Miracle-dz/UniFAR-FTUs huggingface dataset:
On the convergence properties of GAN training

Recent work has shown local convergence of GAN training for absolutely continuous data and generator distributions. In this note we show that the requirement of absolute continuity is necessary: we describe a simple yet prototypical counterexample showing that in the more realistic case of distributions that are not absolutely continuous, unregularized GAN training is generally not convergent. Furthermore, we discuss recent regularization strategies that were proposed to stabilize GAN training. Our analysis shows that while GAN training with instance noise or gradient penalties converges, Wasserstein-GANs and Wasserstein-GANs-GP with a finite number of discriminator updates per generator update do in general not converge to the equilibrium point. We explain these results and show that both instance noise and gradient penalties constitute solutions to the problem of purely imaginary eigenvalues of the Jacobian of the gradient vector field. Based on our analysis, we also propose a simplified gradient penalty with the same effects on local convergence as more complicated penalties.
Dynamical downscaling and variable resolution in limited‐area models

Limited‐area models (LAMs) are widely used in numerical weather prediction and regional climate modelling to obtain high‐resolution results which would be too expensive computationally to acquire using a global model. This is often referred to as downscaling. To run LAMs requires lateral boundary conditions (LBCs) which are normally obtained from a global model or a lower‐resolution LAM containing the domain of the smaller LAM. Using a large‐domain high‐resolution LAM as the control, smaller‐domain LAMs were run using LBCs from a low‐resolution LAM run over the large domain. The results from the smaller‐domain LAMs were used to assess the errors due to the LBCs by taking differences against the large domain control. These differences were also used to understand how downscaling occurs and to assess the impact of increasing the domain size. Tests using variable‐resolution LAMs were conducted to determine whether errors arising from LBCs could be reduced. Investigations were made into the appearance of noise over steep orography at boundaries and possible mitigation strategies are discussed.
Fault‐tolerant leader‐follower formation control of marine surface vessels with unknown dynamics and actuator faults

This paper concentrates on the leader‐follower formation control problem for marine surface vessels with unknown nonlinear dynamics and actuator faults. The unknown inertia matrix and multiplicative fault render the existing methods infeasible. To solve this problem, a low‐complexity prescribed performance controller is first proposed without the help of auxiliary neural/fuzzy systems or adaptive mechanisms. A modification technique is further adopted to relax the initial condition, such that global closed‐loop stability is guaranteed. Finally, simulation results illustrate the above theoretical results.
ENHANCED TOTAL PHENOLIC CONTENT EXTRACTION FROM CUCUMIS MELO L. (KULTIK) KERNEL BY DEEP EUTECTIC SOLVENT (DES)

Kernel of Cucumis melo L is a by-product produced from the water-melon production process. The phenolic compounds could be considered as a potential bioactive source for industrial applications. Therefore, the extraction of these compounds as much as possible will decrease valuable waste and could lead to produce value-added products. In the first part of this study, comparation of the effect of DESs and conventional solvent on total phenolic content (TPC) was performed. Some DESs had significantly better extraction yield than conventional solvent. Therefore, optimization of extraction conditions was performed by single factor experiment. Optimized parameters are molar ratio, type of HBA (hydrogen bond acceptor), addition of water content, extraction time and extraction temperature. From the results obtained, all these parameters were found to have an impact on TPC extraction yield. Also, it is noteworthy that the extraction yield using some selected parameters was on decrease after a certain extent. The best extraction parameter for Cucumis melo L. was found to be choline chloride as HBA, 1:4 molar ratio, %30 water addition, 500 extraction temperature and 30 min extraction time. This result confirms that kernel of Cucumis melo L. is a valuable ingredient due to its bioactive content, DESs could be a good alternative to conventional solvents and the industrial applications of DESs could be possible.
A historical monthly upper-air humidity dataset for Australia

Monthly humidity (represented as dew point temperature, DWPT) data from 22 land and 5 island Australian upper-air sites were analysed, with trends estimated over the 1965–2017 period at four pressure levels. Humidity data were selected to ensure that data collected under consistent sampling conditions were used (‘modified data’). The quality control process involved examining station metadata and applying an objective statistical test that detected discontinuities in the data series. At each station and pressure level, modified data series were adjusted (homogenised) on a monthly timescale when discontinuities were identified. Analysis of the homogenised (adjusted) modified DWPT data indicates that, over the 1965–2017 period, linear trends are mostly positive and smaller compared to unadjusted modified data. The all-Australian time-series show positive trends at the 850–400-hPa levels. The total increases in DWPT since 1965 at 850-, 700-, 500-and 400-hPa levels are ~0.5, ~1.2, ~1.3 and ~0.8°C respectively. The increase in humidity in the lower and middle troposphere is in accordance with the expectation that, as the troposphere warms, the amount of moisture in it should increase (at a differential rate of ~7% °C –1 at low altitudes globally, following Clausius–Clapeyron scaling) due to increasing surface evaporation and moisture-holding capacity of the air. However, changes in atmospheric dynamics also influence the magnitude and distribution of humidity trends. The homogenised modified Australian radiosonde data for the 850-hPa level show that the amount of moisture at this level increased ~8.8% °C –1 during 1965–2015
The Comparative Effectiveness of Monotherapy and Combination Therapies: Impact of Angiotensin Receptor Blockers on the Onset of Alzheimer’s Disease

