microwave generator chlorine diluted by helium is dissociated to chlorine atoms that subsequently react with hydrogen azide to produce excited states of NCl(a1(Delta) ) and NCl(b1(Sigma) ). In this paper, the intensity of NCl(a1(Delta) ) and NCl(b1(Sigma) ) emission dependent on the flow rates of different gases is studied. Moreover, the production of NCl(a1(Delta) ) and NCl(b1(Sigma) ) along the reaction tube is also investigated. By using a simple titration method, we obtain the dissociation efficiency of molecular chlorine up to 100 percent at the flow rates of chlorine no more than 1 mmol/s. We also achieve the quenching rate of NCl(a1(Delta) ) by Cl2 is about 4 X 10-13 cm3/sec molec with excess flow rates of chlorine. Finally, the optimum parameters for NCl(a1(Delta) ) and NCl(b1(Sigma) ) production are summarized.
The link between Work Motivation and Organizational Commitment – Differences between Central and Local Authority Employees

Despite the fact that both the central and local executive bodies are part of the Kazakhstani public administration system, its working conditions, salaries, social allowances and employment relationships are different. Therefore, it can be assumed that civil servants’ attitudes toward their job and organizations, and relationships between them, are different. This paper investigates the motivation-commitment link with respect to differences between central and local authorities’ employees, with a number of goals: to determine levels of motivation and commitment vary the employment place; to identify the main motivation factors that might influence each dimension of organizational commitment. A sample of 1205 civil servants completed standardized questionnaires. The results show significant relationships between motivation and organizational commitment. Results also confirmed the hypothesized relationship differences: Intrinsic and extrinsic motivations are more strongly related to the continuance and normative commitment for central authority employees than for local authority ones. In turn, when both motivational factors increase, local authority employees have a stronger affective commitment than do central authority’s employees.
IDENTIFICATION AND ASSESSMENT OF CURRENCY CRISES IN THE REPUBLIC OF SERBIA

The aim of the paper is to identify the episodes of currency crises in the Republic of Serbia using the exchange market pressure (EMP) index. The country's resilience to currency crises prevents the collapse of the currency and the transfer of negative effects to the entire financial and real sector, so the research and assessment of the factors of currency crises is extremely important. The survey shows that the strongest strikes on the Serbian dinar were in the period of the global financial crisis in 2008, so that adjusting to shocks from abroad is crucial for the sustainability of the applied managed floating exchange rate regime. On the other hand, the stability of the national currency depends mainly on the achieved macroeconomic results, which are presented globally using the misery index.
Parenting online: analyzing information provided by parenting-focused Twitter accounts

ABSTRACT This study investigated the content of parenting information shared on social media by identifying the range and frequency of topics shared by parenting-focused accounts on Twitter. Using the Twitter API, a universe of 675,069 tweets were gathered from 74 of the most-followed parenting-focused accounts, or “hubs,” from January 2016 to June 2018. Using a custom, semi-automated topic modeling approach, we identified the topics – and subtopics within topics – parenting hubs shared with their followers and investigated whether any meaningful differences in topical focus existed between accounts targeting mothers versus fathers. Results indicate that over one third of tweets were about Parenting Behavior and nearly one quarter about Health, with Entertainment, School and Motherhood and Fatherhood generally as less tweeted topics. Mother-focused accounts tweeted more about Health than father-focused accounts, which tweeted more than others about Entertainment. Implications for future parenting and social media research are discussed.
PLEASE Strategy for Teaching Writing Viewed from Students' Self-Esteem

This research aims to examine whether: (1) PLEASE strategy is more effective than RAFT strategy for writing; (2) Students having high self-esteem are better in writing than those having low self-esteem; and (3) There is an interaction between the strategies and the students’ self-esteem. This research was done at a state secondary school located in Sragen, Jawa Tengah, Indonesia. Cluster random sampling was employed to get the sample consisting of two classes. PLEASE strategy was used in the experimental class meanwhile RAFT strategy was employed in the control class. The students in each class were categorized into students having high self-esteem and low self-esteem. Writing test and self-esteem questionnaire were utilized to gather data. Multifactor Analysis of Variance ANOVA 2 x 2 test and Tukey test were employed to analyze the data after normality and homogeneity tests were undergone. The results indicate that: (1) PLEASE strategy is more effective than RAFT strategy for writing; (2) Students having high self-esteem are better in writing than those having low self-esteem; and (3) There is an interaction between the strategies and the students’ self-esteem. It suggests that PLEASE strategy is an effective strategy for writing compared to RAFT strategy. Further researches comparing PLEASE strategy to other strategies, techniques, or methods and collaborating it with media and innovative materials for writing are encouraged.
Eddy Current Non-Destructive Characterization of Carbon Fiber Reinforcement Composites Considering Capacitive Effect

