Miracle-dz/UniFAR-FTUs huggingface dataset:
Can surf culture foster loyalty towards surf destinations?

ABSTRACT The sport of surfing is gaining increasing importance in the context of tourism. Surf tourism has emerged as one promising product of certain regions worldwide. Surfing, as a sport and as a lifestyle, has been grounded in surf culture, which is recognized as a potential attraction factor for certain surf destinations. Although previous research has been undertaken in the field of surf tourism, the impact that the visitors’ perceptions of a destination’s surf culture have on the overall destination image and on loyalty towards that destination is not represented in the peer-reviewed literature. Therefore, a research model is proposed and tested, aiming to contribute to the advancement of knowledge regarding the relevance and influence of surf culture. A survey questionnaire was carried out among visitors to a surf destination in Portugal – Peniche (N = 430). The model was tested using partial least squares structural equation modelling (PLS-SEM). Results reveal that the perceptions of surf culture contribute to a better overall destination image and a higher loyalty towards the destination, with the overall image also having a positive impact on loyalty. However, different components of surf culture have distinct impacts on overall image and loyalty. The study provides important theoretical contributions in terms of surf culture and the components of a surf destination image, as well as offers useful insights for the development of effective management strategies for surf tourism destinations.
A Forecasting Model of Wind Power Based on IPSO–LSTM and Classified Fusion

To improve the predicting accuracy of wind power, this paper proposes a forecasting model of wind power based on the IPSO–LSTM model and classified fusion, which not only overcomes the shortcoming of the artificially determined parameters of LSTM, but also solves the problem that the fused accuracy may be reduced by the environment when adopting a single fusion model. Firstly, some wind speed sub-series were obtained by decomposing the original wind speed according to the wavelet packet decomposition (WPD), and the data sets formed by combining these sub-series with meteorological elements. Subsequently, the wind power components formed by wind speed decomposition are predicted through the long short-term memory neural network (LSTM), which is optimized by the improved particle swarm optimization (IPSO). Consequently, the predicting value of the final wind power was acquired by adopting the method of classified fusion to calculate the wind power components. Several case studies were carried out on the proposed model with the help of Python. It is found from those relevant results that the RMSE and MAE of the proposed model is 1.2382 and 0.8210, respectively. Moreover, the R2 is 0.9952. Those simulating results show that the proposed model may be better for fitting the actual curve of wind power and has excellent predicting accuracy.
Quasicrystals, aperiodicity and lattice systems

This thesis complements the paper Lattice gas models on self-similar aperiodic tilings in that it gives background information, motivation, new results, and proofs that had been omitted from. It can, however, be read independently from. The thesis is organised as follows. Chapter 1 discusses quasicrystals. Quasicrystals are a new form of matter; one that is ordered, yet not periodic. Their discovery has generated a lot of interest in aperiodic systems. Chapter 2 describes a class of tilings, in arbitrary dimension, that share an important property with the Penrose tilings: a certain kind of self-similarity. Chapter 3 discusses lattice systems on self-similar tilings. It introduces notation and summarizes the results of. It also discusses how lattice systems on the cubic lattice fit into the formalism. Chapter 4 is concerned with additive set functions. Such functions arise naturally when studying the existence of thermodynamic quantities, like the mean free energy. The mean free energy is the (spatial) mean of an additive set function. Chapter 5 discusses probability measures in lattice systems on the cubic lattice and relations between periodic probability measures and certain aperiodic probability measures. It shows that the mean entropy exists for 'almost-periodic' probability measures. Finally, Chapter 6 is devoted to 'unique Gibbs measures'.
Age-Related Differences in the Expression of Causal Relationships During Narrative Production of Croatian Children

A successful narration relies on the ability of an individual to express a coherent sequence of temporally and causally related events organised around a specific theme, and this skill typically develops in early preschool age. Narrative coherence can be assessed by sequences or elements of story grammar. According to the causal network model, story grammar is viewed as an interconnected network of causal relationships, including enabling, physical, motivational, and psychological relationships. The importance of causal coherence has been recognised in many studies dealing with narrative discourse from the developmentalperspective. However, previous studies have reported inconsistent results with respect to the use of different types of causal relationships in the narratives of children of different ages. In the present study, we aimed to examine the differences between preschool and school children in their ability to express causal relationships, both overall and specific, in the narratives that they produce. Participants were monolingual Croatian-speaking children with typical language development, who were stratified into two groups: preschool (n = 41, mean age = 6;3 years) and school children (n = 50, mean age = 8;4 years). Narratives were collected using the Multilingual Assessment Instrument for Narratives (MAIN), which was adapted to Croatian. The results show significant differences between the two groups of children in the overall proportion of causal relationships expressed, as well as specifically in the proportion of motivational relationships. There were no significant differences between the groups in production of enabling, physical, or psychological relationships. School children expressed more causal relationships overall than preschool children, as well as specifically more motivational relationships. As far as we know, this study is the first to investigate causality in the narratives of monolingual Croatian-speaking children using the causal network model. Our results only partially confirm the findings of previous studies, suggesting the need for further research to better understand the development of causal coherence in children’s narrative discourse.
Process Parameter Modeling and Optimization of Abrasive Water Jet Dressing Fixed-Abrasive Pad Based on Box–Behnken Design