Background The criteria for use of Alzheimer’s disease (AD) drug Leqembi recommended by the Department of Veterans Affairs (VA) include patients aged 65 years or older with mild cognitive impairment (MCI) or mild AD. Comorbidities that include hypertension, hyperlipidemia, and diabetes are common among these patients. Objectives Our objective is to investigate the comparative effectiveness of the administration of one, two, or three medications belonging to the categories of angiotensin receptor blockers (ARBs), angiotensin-converting enzyme inhibitors (ACEIs), Beta Blockers, Statins, and Metformin, for their potential to delay the clinical onset of AD and provide a window of opportunity for therapeutic intervention. Design Retrospective matched case-control study. Setting Data from the Department of Veterans Affairs national corporate data warehouse. Participants We conducted an analysis of 122,351 participants (13,611 with AD and 108,740 without AD), aged 65-89, who began at least one of the prescribed medication classes under investigation between October 1998 and April 2018. Measurements We utilized Cox proportional hazard regressions, both with and without propensity score weighting, to estimate hazard ratios (HR) associated with the use of different medication combinations for the pre-symptomatic survival time of AD onset. Additionally, we employed a supervised machine learning algorithm (random forest) to assess the relative importance of various therapies in predicting the occurrence of AD. Result Adding Metformin to the combination of ACEI+Beta Blocker (HR = 0.56, 95% CI (0.41, 0.77)) reduced the risk of AD onset compared to ACEI monotherapy alone (HR = 0.91, (0.85, 0.98)), Beta Blocker monotherapy (HR = 0.86, 95% CI (0.80, 0.92)), or combined ACEI+Beta Blocker (HR=0.85, 95%CI (0.77, 0.94)), when statin prescribers were used as a reference. Prescriptions of ARB alone or the combination of ARB with Beta Blocker showed an association with a lower risk of AD onset. Conclusion Selected medications for the treatment of multiple chronic conditions among elderly individuals with hypertension, hyperlipidemia, and diabetes as monotherapy or combination therapies lengthen the pre-symptomatic period before the onset of AD.
EFFECTIVENESS OF AQUEOUS COFFEE EXTRACT AND CAFFEINE IN CONTROLLING PHYTOPHAGOUS HETEROPTERAN SPECIES

Heteroptera species are a growing problem in the cultivation of horticultural crops, and intensive chemical control of these pests is not sustainable. Therefore, natural products are used in sustainable pest management. We investigated the potential of aqueous coffee and caffeine extracts in the control of three heteropteran species Nezara viridula (L.), Halyomorpha halys (Stål)
THE INFLUENCE OF OVERCONFIDENCE, REGRET AVERSION, LOSS AVERSION, AND HERDING BEHAVIOR ON INVESTMENT DECISION IN THE CAPITAL MARKET WITH THE MODERATING ROLE OF RISK PERCEPTION IN GENERATION Z STUDENTS

Behavioral finance arises as a result of inefficient markets. Behavioral finance leads more to the irrational behavior of investors towards their decisions. This study aims to determine and empirically prove the influence of Overconfidence, regret aversion, loss aversion, and herding behavior on investment decisions. An investor's risk perception as an analysis carries a logical rationale for how investors choose when they are faced with multiple investment choices. I used a questionnaire-based survey method to collect sample data of 120 respondents. research analysis method using Partial Least Square. According to the research conducted, the results of Overconfidence have a significant positive effect, while Regret Aversion, Loss Aversion, Herding behavior, risk perception of overconfidence, regret aversion, loss aversion and herding behavior on risk decisions have a non-significant effect.
Examining the Relationship between Sensory Branding, Brand Awareness and Preference after a Blind Tasting Test: An Application on Tea Brands