Received: 14 December 2020 Accepted: 2 April 2021 This paper presents a modelling procedure to take into account the capacitive effect at high frequencies, in Eddy Current Non-Destructive Characterization (EC-NDC) of Unidirectional Carbon Fiber Reinforcement Composite (UD-CFRC) rods. To simulate the complete EC-NDC systems, first, the multilayer circular air coil is physically modeled by a finite element (FE) axisymmetric eddy current model coupled to equivalent RL circuit. Each layer of the coil is represented by an equivalent resistance (R) in series with the equivalent inductance (L). Secondly, R and L of the coil layers are computed for several frequencies up to 5Mhz, and then introduced into the equivalent RLC circuit with considering inter-turn and interlayer capacitances. Then the inversion problem is solved in order to identify all inner capacitances of the coil. Finally, the UD-CFRC rod is introduced into the FE eddy current axisymmetric model coupled to an equivalent RLC circuit, as a homogenized conductive material with an equivalent transverse conductivity. The coil with the presence of the homogenized UD-CFRC rod is then modeled as a transformer with a secondary connected to a capacitor in parallel with a resistance in order to evaluate the inner capacitor of the UD-CFRC. All evaluated parameters are then introduced in the last model. The comparison between the computed impedance parts and the measured ones shows a mean error less than 2% and a maximum one of 5% according to the frequency.
THE EFFECT OF THE CONSUMER DECISION-MAKING PROCESS ON THE PERCEIVED VALUE TOWARD SLOW FASHION

Slow fashion designates a new paradigm in the clothing industry that promotes the importance of fashion goods realized with natural and durable products, empowering consumers to use the purchased clothes for a longer time, decreasing, in this case, the environmental and societal impact of fashion pieces. Even if it designates the opposite of fast fashion production, the slow fashion notoriety is not remarkably high among consumers. This study proposed to examine the effect of the consumers' decision-making process on the noticed value toward slow fashion. In this regard, we considered multiple decision-making constructs and tested their impact on consumers’ perceived value toward slow fashion. Also, we examined if there are discrepancies in the perceived value toward slow fashion based on gender. A survey was designed and administrated in Romania to a sample of 330 consumers aged between 18-25. We applied to the collected data exploratory analysis to identify the distribution of manifest variables into factors, followed by confirmatory factor analysis to test the performance of the obtained factors. Finally, we tested the proposed hypotheses using the structural equation model procedure. Were identified seven dimensions that compose the decision-making process of the consumers, namely, recreational shopping, perfectionism, brand knowledge, over choice confusion, fashion awareness, impulsive buying, and brand loyalty. Also, were found three dimensions that constitute the consumers' perceived value toward slow fashion, namely, emotional, social, and financial dimensions. The results showed that over choice confusion exhibits a positive effect on the emotional and financial value; fashion awareness manifests a positive effect on the social value, while brand loyalty manifests a positive impact on the financial value. In the case of gender impact on the emotional value, it was identified that, if a respondent is a female, the influence is positive and statistically significant.
Behavioral Modeling of a Multimode Power Amplifier Using Perceptrons with AM-AM and AM-PM Complex-Valued Activation Function

Three-layer perceptron (TLP) is one of the approaches to the behavioral modeling of radio frequency (RF) power amplifiers (PAs) for wireless communication systems. A low-pass equivalent PA behavioral modeling should be able to represent the AM-AM and AM-PM characteristic curves, besides generating only useful contributions. This work shows that adapting a complex-valued activation function toencompass the strict characteristics from the AM-AM and AM-PM curves at the same time fulfilling the bandpass constraint gives better results in terms of network complexity and accuracy. Besides that, a novel TLP-based model for a multimode PA is proposed. This type of PA has characteristics that add difficulty to its inverse modeling. A modification in the ascendant method is also proposed for application with TLP-based PA models. This method simplifies the models in terms of operations needed for implementation. In a scenario of same number of network parameters, a significant reduction in modeling error is achieved when a complex-valued TLP that accounts for both AM-AM and AM-PM is used instead of a complex-valued TLP that accounts only for AM-AM. Such reduction is quantified by up to 5.73 dB (-35.53 dB to -41.26 dB) improvements in normalized mean square error (NMSE) metric. Moreover, when applying the ascendant method a 67% reduction in active parameters is achieved (36 to 12 active parameters), deteriorating the NMSE by less than 0.5 dB.
The effect of plasmonic nanoparticles and the thickness of anode interface layer on the efficiency enhancement of organic solar cells

