Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Destination Branding and Tourism Security on Revisit Intention during Covid-19 in Uluwatu Temple, Bali, Indonesia

The condition of the COVID-19 pandemic has caused all destinations to experience a decline in visitors, so the government has created programs such as destination branding so that destination managers and tourism business actors can take many ways to survive. Three things will be a strategy to increase tourist visits after the Covid-19 pandemic at Uluwatu Temple as a main consideration for tourists who want to travel to tourist attractions. The three are health, hygiene and safety. Therefore, this study was conducted to determine the effect of destination branding and tourism safety on revisit intention. The hypothesis tested with a purposive random sampling technique with the total number of 250 respondents. The finding indicates visitor really pay attention to the influence of sustainability in the way they examine revisit intention. This study has six hypotheses and the results of all hypotheses support the intention to revisit and recommend.
Co-located and distributed antenna systems: deployment options for massive multiple-input–multiple-output

To evaluate the benefits of distributed arrays in massive multiple-input–multiple-output systems, the authors investigate the interaction between linear receivers (maximum ratio combining and zero forcing) and three deployments scenarios: (i) a massive co-located array at the cell centre; (ii) a massive array clustered at B discrete locations; and (iii) a massive distributed array with a uniform distribution of individual antennas. The authors also study the effect of propagation parameters, system size, correlation and channel estimation error. The authors demonstrate by analysis and simulation that in the absence of any system imperfections, a massive distributed array is preferable. An intermediate deployment such as a massive array clustered at a few discrete locations, can be more practical to implement and more robust to imperfect channel state information. The authors show an example with a 128 antenna deployment where four locations achieves one third of the gains due to a fully distributed array.
Hybrid Approach Using Deep Autoencoder and Machine Learning Techniques for Cyber-Attack Detection

The feature reduction from the vast amount of data collected from the Internet is challenging and labor-intensive. Data imbalance is another problem in decision-making analysis that leads to a biased model favoring classes with larger samples. This paper proposes a hybrid model using autoencoder and machine learning models. It deals with feature reduction and handles imbalance attack classes using SMOTE method to balance the dataset, and then AE is trained. The bottleneck code of AE is stacked with different classifiers on datasets such as NSL-KDD, UNSW-NB15 and BoT-IoT to evaluate the proposed method. The performance of the proposed approach shows improvement over attack detection without AE. The most noticeable change occurred for SVM on the NSL-KDD dataset that shows doubled improvement of accuracy. In the case of UNSW-NB15, the results vary and see an improvement for the LR model. The BoT-IoT dataset sees the lowest performance variation, i.e., 0%-6%.
The Mediating Role of the Gut Microbiota in the Physical Growth of Children

Gut microbiota succession overlaps with intensive growth in infancy and early childhood. The multitude of functions performed by intestinal microbes, including participation in metabolic, hormonal, and immune pathways, makes the gut bacterial community an important player in cross-talk between intestinal processes and growth. Long-term disturbances in the colonization pattern may affect the growth trajectory, resulting in stunting or wasting. In this review, we summarize the evidence on the mediating role of gut microbiota in the mechanisms controlling the growth of children.
State-of-Charge Estimation of Lithium-Ion Batteries Based on Fractional-Order Square-Root Unscented Kalman Filter

The accuracy of the state-of-charge (SOC) estimation of lithium batteries affects the battery life, driving performance, and the safety of electric vehicles. This paper presents a SOC estimation method based on the fractional-order square-root unscented Kalman filter (FSR-UKF). Firstly, a fractional second-order Resistor-Capacitance (RC) circuit model of the lithium battery is derived. The accuracy of the parameterized model is verified, revealing its superiority over integer-order standard descriptions. Then, the FSR-UKF algorithm is developed, combining the advantages of the square-root unscented Kalman filter and the fractional calculus. The effectiveness of the proposed algorithm is proven under a variety of operational conditions in the perspective of the root-mean-squared error, which is shown to be below 1.0%. In addition, several experiments illustrate the performance of the FSR-UKF.
Does it pay to work? Unpaid labour in the platform economy