The aim of this research is to explore whether there is a relationship between sensory branding and brand awareness and blind taste. A questionnaire and an experiment were used together on 101 volunteers who were familiar with tea brands in the University of Düzce, Turkey. The questionnaire was applied to the participants to measure their sensory branding and brand awareness perceptions. In addition, for the blind taste test, the experiment was conducted. Frequency, Spearman’s Rank Correlation, Cochran Q, McNemar, Mann Whitney U Test, and Logistic Regression tests were used to test the hypotheses. According to the results of the analysis, there were low and moderate relationships between sensory branding and brand awareness in tea brands. In addition, according to the results of the Cochran Q and McNemar tests, there was a difference between the tea brands based on the participants’ blind taste test responses. Moreover, it was determined that the sensory brand perception of the participants did not differ according to the blind taste test results. Similarly, the findings of the blind taste test revealed that the participants’ brand awareness perceptions did not differ. Furthermore, according to the logistic regression analysis findings, sensory branding and brand awareness did not have any effect on the blind taste test. According to the findings of this research, even though the product contents were same, brand studies created awareness in the consumer.
Do innovation and proactiveness impact the business performance of women-owned small and medium-scale enterprises in Vietnam? A study using the PLS-SEM approach

Purpose: This study aims to identify and evaluate the relationship between factors and the business performance of women-owned small and medium enterprises (SMEs) in Vietnam focusing on the dimensions of entrepreneurial orientation factors such as innovation, risk-taking and proactiveness. Design/Methodology/Approach: Data were obtained from 350 female entrepreneurs of SMEs in Vietnam using a structured questionnaire. The partial least squares structural equation modeling method (PLS-SEM) was applied to find the cause-and-effect relationship between exogenous and endogenous variables. Findings: The results show that the business capacity of business owners, the quality of human resources, access to finance, social capital, entrepreneurial orientation and government policies positively impact the enterprise's business performance. The relationship between the three dimensions of entrepreneurial orientation and business performance is examined. In detail, proactiveness and innovation have a positive relationship while risk-taking negatively affects the business performance of women-owned SMEs. Conclusion: The study has shown the factors affecting the business performance of women-owned small and medium-sized enterprises in Vietnam and at the same time proved that EO is a multidimensional concept when the dimensions of EO tend to have different effects on business performance. Research Limitations and Implications: The research may lack a comparison in the field of SMEs to deeply understand the cause-and-effect relationship between exogenous and endogenous variables. Therefore, researchers are encouraged to test the proposed propositions further. Practical Implications: Research results provide insight for businesses, state management agencies, credit institutions and associations on policy-making and appropriate solutions to support and develop the enterprise. Contribution to Literature: The important impact of proactiveness and innovation on SMEs' business performance opens a new door to more research in business orientation.
Game-scoring coordination in handball according to situational variables using time series analysis methods

This study analysed the game-scoring coordination in men’s Spanish Handball League when controlling for quality of opposition, game location, game period and their potential interactive effects. The sample was composed of 142 close games (final goal difference ≤ 5). The scoring processes of the teams throughout the game formed the time series that constituted the basis for subsequent analysis. Different methods of time series analysis were used (i.e. autocorrelation, cross-correlation, moving averages, Hilbert transform). The scoring processes of the teams presented a high consistency across all the games as well as strong inphase modes of coordination in all the game contexts. The only differences were found in relation to the game period. The results showed an increasing game-scoring coordination behaviour as the game unfolded. In particular, the game-scoring coordination was significantly lower for the 1st and 2nd game periods (i.e. 0–10 min and 10–20 min) compared to all the other. This suggests that the first 20 min are those that break the game-scoring. The concept of co-adaptation and the gradual familiarisation between players and teams as the game progresses might contribute to explain these findings. Training aspects should focus particularly on preparing the initial 20 min of the games, creating specific practice tasks.
Single-Modality Supervised Joint PET-MR Image Reconstruction

We present a new approach for deep learned joint PET-MR image reconstruction. The proposed network is inspired by conventional synergistic methods using a joint regulariser. The maximum a posteriori expectation-maximization algorithm for PET and the Landweber algorithm for MR are unrolled and interconnected through a deep learned joint regularisation step. The parameters of the joint U-Net regulariser and the respective regularisation strengths are learned and shared across all the iterations. Along with introducing this framework, we propose an investigation of the impact of the loss function selection on network performance. We explored how the network performs when trained with a single or a multi-modality loss. Finally, we explored under which settings a joint reconstruction was beneficial for MR reconstruction by using various undersampling factors. The results obtained on 2D simulated data show that the joint networks outperform conventional non-deep learned reconstruction methods, both synergistic and independent. For PET, the network trained with only a PET loss achieves a better global reconstruction accuracy than the version trained with a weighted sum of PET and MR loss terms. More importantly, the former further improves the reconstruction of PET-specific features where deep learned MR-guided methods show their limit. Therefore, using a single-modality loss to supervise the training while still reconstructing the two modalities in parallel leads to better reconstructions and improved modality-unique structure recovery. For MR, while the same effect is observed, the gain from joint reconstruction only occurs in the presence of highly undersampled data.
IMPLEMENTATION OF GUIDED INQUIRY LEARNING MODEL ON THE TOPIC OF INVERTEBRATE TO ENHANCE STUDENT CURIOSITY AT GRADE X MIA

