Miracle-dz/UniFAR-FTUs huggingface dataset:
Everybody Has Their Own Image: Teacher Autonomy of the University Teachers

Teacher autonomy is defined as teachers’ freedom to make their own decisions about the curriculum, their professional development, and their participation in the administrative decision-making processes. The term teacher autonomy is commonly discussed in the context of primary and secondary schools. However, it is also important to understand how faculty members perceive and experience their teacher autonomy to empower them professionally. As a result, the aim of this research is to understand how the university teachers define and experience teacher autonomy. The data of this basic qualitative research were collected through an open-ended survey and semi-structured interviews. The survey data were collected from nine participants and the interview data were collected from four participants. The data were analysed with thematic analysis. The results showed that teacher autonomy means being free to make decisions, taking responsibility, freedom and having the trust in the professionalism of a university teacher. The participants feel autonomous in all three dimensions of teacher autonomy. The approach of the management, collaboration, and professional development foster their teacher autonomy while work schedule, accreditation and inexperience limit their teacher autonomy as university teachers.
Probiotics Delay the Decrease of Kidney Function in Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is defined as kidney impairment or reduced estimated glomerular filtration rate (eGFR). The prevalence grows over time. A progressive decrease in kidney function eventually necessitates renal replacement therapy (dialysis or transplantation). Appropriate treatment determines the clinical outcome. One of them is the dietary approach. This review aims to gather evidence of the potential of probiotics to delay CKD damage progression. This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. The review gathers publications from four databases and synthesizes them as evidence. Were 357 publications found, three of which matched the inclusion criteria and were evaluated. The article's synthesis results reveal that probiotics suppress intestinal dysbiosis. These beneficial complicated processes make significant contributions. Thereby, the worsening of renal disease is prevented. Based on the findings, it was concluded that the probiotic positively affected the clinical outcomes of chronic kidney disease.
Constrained homogeneous errors-in-variables modelling and extended weighted total least squares solutions

The homogeneous errors-in-variables (HEIV) model is extended from the regular EIV model for a more wide range of applications. Necessary constraints are imposed to avoid trivial solution or provide ancillary information of parameters. For the constrained HEIV (CHEIV) model with linearly structured data matrix, a generic constrained homogeneous weighted total least squares (CHWTLS) algorithm based on Newton method is derived by assuming the measurements are mutually correlated. An approximate accuracy assessment method is proposed with first order approximation by treating the CHEIV model as a constrained Gauss-Helmert problem. A quadratic constrained HEIV model frequently encountered in fitting and photogrammetry task is proposed as a specific CHEIV model, and a simpler WTLS method based on iterative singular value decomposition (SVD) is developed. A typical two dimensional rectangular building reconstruction problem is simulated to demonstrate the advantages of the homogeneous EIV model and the proposed WTLS algorithms in overcoming the possible ill-posedness and enhancing the numerical efficiency compared with the regular one.
Molecular study of Chlorhexidine resistance in Methicillin Resistant Staphylococcus aureus

ABSTRACT Methicillin Resistant Staphylococcus aureus (MRSA) is a main cause of severe human infections. The aim of this study was to detect chlorhexidine resistance of MRSA by phenotypic and genotypic methods. Fifty MRSA strains were isolated from different hospitals of Mansoura University over a period of one year from December 2021 till November 2022. The antimicrobial susceptibility test was conducted by the disk diffusion method, except for vancomycin which was detected by minimum inhibitory concentration (MIC) determination using microdilution broth method. The MIC towards chlorhexidine (CHG) was determined by microdilution broth method. Qac genes (qacA/B1, qacA/B2, smr, and norA) were detected by Polymerase Chain Reaction (PCR). Transmission electron microscope was used for determination of cell-wall thickness of chlorhexidine susceptible and resistant strains. The results exhibited that the greatest resistance of the isolates was towards Penicillin (100%) and Ceftazidime (100%) and the greatest susceptibility was towards Vancomycin (72%). Decreased susceptibility to CHG at MIC ≥4 mg/L was in 24 isolates (48%). The highest detected genes were smr (100%), norA (50%), and qacA/B2 (45.8%), with a low prevalence of qacA/B1 (4.16%). It was found that the MRSA strain with high resistance to chlorhexidine had more thickened cell wall than that of the susceptible strain.
Transitions between patterned discharges and diffuse discharges in atmospheric helium under applied voltages far below the discharge inception voltage