is Professor at KU Leuven, Belgium. Agnieszka Piasna is Senior Researcher at the European Trade Union Institute (ETUI) in Brussels. Markieta Domecka is Post-doctoral Researcher at KU Leuven. Karol Muszyński is Post-doctoral Researcher at KU Leuven, and Lander Vermeerbergen is Assistant Professor at Radboud University Nijmegen in the Netherlands. Does it pay to work? Unpaid labour in the platform economy
The potential function of post-fledging dispersal behavior in first breeding territory selection for males of a migratory bird

Abstract One possible hypothesis for the function of post-fledging dispersal is to locate a suitable future breeding area. This post-fledging period may be particularly important in migratory species because they have a limited period to gather information prior to autumn migration, and in protandrous species, males must quickly acquire a territory after returning from spring migration to maximize their fitness. Here we use color-ring resightings to investigate how the post-fledging dispersal movements of the Cyprus wheatear Oenanthe cypriaca, a small migratory passerine, relate to their first breeding territory the following year when they return from migration. We found that males established first breeding territories that were significantly closer to their post-fledging location than to their natal sites or to post-fledging locations of other conspecifics, but these patterns were not apparent in females. Our findings suggest that familiarity with potential breeding sites may be important for juveniles of migratory species, particularly for the sex that acquires and advertises breeding territories. Exploratory dispersal prior to a migrant’s first autumn migration may contribute toward its breeding success the following year, further highlighting the importance of early seasonal breeding on fitness and population dynamics more generally.
Study of Injection Strategy for Diesel Start

Three different methods,such as constant fuel,smooth decrease fuel and step decrease fuel were studied in the paper for diesel start based on fuzzy PID(Proportion Integration Differentiation) idle control strategies.It was showed by test results that there will be incomplete combustion cycles with constant fuel and smooth decrease fuel strategies during start state,so emission of diesel was high.There were no misfire cycles during start with the strategy of step decrease fuel,therefore combustion processing and emission were better for start state.
Clouds of Spacecraft Debris Liberated by Hypervelocity Dust Impacts on Parker Solar Probe

Hypervelocity impacts on spacecraft surfaces produce a wide range of effects including transient plasma clouds, surface material ablation, and for some impacts, the liberation of spacecraft material as debris clouds. This study examines debris-producing impacts on the Parker Solar Probe spacecraft as it traverses the densest part of the zodiacal cloud: the inner heliosphere. Hypervelocity impacts by interplanetary dust grains on the spacecraft that produce debris clouds are identified and examined. Impact-generated plasma and debris strongly perturb the near-spacecraft environment, producing distinct signals on electric, magnetic, and imaging sensors, as well as anomolous behavior of the star tracker cameras used for attitude determination. From these data, the spatial distribution, mass, and velocity of impactors that produce debris clouds are estimated. Debris-cloud expansion velocity and debris fragment sizes are constrained by the observational data, and long-duration electric potential perturbations caused by debris clouds are reported, along with a hypothesis for their creation. Impact-generated plasma-cloud expansion velocities, as well as pickup acceleration by the solar wind and driven plasma waves are also measured. Together, these observations produce a comprehensive picture of near-spacecraft environmental perturbations in the aftermath of a hypervelocity impact.
Realization of Laser Range Finding Based on Phase

The authors introduce the basic principle of laser range finding technology based on phase, propound in detail the automatic digital measurement technique of phase difference and its errors, analyze the effect of single phase-picking precision, frequency drift and atmosphere refractive index, etc. on laser ranging errors and put forward some special improvement methods. The results of laser ranging realization show that adopting phase laser ranging can achieve the precision of ±(5 mm 4+5×10-6D).
Prediction of the compressive strength of self‐compacting concrete using artificial neural networks based on rheological parameters