The research aimed to enhance studentâ€™s curiosity at grade X MIA by implementation of guided inquiry learning model on the topic of invertebrate. Research method was a Classroom Action Research based on the model developed by Lewin (1992). This research was performed within 3 cycles with implementation of guided inquiry learning model based on Kuhlthau (2010). The subject is grade X MIA consist of 17 men students and 22 women students. Data were obtained by questionnaire, interviews, documentation, and observation sheets of four aspects of curiosity developed by Daniel Berlyne (1960) consisted of epistemic curiosity, perceptual curiosity, specific curiosity, diversive curiosity. The result showed that the studentâ€™s curiosity in precycle: epistemic curiosity at 21% with very low category, perceptual curiosity at 8% with very low category, specific curiosity at 12% with very low category, diversive curiosity at 23% with very low category. The studentâ€™s curiosity in cycle I: epistemic curiosity at 22% with very low category, perceptual curiosity at 21% with very low category, specific curiosity at 28% with very low category, diversive curiosity at 28% with very low category. The studentâ€™s curiosity in cycle II: epistemic curiosity at 32% with low category, perceptual curiosity at 24% with very low category, specific curiosity at 35% with low category, diversive curiosity at 39% with low category. The studentâ€™s curiosity in cycle III: epistemic curiosity at 46% with medium category, perceptual curiosity at 42% with low category, specific curiosity at 42% with low category, diversive curiosity at 44% with medium category. The studentâ€™s curiosity increased from very low category (16%) in precycle becomes low category (43,5%) in cycle III and meet the target research. Based on the results of research can be concluded that guided inquiry learning model can improve students' curiosity.
Secretive Coded Caching With Nonuniform Demands in Fog Radio Access Networks

In this letter, we investigate the problem of secretive coded caching in fog radio access networks (F-RANs), aiming at minimizing the average backhaul rate under nonuniform file popularity distribution. Firstly, a two-layer placement scheme which jointly considers secrecy constraints and cache resources in the network is designed. Next, a two-stage delivery scheme which utilizes the network architecture characteristics and exploits the redundancy in user demands is designed. By integrating the above two schemes, a novel secretive coded caching scheme is proposed. Finally, we derive the expression of the average backhaul rate and evaluate the performance of the proposed scheme via simulations. Simulation results show that our proposed scheme outperforms the state of the art in terms of backhaul rate reduction.
Heat stress of cattle from embryonic phase until culling

Heat stress becomes a serious problem in the livestock sector as it affects cows' performance negatively. The objective of this paper review is to investigate the effects of heat stress during the different phases of the life cycle of cows; embryos, calves, heifers, and cows. Heat stress during early maternal gestation affects the ability of embryos to develop increasing the risk of abortion and early embryonic death. Heat stress during late maternal gestation affects the performance of calves and heifers later in their life, as it reduces growth performance, conducts physiological changes, impaired immunity, changes the behavior, and reduces the length and intensity of the estrus in heifers with decreasing in milk production in the first lactation. On the level of cows, milk quality and production, meat quality, and the final body weight decrease under hot temperatures. Heat stress decreases the conception rate, alters follicle growth, and estrous symptoms. Hormones secretion and physiological changes because of the heat stress conduct to impair the immunity system, and in oxidative stress and death in some cases. Same as for calves and heifers a change in the behavior of cows was detected in order to decrease their temperature.
Consensus of fractional-order heterogeneous multi-agent systems

This study is devoted to the consensus protocols design for a set of fractional-order heterogeneous agents, which is composed of two kinds of agents differed by their dynamics and the fractional-order α satisfies 0 < α < 2. Distributed state feedback consensus protocols are constructed for the two kinds of agents, respectively. Based on the Kronecker product technique and the fractional-order stability theory, sufficient conditions are derived to ensure the consensus of heterogeneous multi-agent systems in terms of linear matrix inequalities (LMIs). These can be solved numerically by LMI toolbox in Matlab. Finally, a simulation example is employed to validate the effectiveness of the theoretical results.
Proposal for study on IR light and glucose phantom interaction for human glucose quantification applications

It has been established the importance of a constant glucose monitoring in order to keep a regular control for diabetes patients. Several medical studies accept the necessity of exploring alternatives for the traditional digital glucometer, given the pain and discomfort related to this technique, which can lead to a compromised control of the disease. Several efforts based on the application of IR spectroscopy had been done with favorable, yet not conclusive results. Therefore it’s necessary to apply a comprehensive and interdisciplinary study based on the biochemical and optical properties of the glucose in the human body, in order to understand the interaction between this substance, its surroundings and IR light. These study propose a comprehensive approach of the glucose and IR light interaction, considering and combining important biochemical, physiological and optical properties, as well as some machine learning techniques for the data analysis. The results of this work would help to define the right parameters aiming to obtain an optical glucose quantification system and protocol.