A diffuse glow discharge was generated in atmospheric helium with a background air pressure of 40 Pa. When the applied voltage was slowly decreased to lower ones than the discharge inception voltage, the diffuse discharge showed transitions to a patterned one with a central column, then a patterned one with double circles, including one central column and seven or eight nearby columns in a circle, followed by a pattern with three circles, and finally a partial diffuse discharge under an applied voltage of about 66% of the discharge inception voltage.
Design of Reliable Control Systems in the Presence of Actuator or Sensor Degradation

In this paper we design controller that combines an observer and a control to handle systems subject to actuator or sensor degradation (including complete failure). The observer contains a pre-filter, an adaptive law, and a modified Luenberger observer that achieves estimation of system state and estimation of conditions of actuator or sensor.nbsp We have shown that if a set of differential Riccati inequatities (DRI) is satisfied then the system can be stabilized under actuator degradation. While in sensor degradation case if an Algebraci Riccati inequality (ARI) and a DRI are satisfied then the system is stabilized. nbsp
Fuel Consumption Evaluation of Connected Automated Vehicles Under Rear-End Collisions

Connected automated vehicles (CAV) can increase traffic efficiency, which is considered a critical factor in saving energy and reducing emissions in traffic congestion. In this paper, systematic traffic simulations are conducted for three car-following modes, including intelligent driver model (IDM), adaptive cruise control (ACC), and cooperative ACC (CACC), in congestions caused by rear-end collisions. From the perspectives of lane density, vehicle trajectory and vehicle speed, the fuel consumption of vehicles under the three car-following modes are compared and analysed, respectively. Based on the vehicle driving and accident environment parameters, an XGBoost algorithm-based fuel consumption prediction framework is proposed for traffic congestions caused by rear-end collisions. The results show that compared with IDM and ACC modes, the vehicles in CACC car-following mode have the ideal performance in terms of total fuel consumption; besides, the traffic flow in CACC mode is more stable, and the speed fluctuation is relatively tiny in different accident impact regions, which meets the driving desires of drivers.
A Flow feature detection framework for large-scale computational data based on incremental proper orthogonal decomposition and data mining

ABSTRACT A framework based on incremental proper orthogonal decomposition (iPOD) and data mining to perform large-scale computational data analysis is presented. It includes iPOD to incrementally reduce data dimensions and decouple dynamic flow structures in massive CFD data; data mining to classify and identify candidate global regions of interest (ROIs) for focused analysis; feature detection to capture key flow features and ultimate ROIs (UROIs); and targeted data storage and visualisation. Quantitative results show that iPOD is able to process large datasets that overwhelm the batch-POD, leading to 4–16× data reduction in the temporal domain. Data mining and feature detection algorithms, respectively, identify 50–70% of the spatial domain with high probability of flow feature occurrence and only 2–30% containing key flow features. The UROI and associated data can be selectively stored and visualised. In contrast to batch-POD, iPOD reduces memory usage by more than 10× and time by up to 75%.
Evaluation of sugarcane promising clones based on the morphophysiological traits developed from fuzz