Self‐compacting concrete (SCC) is a fluid concrete designed to flow freely through reinforcements in order to completely fill the formwork. The appearance of this type of concrete increases the need to precisely characterize its compressive strength as a function of their behavior during flow. This article summarizes the use of artificial neural networks for the modelization of compressive strength, at 28 days, of SCC based on rheological parameters found during empirical tests (slump flow diameter, H2/H1 ratio of L‐Box, and V‐Funnel flow time) and the values of plastic viscosity and the yield stress. The objective of this numerical and experimental study is to find an optimal model to modelize the compressive strength. Thus, the results obtained after training of several models are showed that the architecture of the optimum with two hidden layers model is 5‐50‐50‐1 with a Pearson's correlation R = 97.58%.
EGFR-Targeted Photodynamic Therapy

The epidermal growth factor receptor (EGFR) plays a pivotal role in the proliferation and metastatization of cancer cells. Aberrancies in the expression and activation of EGFR are hallmarks of many human malignancies. As such, EGFR-targeted therapies hold significant potential for the cure of cancers. In recent years, photodynamic therapy (PDT) has gained increased interest as a non-invasive cancer treatment. In PDT, a photosensitizer is excited by light to produce reactive oxygen species, resulting in local cytotoxicity. One of the critical aspects of PDT is to selectively transport enough photosensitizers to the tumors environment. Accordingly, an increasing number of strategies have been devised to foster EGFR-targeted PDT. Herein, we review the recent nanobiotechnological advancements that combine the promise of PDT with EGFR-targeted molecular cancer therapy. We recapitulate the chemistry of the sensitizers and their modes of action in PDT, and summarize the advantages and pitfalls of different targeting moieties, highlighting future perspectives for EGFR-targeted photodynamic treatment of cancer.
Neonatal Sepsis and Hemostasis

Neonatal sepsis is considered critical for a significant increase in neonatal morbidity and mortality among hospitalized neonates. Neonatal sepsis, in most cases, coexists with coagulopathy, which can prove to be life-threatening. Complex molecular and cellular systems are involved in the cross-talk between inflammation and hemostasis during sepsis. Disturbances in the regulating systems of the vascular endothelium, and platelet–endothelial and platelet–neutrophil interactions play a pivotal role in both inflammation and coagulation. This complex process is poorly understood in neonates. In addition to the developmental maturation of hemostasis and the immune response in neonatal sepsis, a cellular model of hemostasis during sepsis should be taken into account. This review focused on the molecular and cellular mechanisms underlying inflammation and hemostasis during neonatal sepsis, taking the developmental immune response and developmental hemostasis into account in order to provide future diagnostic approaches to be applied in everyday clinical settings. Regarding the diagnostic modalities, we briefly provide the limitations of the currently used conventional coagulation assays, focusing on viscoelastic tests and platelet flow cytometry.
Impact Factors of Travel Intention During the Toll Road Being Free on the Major Holidays

Based on the objective reality of the toll road being free on the major holidays,the research objects of this paper are the travelers who have their own private cars.This paper,by the method of empirical,researches the interaction among all impact factors.By using survey data collected from 261 travelers who have the experience traveled on the toll road being free on the major holidays,it builds a concept model based on the theory of planned behavior( TPB),and designs the measurement scale about travel attitude and intention.Through the research of this paper,on one hand,it is possible to expand basic research theory in the field in domestic,and on the other hand,it also reveals mechanism of action of the policy of free toll road to the travel intention.The results show that the perceived service quality,the positive utility have a positive impact on the traveler's travel attitude,and the negative utility has a negative impact on the traveler's travel attitude.The travel attitude,perceived behavioral control and subjective norm will affect travelers' travel intention.
Meta-Analysis as a Tool to Identify Candidate Genes Involved in the Fagus sylvatica L. Abiotic Stress Response

