Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Tourism: An Alternative View on Cultural Intangible Heritage and Sustainability in Tavira, Portugal

The digitalization of cultural routes and virtual storytelling has emerged as a way of showcasing to individuals the heritage of different cultural universes. Regarding this fractional environment, and as a by-product of the international EU funded iHERITAGE project, (B_A.2.1_0056), the goal is to create, through an innovation-driven growth process and technological transfer, brand strategies for the affirmation and better knowledge of intangible realities in the Mediterranean region. The Sicilian Tourism Department in Italy is the project’s lead beneficiary, with representative partners throughout six Mediterranean countries (Italy, Egypt, Spain, Jordan, Lebanon, Portugal). The case study in Portugal is being developed in Tavira, through the intangible cultural heritage of the Mediterranean diet. The research based on the cultural experience, the history of the landscape and the sense of identity and continuity of knowledge is reassigned into a digital platform—the creation of apps and, within this, the design of a virtual route that navigates key geographical places. These apps will later revolve around one of the cultural elements of the Mediterranean, namely, the olive oil activity, with a detailed presentation of the manufacturing process, as well as its didactic interpretation and dissemination about the protection and conservation of Mediterranean research. The methodological approach is developed through the analysis and interpretation of a detailed list of references, fieldwork in a plurality of sites, contextual inquiries and interviews. As a powerful tool for internet marketing and research, these apps will reinforce identity, hospitality and tourism enterprises connected through the virtual itinerary, allowing a closer interaction between tourists and locals, endorsing the rise of technological development, as well as to drastically reduce environmental and ecological risks.
Feasibility of Food FARMacia: Mobile Food Pantry to Reduce Household Food Insecurity in Pediatric Primary Care

Despite recommendations for systematic food insecurity screening in pediatric primary care, feasible interventions in clinical settings are lacking. The goal of this study was to examine reach, feasibility, and retention in Food FARMacia, a pilot clinically based food insecurity intervention among children aged <6 years. We examined electronic health record data to assess reach and performed a prospective, longitudinal study of families in Food FARMacia (May 2019 to January 2020) to examine attendance and retention. We used descriptive statistics and bivariate analyses to assess outcomes. Among 650 pediatric patients, 172 reported household food insecurity and 50 registered for Food FARMacia (child mean age 22 ± 18 months; 88% Hispanic/Latino). Demographic characteristics of Food FARMacia participants were similar to those of the target group. Median attendance rate was 75% (10 sessions) and retention in both the study and program was 68%. Older child age (retention: age 26.7 ± 18.7 months vs. attrition: age 12.1 ± 13.8 months, p = 0.01), Hispanic/Latino ethnicity (retention: 97% vs. attrition: 69%, p < 0.01), and larger household size (retention: 4.5 ± 1.1 vs. attrition: 3.7 ± 1.4, p = 0.04) correlated with retention. A clinically based mobile food pantry pilot program and study reached the target population and were feasible.
Deep Learning for Smart Healthcare—A Survey on Brain Tumor Detection from Medical Imaging

Advances in technology have been able to affect all aspects of human life. For example, the use of technology in medicine has made significant contributions to human society. In this article, we focus on technology assistance for one of the most common and deadly diseases to exist, which is brain tumors. Every year, many people die due to brain tumors; based on “braintumor” website estimation in the U.S., about 700,000 people have primary brain tumors, and about 85,000 people are added to this estimation every year. To solve this problem, artificial intelligence has come to the aid of medicine and humans. Magnetic resonance imaging (MRI) is the most common method to diagnose brain tumors. Additionally, MRI is commonly used in medical imaging and image processing to diagnose dissimilarity in different parts of the body. In this study, we conducted a comprehensive review on the existing efforts for applying different types of deep learning methods on the MRI data and determined the existing challenges in the domain followed by potential future directions. One of the branches of deep learning that has been very successful in processing medical images is CNN. Therefore, in this survey, various architectures of CNN were reviewed with a focus on the processing of medical images, especially brain MRI images.
On the benefits of point-to-multipoint coherent optics for multilayer capacity planning in ring networks with varying traffic profiles

Point-to-multipoint (P2MP) coherent optics using digital subcarrier multiplexing have recently been proposed as a promising new technology to reduce the cost and complexity of optical transport networks, particularly those in metro aggregation scenarios with hub-and-spoke (H&S) traffic patterns. In this paper, we perform a case study on fault tolerant ring networks with more general traffic profiles to assess the benefits of P2MP optics for alternative network scenarios such as those appearing in metro rings. We propose mixed integer linear programming formulations for multilayer capacity planning to minimize total transceiver costs, considering both point-to-point and P2MP transceivers, as well as a heuristic approach for the more complex P2MP case. Results indicate that P2MP optics can bring several advantages for all tested traffic profiles, ranging from pure uniform flows to mostly H&S. Transceiver cost savings are achieved in various cases, greater at higher network loads and for traffic patterns that are mostly H&S. Results also show that P2MP optics prompt a multilayer redesign of the network with significantly reduced spectrum usage and a reduced number of IP hops, resulting in lower optical–electronic–optical and IP processing latency and lower IP layer equipment costs for all traffic profiles.
Characteristics of lift and resistance of spherical wall in semi-unbounded flow field