Sugarcane is one of the critical commercial crops and principal sources of ethanol and sugar worldwide. Unfavorable conditions and poor seed setting rates hinder variety development in sugarcane. Countries like Pakistan directly import fuzz (true seed) and other propagation material from the USA, China, Brazil, etc. In this study, we imported fuzz from China, developed 29 genotypes germinating in the glasshouse, and evaluated at field conditions along with two local checks (CPF-251 and HSF-240). Morphophysiological data were recorded, including plant height (PH), cane length (CL), internodal length (IL), tiller number (TN), brix percentage (B), cane diameter (CD), chlorophyll a (Chl. a), chlorophyll b (Chl. b), and total chlorophyll (T. Chl). Results showed highly significant (p < 0.001) differences among the sugarcane accessions for all the studied traits. High broad-sense heritability (81.89% to 99.91%) was recorded for all the studied parameters. Genetic Advance (GA) ranges from 4.6% to 65.32%. The highest GA was observed for PH (65.32%), followed by CL (63.28%). Chlorophyll leaching assay was also performed at different time points (0, 50, 100, 150, and 200 min). All the genotypes showed the same leaching trend at all times, and better performing genotypes showed less leaching compared to poor performing, indicating the high amount of cutin and wax on the leaf surface. Correlation analysis showed that PH, CL, IL, and TN had significant associations. Principal components analysis (PCA) further confirms these results. Based on PCA and correlation results, PH, CL, IL, and TN can be utilized as a selection criterion for sugarcane improvement. Genotypes such as NS-4a, NS-5, NS-6, NS-8, NS-9, and NS-15 are recommended for future breeding programs related to sugarcane variety development.
Stress-Strength Reliability Model with The Exponentiated Weibull Distribution: Inferences and Applications

In this paper, we deal with the estimation of the reliability $R=P(Y<X)$ where $X$, a unit strength, and $Y$, a unit stress, are independent exponentiated Weibull random variables. The maximum likelihood and Bayesian methods are used to make inference about $R$. We obtain the Baysian estimator using Lindely's procedure under squared error loss and LINEX loss functions with gamma prior for the unknown model parameters. The asymptotic and bootstrap confidence intervals are obtained as well as the credible interval for R is constructed in view of the empirical Bayesian procedure. For illustrative purposes, analysis of real data sets is presented. Mont Carlo simulations are carried out to compare the performances of the different estimators.
Microfabrication Process Development for a Polymer-Based Lab-on-Chip Concept Applied in Attenuated Total Reflection Fourier Transform Infrared Spectroelectrochemistry

Micro electro-mechanical systems (MEMS) combining sensing and microfluidics functionalities, as are common in Lab-on-Chip (LoC) devices, are increasingly based on polymers. Benefits of polymers include tunable material properties, the possibility of surface functionalization, compatibility with many micro and nano patterning techniques, and optical transparency. Often, additional materials, such as metals, ceramics, or silicon, are needed for functional or auxiliary purposes, e.g., as electrodes. Hybrid patterning and integration of material composites require an increasing range of fabrication approaches, which must often be newly developed or at least adapted and optimized. Here, a microfabrication process concept is developed that allows one to implement attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) and electrochemistry on an LoC device. It is designed to spatially resolve chemical sensitivity and selectivity, which are instrumental for the detection of chemical distributions, e.g., during on-flow chemical and biological reaction chemistry. The processing sequence involves (i) direct-write and soft-contact UV lithography in SUEX dry resist and replication in polydimethylsiloxane (PDMS) elastomers as the fluidic structure; (ii) surface functionalization of PDMS with oxygen plasma, 3-aminopropyl-triethoxysilane (APTES), and a UV-curable glue (NOA 73) for bonding the fluidic structure to the substrate; (iii) double-sided patterning of silicon nitride-coated silicon wafers serving as the ATR-FTIR-active internal reflection element (IRE) on one side and the electrode-covered substrate for microfluidics on the back side with lift-off and sputter-based patterning of gold electrodes; and (iv) a custom-designed active vacuum positioning and alignment setup. Fluidic channels of 100 μm height and 600 μm width in 5 mm thick PDMS were fabricated on 2” and 4” demonstrators. Electrochemistry on-chip functionality was demonstrated by cyclic voltammetry (CV) of redox reactions involving iron cyanides in different oxidation states. Further, ATR-FTIR measurements of laminar co-flows of H2O and D2O demonstrated the chemical mapping capabilities of the modular fabrication concept of the LoC devices.
Electrospun Nanofibers including Organic/Inorganic Nanohybrids: Polystyrene- and Clay-Based Architectures in Immunosensor Preparation for Serum Amyloid A