In this study, we aimed to evaluate whether candidate genes for abiotic stresses in Fagus sylvatica L. are also candidate genes for herbaceous plants, with the purpose of better defining the abiotic stress response model of F. sylvatica. Therefore, a meta-analysis was performed on published papers related to abiotic stress. Firstly, we carried out a systematic review regarding the activity of 24 candidate genes selected for F. sylvatica under abiotic stress reported in 503 articles. After choosing the inclusion criteria, 73 articles out of 503, regarding 12 candidate genes, were included in this analysis. We performed an exploratory meta-analysis based on the random-effect model and the combined effect-size approach (Cohen’s d). The results obtained through Forest and Funnel plots indicate that the candidate genes for F. sylvatica are considered to be candidate genes in other herbaceous species. These results allowed us to set up models of plants’ response to abiotic stresses implementing the stress models in forest species. The results of this study will serve to bridge knowledge gaps regarding the pathways of response to abiotic stresses in trees based on the meta-analysis. The study approach used could be extended to observe larger gene databases and different species.
Bronchial Carcinoids: From Molecular Background to Treatment Approach

Simple Summary Bronchial carcinoids (BCs) are uncommon and usually slow growing neuroendocrine epithelial malignancies that represent less than 2% of all lung cancers. Differences in the extent of molecular alterations between neuroendocrine carcinomas and BCs may underline the differences in the aggressiveness of these lesions. Moreover, although atypical BCs and typical BCs have similar set of mutations, some differential molecular and genetic alterations have been described between these two entities. A better understanding of the genetic and molecular background of BCs would allow a better selection of medical treatments in these patients. Regarding treatment, most BCs can be cured by surgery; however, inoperable tumors are mostly insensitive to chemotherapy and radiotherapy. In advanced BCs, the only drug that has a positive phase III clinical trial in BCs is everolimus. Somatostatin analogues constitute the gold standard for symptomatic relief. Peptide receptor radionuclide therapy has been associated with longer progression free. The efficacy of other treatments such as antiangiogenic agents and immunotherapy is still not established. Abstract A better understanding of the genetic and molecular background of bronchial carcinoids (BCs) would allow a better estimation of the risk of disease progression and the personalization of treatment in cases of advanced disease. Molecular studies confirmed that lungs neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs) are different entities; thus, no progression of NET to NEC is expected. In BCs, MEN1 gene mutations and deletions and decreased gene expression have been associated with a poor prognosis. ATRX mutation has also been linked to a shorter disease-specific survival. In terms of therapeutic targets, PI3K/AKT/mTOR pathway mutations have been described in 13% of typical carcinoids (TCs) and 39% of atypical carcinoids (ACs), representing a targetable mutation with kinase inhibitors. Regarding treatment, surgical resection is usually curative in localized BCs and adjuvant treatment is not routinely recommended. Multiple options for systemic therapy exist for patients with advanced BCs, although limited by a heterogeneity in the scientific evidence behind their use recommendation. These options include somatostatin analogues, everolimus, peptide receptor radionuclide therapy, chemotherapy, radiotherapy, antiangiogenic agents, and immunotherapy. In this article, we provide a comprehensive review about the molecular and genetic background of BCs, and about the treatment of local and metastatic disease, as well as the main paraneoplastic syndromes that have been associated with this tumor.
GRAMMAR PARSER-BASED SOLUTION FOR THE DESCRIPTION OF THE COMPUTATIONAL GRAPH FOR THE GNA FRAMEWORK

The data flow paradigm has established itself as a powerful approach to machine learning. In fact, it isalso very powerful for computational physics, although it is not used as much in the field. One of thecomplications is that physical models are much less homogeneous compared to ML, which makestheir description a complicated task. In this paper we present a syntax analyzer for the GNAframework. The framework is designed to build mathematical models as lazy evaluated directedacyclic graphs. The syntax analyzer introduces a way for a concise description and configuration ofthe models using math-like syntax, providing scalability and branching. The goal of the project is todevelop a technique and a software to facilitate a generic analysis and input data descriptioncompatible with multiple backends, e.g. GNA.
Hyperspectral imaging for in-vivo/ex-vivo tissue analysis of human brain cancer