Clarifying the influence of the dress process parameters of the abrasive water jet on the dressing effect of fixed-abrasive pads (FAPs) is a prerequisite for online controllable dressing of abrasive water jets. This paper uses three factors and three horizontal response surface methods to explore the influence of jet pressure, abrasive concentration, and nozzle angle on FAP dressing quality. The prediction model of the material removal rate of a FAP machined using three process parameters is established. The influence of pairwise interactions of the three process parameter variables on the dressing effect and the optimal process parameters under each target is analyzed. Finally, the optimal process parameters predicted by the model are verified by experiments. The results show that the best dressing parameters with the MRR of the workpiece as the response value are as follows: jet pressure 3.8 MPa, abrasive concentration 3%, and nozzle angle 73°. The predicted value of the optimal process performance is 464.574 nm/min, and the experimental verification result is 469.136 nm/min; the error between the experimental value and the predicted value is within a reasonable range.
Circulating saturated fatty acids and risk of gestational diabetes mellitus: A cross-sectional study and meta-analysis

Background Previous studies have analyzed the associations between the circulating saturated fatty acids (SFAs) and gestational diabetes mellitus (GDM), but no consistent conclusions have been reached. The aim of this study was to evaluate whether plasma SFAs were in correlation with GDM risks in our in-house women cross-sectional study and to better define their associations on the clinical evidence available to date by a dose-response meta-analysis. Methods We carried out a cross-sectional study of 807 pregnant women in 2018–2019 (Shanghai, China). GDM was defined according to the criteria of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Gas chromatography was used to determine the plasma fatty acids (FAs) in the 24–28 gestational weeks. The SFAs levels of non-GDM and GDM participants were compared by Mann–Whitney test, and the association between SFAs and GDM was explored by multivariate logistic models. Further, the potential diagnostic value of plasma SFAs was evaluated using the method of receiver operating characteristic (ROC) analysis. For meta-analysis, five databases were systematically searched from inception to March 2022, and we included 25 relevant studies for calculating pooled standard mean differences (SMDs) and 95% CI to describe the differences in SFAs profiles between non-GDM and GDM women. Study-specific, multivariable-adjusted ORs and 95% CI were also pooled using a fixed-effect model or random-effects model according to the heterogeneity to evaluate the associations between circulating SFAs and GDM prevalence. Results In our cross-sectional study, we found plasma proportion of palmitic acid (C16:0) was positively associated (aOR: 1.10 per 1% increase; 95% CI: 1.04, 1.17), while plasma stearic acid (C18:0) (aOR: 0.76 per 1% increase; 95% CI: 0.66, 0.89), arachidic acid (C20:0) (aOR: 0.92 per 0.1% increase; 95% CI: 0.87, 0.97), behenic acid (C22:0) (aOR: 0.94 per 0.1% increase; 95% CI: 0.92, 0.97), and lignoceric acid (C24:0) (aOR: 0.94 per 0.1% increase; 95% CI: 0.92, 0.97) were inversely associated with GDM. The area under the receiver operative characteristic curve increased from 0.7503 (the basic diagnostic model) to 0.8178 (p = 0.002) after adding total very-long-chain SFAs (VLcSFAs). A meta-analysis from 25 studies showed the circulating levels of three individual SFAs of GDM women were different from those of normal pregnant women. The summarized ORs for GDM was 1.593 (95% CI: 1.125, 2.255, p = 0.009), 0.652 (95% CI: 0.472, 0.901, p = 0.010) and 0.613 (95% CI: 0.449, 0.838, p = 0.002), respectively, comparing the highest vs. lowest quantile of the concentrations of C16:0, C22:0, and C24:0. Conclusion Our results, combined with the findings from meta-analysis, showed that women with GDM had a particular circulating SFA profile, characterized by higher levels of palmitic acid, and lower levels of VLcSFAs. Alterations in the chain lengths of blood SFA profile were shown to be associated with the occurrence of GDM.
Comparative Investigation of the Chemiluminescent Properties of a Dibrominated Coelenterazine Analog

