Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Student Learning Experience in Large Programming Classes Using Pseudo-Flipped Method

In an effort to improve student engagement in large programming classes, this study proposes a pseudo-flipped (PF) method of teaching that combines the core principles of two popular teaching methods, traditional and flipped (or inverted), thereby mitigating the drawbacks of these methods. In traditional teaching, class time is mostly used by instructors to teach a class using pre-prepared lecture slides and smartboards or similar alternatives, whereas students, mostly passively, listen to the lecture and take notes. In a purely flipped class, all resources traditionally taught in classroom are moved outside the classroom, either as text, video, audio, students are expected to read or view lectures before class, and the instructor uses class time in solving problems. In the proposed PF method, students are taught in a traditional way for half the allocated time. For the other half, students solve problems in class with the instructorÃ¢â‚¬â„¢s assistance. Similar to the flipped method, in PF, students learn concepts on their own outside the classroom using an interactive textbook. To fill gaps in their knowledge, instructors spend time teaching those core concepts in class by solving problems. PF promotes active learning by engaging students towards solving problems on learnt concepts. A survey is done in a programming class to find student opinion on how useful this pseudo-flipped method is on student engagement as opposed to traditional teaching. Both quantitative and qualitative analysis of the survey responses strongly favour the proposed method, with more than 70% of students in favour of it.
Health Biotechnology and Biopharma (2021), 5(2): 46-60

Omentin is an adipocytokine that has anti-diabetic property. Genetic variations in ITLN-1 may affect blood glucose level by inactivating Akt/PKB signaling pathway. The aim of this study was to evaluate the association between ITLN-1 gene non-synonymous +326 A>T and synonymous +258 G>A polymorphisms with susceptibility to T2DM. Significant distribution observed in genotype frequency of +258G>A variants in T2DM patients and controls. Genetic models for codominant, dominant and recessive genotypes for +326 A>T and recessive genotype for +258 G>A were found capable of increasing the risk of T2DM. Allelic association analysis showed T-allele (+326 A>T) conferred higher risk of the diabetes. Results suggested that genetic variants of ITLN-1 may act as possible molecular targets for early diagnosis of T2DM in future.
Light-matter interactions: artificial and solid-state crystals embedded in an optical cavity

This thesis is devoted to the characterization of crystalline structures for quantum technological applications. It is composed of two parts.In a first project we study the localization transition of one particle in an one-dimensional artificial quasiperiodic crystal, whose potential depends on the particle position. We consider an ultracold atom in an optical lattice, embedded in an optical cavity. The atom strongly couples to the cavity, leading to a second optical potential. The position of the atom within the cavity affects the cavity field, thus the atomic motion backacts on the potential it is subjected to. For incommensurate wavelengths, we show that the competition between the two potentials yields a quasiperiodic potential. We determine the parameters for which we reproduce the Aubry-Andr'e model and discuss the effects of the backaction on the localization transition.In the second project we propose a frequency down-conversion scheme to generate THz radiation using the exciton-phonon coupling in a semiconductor crystal. Our idea is based on a chain of interactions that are naturally present in a pumped semiconductor microcavity. We derive the crucial exciton-phonon coupling, starting from the electron-phonon interaction via the deformation potential and taking into account the crystal symmetry properties. We identify conditions necessary for THz emission, estimate the emission power and show that the exciton-phonon interaction provides a second-order susceptibility.
Monte Carlo drift correction – quantifying the drift uncertainty of global climate models

Abstract. Global climate models are susceptible to drift, causing spurious trends in output variables. Drift is often corrected using data from a control simulation. However, internal climate variability within the control simulation introduces uncertainty to the drift correction process. To quantify this drift uncertainty, we develop a probabilistic technique: Monte Carlo drift correction (MCDC). MCDC samples the standard error associated with drift in the control time series. We apply MCDC to an ensemble of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We find that drift correction partially addresses a problem related to drift: energy leakage. Nevertheless, the energy balance of several models remains suspect. We quantify the drift uncertainty of global quantities associated with the Earth's energy balance and thermal expansion of the ocean. When correcting drift in a cumulatively integrated energy flux, we find that it is preferable to integrate the flux before correcting the drift: an alternative method would be to correct the bias before integrating the flux, but this alternative method amplifies the drift uncertainty. Assuming that drift is linear likely leads to an underestimation of drift uncertainty. Time series with weak trends may be especially susceptible to drift uncertainty: for historical thermosteric sea level rise since the 1850s, the drift uncertainty can range from 3 to 24 mm, which is of comparable magnitude to the impact of omitting volcanic forcing in control simulations. Derived coefficients – such as the ocean's expansion efficiency of heat – can also be susceptible to drift uncertainty. When evaluating and analysing global climate model data that are susceptible to drift, researchers should consider drift uncertainty.
Acceptance, Mindfulness, and Compassionate-Based Intervention in Overweight and Obese Women and its Effect on Metabolic Syndrome Components: A Randomized Controlled Trial