Accurate identification of tumor boundaries during brain cancer surgery determines the quality of life of the patient. Different intraoperative guidance tools are currently employed during the resection tumor but having several limitations. Hyperspectral imaging (HSI) is arising as a label-free and non-ionizing technique that could assist neurosurgeons during surgical procedures. In this paper, an analysis between in-vivo and ex-vivo human brain tumor samples using HSI has been performed to evaluate the correlation between both types of samples. Spectral ratios of the oxygenated and deoxygenated hemoglobin were employed to distinguish between normal tissue, tumor tissue and blood vessels. A database composed by seven in-vivo and fourteen ex-vivo hyperspectral images obtained from seven different patients diagnosed with glioblastoma Grade IV, metastatic secondary breast cancer, meningioma Grade I and II, and astrocytoma (glioma) Grade II. 44,964 pixels labeled pixels were employed in this work. The proposed method achieved discrimination between different tissue types using the proposed spectral ratio. Comparison between in-vivo and ex-vivo samples indicated that ex-vivo samples generate higher hemoglobin ratios. Moreover, vascular enhanced maps were generated using the spectral ratio, targeting real-time intraoperative surgical assistance.
Challenges in Physical Layer Security for Visible Light Communication Systems

This article highlights challenges associated with securing visible light communication (VLC) systems by using physical layer security (PLS) techniques. Motivated by the achievements in PLS studies for radio frequency (RF) communication, many PLS techniques for VLC systems were also rigorously investigated by tailoring the RF techniques to the VLC environment. However, careful consideration of the inherent differences between RF and VLC systems is still needed. By disregarding these differences, an eavesdropper could be given an opportunity to wiretap the VLC systems, even when PLS techniques are employed to protect them. Crucially, the fact that it is often not possible to know the number and locations of eavesdroppers in real VLC systems may allow eavesdroppers to devise various cooperative eavesdropping methods. By examining a few examples of the possible eavesdropper threats that can occur in VLC systems, this article offers novel insights into the vulnerabilities of state-of-the-art PLS schemes for VLC systems. Although the focus of the paper is mostly on these weaknesses, some potential solutions are also briefly proposed with a view to stimulating discourse in the community.
Hyaluronic Acid/Collagenase Ointment in the Treatment of Chronic Hard-to-Heal Wounds: An Observational and Retrospective Study

Background: Wound bed preparation is an important concept in clinical practice and is related to adequate debridement. The use of proteolytic enzymes is an established method of enzymatic wound debridement, especially in hard-to-heal ulcers that are unresponsive to normal healing procedures and progress. The TIME framework (tissue, inflammation/infection, moisture balance, and edge of wound) offers an appropriate strategy to eliminate resistance to healing, as well as maximizing the healing process. Maintenance debridement, as opposed to sporadic debridement, may be proposed in preserving an adequate wound bed towards complete recovery. Collagenase has been effective in debridement due to its ability to degrade collagen and elastin. In this clinical context, collagenase taken from Vibrio alginolitycus is the most favorably expressed enzymatic debriding agent. Methods: This retrospective observational study evaluates the efficacy of an ointment based on hyaluronic acid and collagenase (Bionect Start®), considering a reduced healing time and greater healing quality. We included 70 patients with chronic wounds of different etiologies, including diabetes mellitus (20), post-traumatic ulcers (35), chronic burns of degrees I and II (10), and pressure ulcers (5). We analyzed wound characteristics using the wound bed score (WBS) concept, healing time, as well as operator and patient satisfaction. Results: Frequency of debridement efficacy in terms of wound bed cleansing varied from 26% after 2 weeks to 93% after 4 weeks. We observed complete healing in 62 patients within an eight-week period. The overall operator and patient satisfaction after 8 weeks were 100% and 90%, respectively. Moreover, all patients reported less pain. Conclusions: A combined action of hyaluronic acid and collagenase ointment demonstrated a reduction in healing time while improving healing quality, with a decrease in pain.