Diagnostic techniques based on biomolecules have application potential that can be realized in many fields, such as disease diagnosis, bioprocess imaging, food/beverage industries, and environmental pollutant imaging. Successful surface immobilization of biomolecules is critical to increasing the stabilization, sensitivity, and selectivity of biomolecules used in bioassay systems. Nanofibers are good candidates for the immobilization of biomolecules owing to many advantages such as morphology and pore size. In this study, montmorillonite (MMT) clay is modified with poly(amidoamine) (PAMAM) generation 3 (PAMAMG3) and added to polystyrene (PS) solutions, following which PS/MMT-PAMAMG3 nanofibers are obtained using the electrospinning method. The nanofibers are obtained by testing PS% (wt%) and MMT-PAMAMG3% (wt%) ratios and characterized with scanning electron microscopy. Antiserum amyloid A antibody (Anti-SAA) is then conjugated to the nanofibers on the electrode surface via covalent bonds using a zero-length cross linker. Finally, the obtained selective surface is used for electrochemical determination of serum amyloid A (SAA) levels. The linear range of PS/MMT-PAMAM/Anti-SAA is between 1 and 200 ng/mL SAA, and the detection limit is 0.57 ng/mL SAA. The applicability of PS/MMT-PAMAMG3/Anti-SAA is investigated by taking measurements in synthetic saliva and serum both containing SAA.
Time–frequency representation using IEVDHM–HT with application to classification of epileptic EEG signals

Time–frequency representation (TFR) is useful for non-stationary signal analysis as it provides information about the time-varying frequency components. This study proposes a novel TFR based on the improved eigenvalue decomposition of Hankel matrix and Hilbert transform (IEVDHM–HT). In the proposed method, first the authors decompose non-stationary signals using the IEVDHM with suitably defined criterion for eigenvalue selection, requirement of number of iterations, and new component merging criteria. Furthermore, the HT is applied on extracted components in order to obtain the TFR of non-stationary signals. The performance of proposed TFR has been evaluated on synthetic signals in clean and white noise environment with different signal-to-noise ratios. The proposed method gives good performance in terms of Renyi entropy measure in comparison with other existing methods. Application of the proposed TFR is also shown for the classification of epileptic seizure electroencephalogram (EEG) signals. The least-square support vector machine (LS-SVM) with radial basis function kernel is used for classification of seizure and seizure-free EEG signals obtained from the publicly available database by the University of Bonn, Germany. The proposed method has achieved classification accuracy 100% for the studied EEG database.
Analisis Sentimen Pengguna Sistem Pay Later Menggunakan Support Vector Machine Metode Pembobotan Lexicon

Layanan pay later sangat mudah dengan cepat populer di masyarakat, hal ini disebabkan karena fitur ini cenderung mudah digunakan dan populer karena tertanam pada e-commerce. Banyaknya penyedia layanan pay later menyebabkan diperlukannya pemilahan penyedia paylater mana yang akan digunakan berdasarkan berbagai pertimbangan termasuk review dari pengguna lain. Di sisi lain, review pengguna lain dapat diperoleh dari Twitter. Data dari Twitter menunjukkan terdapat ribuan tweets pada tahun 2021 hingga 2022 berisikan opini masyarakat terkait penggunaan pay later. Tweets tersebut membahas tentang keunggulan, keluhan, dan ulasan dari penggunaan pay later. Namun, beberapa keunggulan, keluhan, dan ulasan tersebut banyak yang bersifat abstrak sehingga masih belum optimal pemanfaatannya. Penelitian ini bertujuan untuk mengklasifikasikan data tweet yang berkaitan dengan pay later menggunakan algoritma Support Vector Machine (SVM). Dari penelitian ini telah berhasil dibangun model klasifikasi SVM untuk kasus sentimen Shopee Paylater dan Go Paylater. Pada pemodelan sentimen Shopee Paylater diperoleh bahwa model telah dapat memprediksi kelas data uji dengan akurasi 89.74%. Pada pemodelan sentimen Go Paylater diperoleh bahwa model telah dapat memprediksi kelas data uji dengan akurasi 90.27%. Kata Kunci : Analisis Sentimen, Klasifikasi, Pay later, SVM, Lexicon
Bottleneck identification and failure prevention with procedural learning in 5G RAN