Objectives: This study aimed to examine the efficacy of acceptance, mindfulness, and compassion (Kg-free) on obese and overweight women diagnosed with metabolic syndrome components. Materials and Methods: In this randomized controlled trial, 52 obese and overweight women with body mass index (BMI) ≥25 were evaluated in two intervention and control groups, The intervention was implemented weekly. Triglyceride (TG), high-density lipoprotein (HDL), fasting blood sugar (FBS), blood pressure (BP), BMI, and waistline measurements thyroid tests were assessed measured as the main outcome, and life-quality and sexual function improvement as its secondary outcome in pre, post and follow-up phase. Results: The study results indicated that the acceptance, mindfulness, and compassion (Kg-free) protocol was effective on the BMI, waistline, TG level, BP (systolic and diastolic index), quality of life, and sexual function in women with overweight and obesity, but fasting BP and HDL level did not significant (d=0.001–0.50; significant at the 0.001 level). Conclusions: The present trial was carried out aiming to examine the efficacy of group intervention based on acceptance, mindfulness, and compassion on obese and overweighed women and its effect on the components of metabolic syndrome, including the waistline, BMI, BP, FBS, TG, HDL, the quality of life, and the sexual function. Our results showed that group intervention based on acceptance, mindfulness, and compassion could reduce the BMI of the individuals in the intervention group compared to the control group. Moreover, the present study provided further evidence that this intervention bears an essential part in the psychological interventions for individuals struggling with overweight and obesity.
Games for biofeedback therapy system

This bachelor thesis is concerned with the creation of biofeedback games for therapy purposes. The games are built on top of an existing software project developed for the purposes of Neurofeedback created by BioDat Group. The games present clear visual and audio stimuli to the user. This thesis describes the theoretical research behind neurofeedback therapy as well as a description of the created games and their implementation.
Genome-Wide Acetylation Modification of H3K27ac in Bovine Rumen Cell Following Butyrate Exposure

Butyrate contributes epigenetically to the changes in cellular function and tissue development of the rumen in ruminant animals, which might be achieved by its genetic or epigenetic regulation of gene expression. To explore the role of butyrate on bovine rumen epithelial function and development, this study characterized genome-wide H3K27ac modification changes and super-enhancer profiles in rumen epithelial primary cells (REPC) induced with butyrate by ChIP-seq, and analyzed its effects on gene expression and functional pathways by integrating RNA-seq data. The results showed that genome-wide acetylation modification was observed in the REPC with 94,675 and 48,688 peaks in the butyrate treatment and control group, respectively. A total of 9750 and 5020 genes with increased modification (H3K27ac-gain) and decreased modification (H3K27ac-loss) were detected in the treatment group. The super-enhancer associated genes in the butyrate-induction group were involved in the AMPK signaling pathway, MAPK signaling pathway, and ECM-receptor interaction. Finally, the up-regulated genes (PLCG1, CLEC3B, IGSF23, OTOP3, ADTRP) with H3K27ac gain modification by butyrate were involved in cholesterol metabolism, lysosome, cell adhesion molecules, and the PI3K-Akt signaling pathway. Butyrate treatment has the role of genome-wide H3K27ac acetylation on bovine REPC, and affects the changes in gene expression. The effect of butyrate on gene expression correlates with the acetylation of the H3K27ac level. Identifying genome-wide acetylation modifications and expressed genes of butyrate in bovine REPC cells will expand the understanding of the biological role of butyrate and its acetylation.
A Modeling Approach to Investigate Drivers, Variability and Uncertainties in O 2 Fluxes and the O 2 :CO 2 Exchange Ratios in a Temperate Forest