Chemi- and bioluminescence are remarkable light-emitting phenomena, in which thermal energy is converted into excitation energy due to a (bio)chemical reaction. Among a wide variety of chemi-/bioluminescent systems, one of the most well-known and studied systems is that of marine imidazopyrazinones, such as Coelenterazine and Cypridina luciferin. Due to the increasing usefulness of their chemi-/bioluminescent reactions in terms of imaging and sensing applications, among others, significant effort has been made over the years by researchers to develop new derivatives with enhanced properties. Herein, we report the synthesis and chemiluminescent characterization of a novel dibrominated Coelenterazine analog. This novel compound consistently showed superior luminescence, in terms of total light output and emission lifetime, to natural imidazopyrazinones and commercially available analogs in aprotic media, while being capable of yellow light emission. Finally, this new compound showed enhanced chemiluminescence in an aqueous solution when triggered by superoxide anion, showing potential to be used as a basis for optimized probes for reactive oxygen species. In conclusion, bromination of the imidazopyrazinone scaffold appears to be a suitable strategy for obtaining Coelenterazines with enhanced properties.
COMMENT: Convergence time and finite size effects in neural networks

The time needed for convergence to a stable state starting from an initial state having macroscopic overlap with a stored state is studied numerically for networks up to N=105 neurons. Although such systems are much larger than those traditionally used in studying neural networks, they are still too small to extract reliable information about the asymptotic behaviour of the convergence time.
Discrete Morse Complexes

We investigate properties of the set of discrete Morse functions on a simplicial complex as defined by Forman. It is not difficult to see that the pairings of discrete Morse functions of a finite simplicial complex again form a simplicial complex, the discrete Morse complex. It turns out that several known results from combinatorial topology and enumerative combinatorics, which previously seemed to be unrelated, can be re-interpreted in the setting of these discrete Morse complexes.
Challenges of caregivers providing care to children with disabilities at non-governmental organisations in Tshwane townships, South Africa

Background Caregivers of children with disabilities are vital stakeholders when it comes to safeguarding the health, well-being and overall survival of the children that they care for. Caregivers, however, face many challenging conditions that make it difficult for them to optimally fulfil their caregiving role. Understanding these challenges is crucial for developing empowerment programmes for caregivers, which will ensure that children with disabilities receive comprehensive, optimal care and that caregivers experience a good quality of life. Objectives The aim of this study was to explore and describe the experiences of caregivers providing care to children with disabilities at non-governmental organisations (NGOs) in townships of Tshwane, South Africa. Method This study followed an exploratory, descriptive and contextual research design within a qualitative methodology. The population in this study included caregivers who care for children with disabilities at NGOs (n = 10). Participants for the study were selected using the purposive sampling technique. Data were collected by conducting semistructured interviews with caregivers. Data were analysed according to the six phases of thematic analysis proposed by. Results The study revealed six themes that represent the challenges experienced by caregivers, namely (1) initial impressions, (2) rendering care, (3) stress, (4) lack of outside support, (5) coping and (6) poor community recognition. Conclusion Support from the Departments of Health and Social Development and other institutions providing community rehabilitation services to townships should be provided to caregivers in order to empower them with skills and knowledge to effectively address the challenges they face so that they can render optimal care to the children they care for. Contribution Results of this study could assist in ensuring improved recognition, resilience and supportive resources for caregivers in collaboration with community based rehabilitation stakeholders in the community that would ultimately lead to improved care for children with disabilities in townships within South Africa.
Diversity and species composition of ants at coffee agroforestry systems in East Java, Indonesia: Effect of habitat condition and landscape composition

Abstract. Muhammad FN, Rizali A, Rahardjo BT. 2022. Diversity and species composition of ants at coffee agroforestry systems in East Java, Indonesia: Effect of habitat condition and landscape composition. Biodiversitas 23: 3313-3321. Habitat condition and landscape composition are the main factors that shape biodiversity in agroecosystems. However, information on the effect of habitat conditions and landscape composition on biodiversity in agroforestry systems is lacking. Agroforestry systems possess habitats that are characterized by a high diversity of vegetation, that can support biodiversity both on the field or landscape scale. This research aimed to study the diversity and species composition of ants in coffee (Coffea spp.) agroforestry systems, and to investigate the effects of habitat conditions and landscape composition on ant communities. Field research was conducted in twelve coffee agroforestry systems in East Java, Indonesia. Ants were sampled with the fogging method for canopy ants and pitfall traps for ground-dwelling ants in 40 m x 30 m plots. In each location, habitat conditions aspects (such as cultural technique and tree age) were identified by interviews with farmers and vegetation observation. Meanwhile, landscape composition was characterized by ground checking and mapping the land-use type within a 500 m radius from plot centers. This research recorded 35 species and 4,622 individuals of ants from all coffee plantations. Dolichoderus thoracicus was the most dominant canopy ant, while Pheidole sp.2 was the most dominant ground-dwelling ant in all plantations. Based on the GLM analysis, different responses were found between canopy and ground-dwelling ants in relation to habitat conditions and landscape composition. Canopy and ground-dwelling ants were affected by habitat conditions (such as tree age and canopy cover). The species composition of ground-dwelling ants was also affected by habitat conditions. In conclusion, habitats in coffee plantations can affect ant communities with ground-dwelling ants being more sensitive than canopy ants. Meanwhile, landscape composition can affect the species richness of all ants and not affect each stratum (canopy and ground-dwelling ants).
Shedding light on the prompt high efficiency paradox - self consistent modeling of GRB afterglows