To meet the low latency requirements of 5G Radio Access Networks (RAN), it is essential to learn where performance bottlenecks occur. As parts are distributed and virtualized, it becomes troublesome to identify where unwanted delays occur. Today, vendors spend huge manual effort analyzing key performance indicators (KPIs) and system logs to detect these bottlenecks. The 5G architecture allows a flexible scaling of microservices to handle the variation in traffic. But knowing how, when, and where to scale is difficult without a detailed latency analysis. In this article, we propose a novel method that combines procedural learning with latency analysis of system log events. The method, which we call LogGenie, learns the latency pattern of the system at different load scenarios and automatically identifies the parts with the most significant increase in latency. Our evaluation in an advanced 5G testbed shows that LogGenie can provide a more detailed analysis than previous research has achieved and help troubleshooters locate bottlenecks faster. Finally, through experiments, we show how a latency prediction model can dynamically fine-tune the behavior where bottlenecks occur. This lowers resource utilization, makes the architecture more flexible, and allows the system to fulfill its latency requirements.
Helically symmetric extended MHD: Hamiltonian formulation and equilibrium variational principles

Hamiltonian extended MHD (XMHD) dynamics is restricted to respect helical symmetry by reducing the Poisson bracket for 3D dynamics to a helically symmetric one, as an extension of the previous study for translationally symmetric XMHD [D. A. Kaltsas et al, Phys. Plasmas 24, 092504 (2017)]. Four families of Casimir invariants are obtained directly from the symmetric Poisson bracket and they are used to construct Energy-Casimir variational principles for deriving generalized XMHD equilibrium equations with arbitrary macroscopic flows. The system is then cast into the form of Grad-Shafranov-Bernoulli equilibrium equations. The axisymmetric and the translationally symmetric formulations can be retrieved as geometric reductions of the helical symmetric one. As special cases, the derivation of the corresponding equilibrium equations for incompressible plasmas is discussed and the helically symmetric equilibrium equations for the Hall MHD system are obtained upon neglecting electron inertia. An example of an incompressible double-Beltrami equilibrium is presented in connection with a straight-stellarator configuration.
The integration of superlattices and immersion nonlinear ultrasonics to enhance damage detection threshold

We demonstrate the enhancement of immersion nonlinear ultrasonic testing (NLUT) by exploiting superlattices (SLs). NLUT can detect sub-wavelength micro-structural changes in solids by measuring the fundamental and second harmonic frequencies. The amplitude of second harmonic frequency increases with the presence of defects or other heterogeneities. The immersion NLUT is beneficial as water provides a consistent coupling condition; however, water generates high non-linearity that can mask the weak non-linearity originated from the micro-structural features in solids. In this research, SLs are proposed to remove the non-linearity arisen from water and experimental instruments. The SLs made of a periodic arrangement of composite layers can provide a band gap to restrict the propagation of a specific range of frequencies between transmitter and receiver. The periodic arrangement of solid-fluid layers is numerically designed and experimentally adapted to the immersion NLUT. Our results imply that the periodic array of 100 μm thick glass and 100 μm thick water layers provides a band gap that blocks 4.5 MHz (the second harmonic frequency), while this periodic structure passes 2.25 MHz (the first harmonic frequency). The improvement in the sensitivity of the NLUT is demonstrated through detecting the micro-structural changes associated with plastic deformation in aluminum 1100 specimens. It is revealed that the proposed methodology enhances the damage detection sensitivity of immersion NLUT by an order of magnitude as compared to the current practice.We demonstrate the enhancement of immersion nonlinear ultrasonic testing (NLUT) by exploiting superlattices (SLs). NLUT can detect sub-wavelength micro-structural changes in solids by measuring the fundamental and second harmonic frequencies. The amplitude of second harmonic frequency increases with the presence of defects or other heterogeneities. The immersion NLUT is beneficial as water provides a consistent coupling condition; however, water generates high non-linearity that can mask the weak non-linearity originated from the micro-structural features in solids. In this research, SLs are proposed to remove the non-linearity arisen from water and experimental instruments. The SLs made of a periodic arrangement of composite layers can provide a band gap to restrict the propagation of a specific range of frequencies between transmitter and receiver. The periodic arrangement of solid-fluid layers is numeric.