The O 2 :CO 2 exchange ratio (ER) between terrestrial ecosystems and the atmosphere is a key parameter for partitioning global ocean and land carbon fluxes. The long-term terrestrial ER is considered to be close to 1.10 moles of O 2 consumed per mole of CO 2 produced. Due to the technical challenge in measuring directly the ER of entire terrestrial ecosystems (ER eco ), little is known about the variations in ER at the hourly and seasonal scales as well as how different 15 components contribute to ER eco . In this modeling study, we explore the variability and drivers of ER eco and evaluate the hypothetical uncertainty in determining ecosystem O 2 fluxes based on current instrument precision. We adapted the one-dimensional, multi-layer atmosphere-biosphere gas exchange model, CANVEG, to simulate hourly ER eco from modeled O 2 and CO 2 fluxes in a temperate beech forest in Germany. We found that the annual mean ER eco ranged from 1.06 to 1.12 mol mol -1 within the five years’ study period. Hourly ER eco 20 showed strong variations over diel and seasonal cycles and within the vertical canopy profile. Determination of ER from O 2 and CO 2 mole fractions in air above and within the canopy (ER conc ) varied between 1.115 and 1.15 mol mol -1 . CANVEG simulations also indicated that ecosystem O 2 fluxes could be derived using the flux-gradient method in combination with measurements of vertical scalar gradients and CO 2 , sensible heat or latent heat fluxes obtained with the eddy covariance technique. Owing to measurement uncertainties, however, the uncertainty in estimated O 2 fluxes derived with the flux-gradient 25 approach could be as high as 15 μmol m -2 s -1 , which represented the 90% quantile of the uncertainty in hourly data with a high-accuracy instrument. We also demonstrated that O 2 fluxes can be used to partition net CO 2 exchange fluxes into their component fluxes of photosynthesis and respiration, if ER eco is known. The uncertainty of the partitioned gross assimilation ranged from 1.43 to 4.88 μmol m -2 s -1 assuming a measurement uncertainty of 0.1 or 2.5 μmol m -2 s -1 for net ecosystem CO 2 exchange and from 0.1 to 15 μmol m -2 s -1 for net ecosystem O 2 exchange, respectively. Our analysis suggests that O 2 30 measurements at ecosystem scale have the potential for partitioning net CO 2 fluxes into their component fluxes, but further improvement in instrument precision is needed.
Evaluation of Groundwater Quality for Drinking and Agricultural Purpose

This study examines a variety of chosen groundwater samples from Mohanur, which has issues with its quality for drinking and agricultural use. Reading the study's findings will give you crucial information status of the ground water in Mohanur and can assist in locating the domestic and industrial sources of contamination. This is very helpful in guiding future research to pinpoint and reduce the issue of ground water pollution and helps to take action to address the problem. When a body of water is harmed by anthropogenic toxins, it is often considered to as polluted when it either cannot be used for human purposes, such as drinking water, or when its ability to support its biotic populations significantly changes. Despite their interdependence, surface water and groundwater have frequently been researched and managed as separate resources. In this study, 14 significant parameters were picked to calculate the water quality index. The World Health Organization (WHO) and Indian Council for Medical Research's criteria (ICMR) for the quality of drinking water were used to create the Water Quality Index (WQI). In this study, the weighted arithmetic index approach was employed to calculate WQI.
Universality of the cross entropy in $\mathbb{Z}_2$ symmetric monitored quantum circuits

The linear cross-entropy (LXE) has been recently proposed as a scalable probe of the measurement-driven phase transition between volume- and area-law-entangled phases of pure-state trajectories in certain monitored quantum circuits. Here, we demonstrate that the LXE can distinguish distinct area-law-entangled phases of monitored circuits with symmetries, and extract universal behavior at the critical points separating these phases. We focus on (1+1)-dimensional monitored circuits with an on-site $\mathbb{Z}_{2}$ symmetry. For an appropriate choice of initial states, the LXE distinguishes the area-law-entangled spin glass and paramagnetic phases of the monitored trajectories. At the critical point, described by two-dimensional percolation, the LXE exhibits universal behavior which depends sensitively on boundary conditions, and the choice of initial states. With open boundary conditions, we show that the LXE relates to crossing probabilities in critical percolation, and is thus given by a known universal function of the aspect ratio of the dynamics, which quantitatively agrees with numerical studies of the LXE at criticality. The LXE probes correlations of other operators in percolation with periodic boundary conditions. We show that the LXE is sensitive to the richer phase diagram of the circuit model in the presence of symmmetric unitary gates. Lastly, we consider the effect of noise during the circuit evolution, and propose potential solutions to counter it.
Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea

Abstract. Extreme sea level events, such as storm surges, pose a threat to coastlines around the globe. Many tide gauges have been measuring the sea level and recording these extreme events for decades, some for over a century. The data from these gauges often serve as the basis for evaluating the extreme sea level statistics, which are used to extrapolate sea levels that serve as design values for coastal protection. Hydrodynamic models often have difficulty in correctly reproducing extreme sea levels and, consequently, extreme sea level statistics and trends. In this study, we generate a 13-member hindcast ensemble for the non-tidal Baltic Sea from 1979 to 2018 using the coastal ocean model GETM (General Estuarine Transport Model). In order to cope with mean biases in maximum water levels in the simulations, we include both simulations with and those without wind-speed adjustments in the ensemble. We evaluate the uncertainties in the extreme value statistics and recent trends of annual maximum sea levels. Although the ensemble mean shows good agreement with observations regarding return levels and trends, we still find large variability and uncertainty within the ensemble (95 % confidence levels up to 60 cm for the 30-year return level). We argue that biases and uncertainties in the atmospheric reanalyses, e.g. variability in the representation of storms, translate directly into uncertainty within the ensemble. The translation of the variability of the 99th percentile wind speeds into the sea level elevation is in the order of the variability of the ensemble spread of the modelled maximum sea levels. Our results emphasise that 13 members are insufficient and that regionally large ensembles should be created to minimise uncertainties. This should improve the ability of the models to correctly reproduce the underlying extreme value statistics and thus provide robust estimates of climate change-induced changes in the future.
Hidden Markov Model for Stock Trading

Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example) based on the stock price predictions. The procedure starts by using four criteria, including the Akaike information, the Bayesian information, the Hannan Quinn information, and the Bozdogan Consistent Akaike Information, in order to determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of the S&P 500 index. For this work, the out-of-sample R OS 2 , and some other error estimators are used to test the HMM predictions against the historical average model. Finally, both the HMM and the historical average model are used to trade the S&P 500. The obtained results clearly prove that the HMM outperforms this traditional method in predicting and trading stocks.
A Perusal on Intrusion Detection & Deterrence Methodologies

-The increase in the security breach of computer systems and computer networks has led to the increase in the number of security tools that seek to protect these assets. Among these tools are intrusion detection and prevention systems (IDPS). IDPS are security systems that are used to detect and prevent security threats to computer systems and computer networks. These systems are configured to detect and respond to security threats automatically, thereby reducing the risk to monitored computers and networks. Intrusion detection and prevention systems use different methodologies such as signature based, anomaly based, stateful protocol analysis, and a hybrid system that combines some or all of the other systems to detect and respond to security threats. Intrusion detection and prevention system comes as an appliance or a software tool. The combinations of the methodologies, delivery mechanisms, and the technical requirements for properly configuring these systems make it difficult to understand and evaluate these systems. This problem is amplified by the lack of publicly available work and current data sets for use in evaluating the effectiveness of intrusion detection and prevention systems. In this paper we will offer a clear explanation of the detection methodologies used by the IDPSs and offer a way to compare these methodologies.
A ﬁsh-based index of large river quality for French Guiana (South America): method and preliminary results (cid:1)

– Growing pressures from development activities, on aquatic environments in South American countries, have created an urgent need for tools to measure the quality of aquatic systems. The index of biotic integrity, based on ﬁsh assemblages, elaborated in North America, constitutes a basis for the development of these tools. However, its direct application is problematic in regions having a rich and diverse ichthyofauna and where the knowledge of ﬁsh species ecology is incomplete. The response of taxonomic or trophic groups is often unknown and the selection of ﬁsh assemblage metrics cannot be based on previous knowledge, as in intensely studied regions. This work proposes a method, similar to the approach recently pursued in Europe, based on comparing the variability of ﬁsh assemblages in reference situations with their variability inﬂuenced by human-induced perturbations. The method was developed from 53 samples of 27 reaches in 7 hydrographic basins of French Guiana. For each of 28 ﬁsh assemblage descriptors, stepwise multiple linear regressions with 28 habitat variables were carried out. The residuals of the models obtained were used as candidate metrics independent of natural environmental factors. Nine metrics showing signiﬁcant di ﬀ erences between reference and disturbed samples were selected to constitute the index. The index was validated by analysing a temporal data series obtained from a reach disturbed by dam construction.
Overview for virtual reality (VR) researchers on the current use of VR to treat psychological problems

Three-dimensional (3D) environments are increasingly being used to provide therapy to those suffering from mental health problems. Virtual environments can provide a safe and realistic simulation to expose patients to the cause of their problem. This paper presents a review of the use of 3D environments to assess and treat mental health problems. Within the review applications to treat mental health problems such as post-traumatic disorder, autism and phobias are described. The areas reviewed in this paper describe more recent works in the area of three-dimensional interfaces for the treatment of mental health problems.
Discriminating between the Weibull and Power Lindley Distributions Utilizing Fisher Information

Recently, the power Lindley distribution was proposed by Ghitany et al. (2013). It can be considered as an alternative to the Weibull distribution. In some cases, the Weibull and PL distributions provide similar data fit. In this paper, we discriminate between the Weibull and PL distributions by taking advantage of the Fisher information procedure proposed by Gupta and Kundu (2006). In addition, the Fisher information matrix is used to compute the asymptotic variance of the p th percentile estimators including the asymptotic variances of the median and the average asymptotic variance of the percentile estimators. Furthermore, both of the asymptotic variances are useful as they can provide the further information of the Q-Q plot, especially the variation. In cases of the Weibull and PL distributions, the trends of the asymptotic variance of the p th percentile estimators are demonstrated with respect to the shape and the scale parameters. Moreover, we also analyze two datasets and compare the result between the likelihood ratio and the Fisher information procedures.