In this work, the effect of gold (Au) nanoparticles (NPs) position on the optical parameters of organic solar cells (OSCs) has been investigated. The position of NPs inside the anode interface layer (AIL) and the active layer has been changed and the role of NPs position in light transmission, power absorption, short-circuit current density (Jsc), and maximum generation rate has been studied. I have also used silver (Ag) nanoparticles inside the middle part of the anode interface layer and have investigated the optical parameters and have compared the transmission and power absorption spectrum with Au NPs. Moreover, the role of AIL thickness in optical parameters has been studied. I use the finite-difference time-domain (FDTD) method for all simulations. This study can be useful for new perspectives and light management in organic solar cells.
Heavy metal accumulation and antioxidant properties of Nephrolepis biserrata growing in heavy metal-contaminated soil

Antioxidant defense mechanisms are crucial for plants to survive under stress conditions. We investigated the capacity of a wild fern species, Nephrolepis biserrata, growing in the vicinity of industrial land to accumulate heavy metals, and assessed its antioxidative response under metal stress. The soils in this particular area were highly contaminated with zinc followed by lead and copper. As control, N. biserrata located 10 km away from the industrial area were collected and assessed. N. biserrata from the contaminated sites accumulated metals in their tissues in similar descending order of zinc>lead>copper. The values of bioaccumulation factor between 0 to 0.1 indicate N. biserrata as a moderate accumulator for the tested metals. For the enzymatic antioxidant assays, the activities of catalase and ascorbate peroxidase were significantly higher in N. biserrata from contaminated soil compared to control, while the activity of superoxide dismutase was not differ significantly in plants from both sites. We also detected higher contents of total phenolics and total flavonoids in N. biserrata collected from contaminated site compared to control. Our HPLC analysis revealed higher levels of myricetin and kaempferol in plant samples from the contaminated area. Our study verified the capacity of N. biserrata to scavenge oxygen radicals when exposed to heavy metal stress. Such ability to tolerate stressful condition suggests that the plant is a potential metal phytoremediator
Identifikasi Protein Signifikan pada Interaksi Protein-Protein Penyakit Alzheimer Menggunakan Algoritme Top-k Representative Skyline Query

Penyakit Alzheimer merupakan penyakit neurodegeneratif yang paling umum terjadi. Analisis protein-protein interaction (PPI) dapat memberikan pemahaman lebih baik terhadap penyakit neurodegeneratif dan bisa digunakan untuk menemukan protein yang memiliki peran signifikan pada penyakit Alzheimer. Data PPI diperoleh dari eksperimen dan prediksi komputasional. PPI dapat dianalisis menggunakan centrality measures. Telah banyak penelitian terdahulu terkait analysis PPI menggunakan centrality measures. Top-k RSP merupakan salah satu metode yang dapat digunakan untuk menemukan protein signifikan dengan menggunakan aturan dominansi. Top-k RSP digunakan pada sumber data interaksi eksperimen dan eksperimen+prediksi. Hasil penelitian ini menunjukkan bahwa APP dan PSEN1 merupakan protein signifikan untuk penyakit Alzheimer. Penelitian ini juga menunjukkan bahwa kedua sumber data (eksperimen+prediksi) dan algoritme Top-k RSP terbukti dapat digunakan untuk analisis PPIdari penyakit Alzheimer.
Application of KNN and Semi-Empirical Models for Prediction of Polycyclic Aromatic Hydrocarbons Solubility in Supercritical Carbon Dioxide

ABSTRACT The solubility of polycyclic aromatic hydrocarbons in supercritical carbon dioxide is of great importance in a wide range of applications such as extraction from polluted soils and catalytic hydrogenation. In this study, for the first time a K-nearest neighbor (KNN) as a nonparametric and easy learning model was proposed to predict the solubility of 11 polycyclic aromatic hydrocarbons in supercritical carbon dioxide. The KNN model was constructed with optimum values of K for different compounds. To have a better understanding of the KNN model capability, predictions were compared with the outputs of several well-known semi-empirical models (Chrastil, Adachi and Lu, Li, Garlapati and Madras, Sparks and Bian). Results showed that the KNN model has an average absolute relative deviation (AARD) of about 12.47% for 11 polycyclic aromatic hydrocarbons modified density based correlations (Sparks and Bian) while the best semi-empirical equation (Sparks) result an AARD of about and 11.50%.