We examine GRBs with both Fermi-LAT and X-ray afterglow data. Assuming that the 100MeV (LAT) emission is radiation from cooled electrons accelerated by external shocks, we show that the kinetic energy of the blast wave estimated from the 100MeV flux is 50 times larger than the one estimated from the X-ray flux. This can be explained if either: i) electrons radiating at X-rays are significantly cooled by SSC (suppressing the synchrotron flux above the cooling frequency) or ii) if the X-ray emitting electrons, unlike those emitting at 100MeV energies, are in the slow cooling regime. In both cases the X-ray flux is no longer an immediate proxy of the blast wave kinetic energy. We model the LAT, X-ray and optical data and show that in general these possibilities are consistent with the data, and explain the apparent disagreement between X-ray and LAT observations. All possible solutions require weak magnetic fields: $10^{-6}< \epsilon_B < 10^{-3}$ (where $\epsilon_B$ is the fraction of shocked plasma energy in magnetic fields). Using the LAT emission as a proxy for the blast wave kinetic energy we find that the derived prompt efficiencies are of order 15%. This is considerably lower compared with previous estimates (87% and higher for the same bursts). This provides at least a partial solution to the "prompt high efficiency paradox".
A Lightweight CNN Model Based on GhostNet

The existing deep learning models have problems such as large weight parameters and slow inference speed of equipment. In practical applications such as fire detection, they often cannot be deployed on equipment with limited resources due to the huge amount of parameters and low efficiency. In response to this problem, this paper proposes a lightweight smoke detection model based on the convolutional attention mechanism module. The model is based on the YOLOv5 lightweight framework. The backbone network draws on the GhostNet design idea, replaces the CSP structure of the FPN and head layers with the GhostBottleNeck module, adds a convolutional attention mechanism module to the backbone network layer, and uses the CIoU loss function to improve the regression accuracy. Using YOLOv5s as the benchmark model, the parameter amount of the proposed lightweight neural network model is 2.75 M, and the floating-point calculation amount is 2.56 G, which is much lower than the parameter amount and calculation amount of the benchmark model. Tested on the public fire dataset, compared with the traditional deep learning algorithm, the model proposed in the paper has better detection performance and the detection speed is significantly better than the benchmark model. Tested under the unquantized simulator, the speed of the proposed model to detect a single picture is 60 ms, which can meet the requirements of real-time engineering applications.
Activated Protein C Ameliorates Tubular Mitochondrial Reactive Oxygen Species and Inflammation in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is an emerging pandemic, paralleling the worldwide increase in obesity and diabetes mellitus. DKD is now the most frequent cause of end-stage renal disease and is associated with an excessive risk of cardiovascular morbidity and mortality. DKD is a consequence of systemic endothelial dysfunction. The endothelial-dependent cytoprotective coagulation protease activated protein C (aPC) ameliorates glomerular damage in DKD, in part by reducing mitochondrial ROS generation in glomerular cells. Whether aPC reduces mitochondrial ROS generation in the tubular compartment remains unknown. Here, we conducted expression profiling of kidneys in diabetic mice (wild-type and mice with increased plasma levels of aPC, APChigh mice). The top induced pathways were related to metabolism and in particular to oxidoreductase activity. In tubular cells, aPC maintained the expression of genes related to the electron transport chain, PGC1-α expression, and mitochondrial mass. These effects were associated with reduced mitochondrial ROS generation. Likewise, NLRP3 inflammasome activation and sterile inflammation, which are known to be linked to excess ROS generation in DKD, were reduced in diabetic APChigh mice. Thus, aPC reduces mitochondrial ROS generation in tubular cells and dampens the associated renal sterile inflammation. These studies support approaches harnessing the cytoprotective effects of aPC in DKD.