The dynamic characteristics of the wall lift and drag of the rigid sphere moving parallel to the single wall surface in the static viscosity laminar flow field are numerically studied, on the basis of the three-dimensional numerical simulation method of the quasi-steady “relativity of motion. ” The results show that: (1) The wall surface acts to increase the drag; (2) On the near wall, the lift coefficient decreases as the Reynolds number between the sphere and the wall increase when Re < 100. However, when Re > 100, the lift coefficient increases sharply; (3) On the far wall, there is no wall effect when Re > 10, consistent with the unbounded flow, but the wall effect still exists when Re < 10; and (4) The particle rotation has few influences on drag but slightly increases the lift. And the lift induced by rotation is mainly determined by the surrounding fluid pressure. These results all contribute to the study of the hydrodynamic behavior of particles in the boundary and deepen the understanding of the phenomenon of particle transport in the wall effect layer.
Circulating Levels of Endotrophin Are Prognostic for Long-Term Mortality after AKI

Key Points In patients with AKI, endotrophin can predict long-term mortality and has a stronger association with mortality than eGFR. In patients with AKI, endotrophin can predict kidney disease progression at later time points and is superior to eGFR. Visual Abstract Background AKI involves a rapid decrease in kidney function that may be associated with structural damage. Early markers predicting AKI are emerging, but tools to assess patients’ long-term health risks after AKI are still lacking. Endotrophin (ETP) is a bioactive molecule released during the formation of collagen type VI. We evaluated the potential of circulating ETP as a prognostic biomarker of adverse outcomes after AKI. Methods We measured ETP in plasma samples collected 1 year after an episode of AKI, using the PRO-C6 ELISA in 801 patients (393 patients with AKI and 408 controls) from the prospective AKI Risk in Derby (ARID) study (ISRCTN25405995), who were then followed until year 3. Kidney disease progression was defined as ≥25% decline in eGFR combined with a decline in CKD stage. Results ETP levels were significantly higher in the AKI group compared with controls (P<0.001). In the AKI group, ETP could discriminate patients with kidney disease progression at year 3 (AUC=0.67, P<0.01), whereas eGFR could not (AUC=0.51, P=0.57). In logistic regression including common risk factors, ETP was independently associated with kidney disease progression in patients with AKI (OR=1.10, P<0.01). ETP could discriminate survivors from nonsurvivors at year 3 (AUC=0.64, P<0.01). In a Cox proportional hazards regression for mortality after AKI that included common risk factors, only ETP (HR=1.05; P<0.001) and age (HR=1.06, P<0.01) were retained in the final model. Conclusions Patients in the AKI group had higher levels of plasma ETP at year 1 as compared with those who had not had AKI. In the AKI group, ETP levels predict kidney disease progression and mortality. Because ETP is a profibrotic molecule, our findings may indicate that ETP identifies patients with active fibrogenesis after AKI, suggestive of long-term renal remodeling, which is associated with patient outcome.
MABASR - A Robust Wireless Interface Selection Policy for Heterogeneous Vehicular Networks

Connectivity is rapidly becoming a core feature of modern vehicles to enable the provision of intelligent services that promote safer transport networks, real-time traffic infotainment systems and remote asset monitoring. As such, a reliable communications back-bone is required to connect vehicles that deliver real-time data to smart services deployed at cloud or edge architecture tiers. Hence, reliable uplink connectivity becomes a necessity. Next-generation vehicles will be equipped with multiple wireless interfaces, and require robust mechanisms for reliable and efficient management of such communication interfaces. In this context, the contribution of this article is a learning based approach for interface selection known as the Multi-Armed Bandit Adaptive Similarity-based Regressor (MABASR). MABASR takes advantage of the underlying linear relationship between channel quality parameters and uplink data rate to realise a robust interface selection policy. It is shown how this approach outperforms algorithms developed in prior work, achieving up to two orders of magnitude lower standard deviation of the obtained reward when trained on different data sets. Thus, higher reliability and less dependency on the structure of the training data are achieved. The approach is tested in mobile, static, and artificial static scenarios where severe network congestion is simulated. All data sets used for the evaluation are made publicly available.
Diversity techniques in communications receivers

This chapter discusses the radiowaves that arrive in communication receivers. In all except very simple transmission conditions, radio communication links are subjected to conditions in which energy can travel from the transmitter to the receiver via more than one path. This "multipath" situation arises in different ways depending upon the application, for example in MF and HF skywave transmissions it arises because of reflections from two or more ionospheric layers, or from two-hop propagation. In mobile radio, it arises because of reflection and scattering from buildings, trees and other obstacles along the path.
DESIGN OF A LINEAR AND W IDE RANGE CURRENT STARVED VOLTAGE CONTROLLED OSCILLATOR FOR PLL

This paper focuses on design and analysis of Current Starved RingVoltage Controlled Oscillators (CSVCO) for PLL application. The CSVCO circuit is designed and simulated using GPDK 180nm CMOS Technology. The CSVCO has frequency range from 53 MHzto 2.348 GHz and power consumption is 848µW. The jitter is improved by connecting a D Flip Flop. In this design the maximum time jitter after D flip flop is 3.1ps and 1.5ps for rising and falling edgerespectively and output frequency is from 173MHz to 1.2GHz. The supply voltage V DD is 1.8V.
Metabolic Syndrome During Pregnancy: Prevalence and Determinants Among Pregnant Women Followed-Up at the Dschang District Hospital, West Region of Cameroon

Purpose Metabolic syndrome (MS) during pregnancy constitutes a serious threat to the mother and child health that will shortly become a major public health issue, especially in developing countries. However, in Cameroon, epidemiological data on MS during pregnancy are still scarce. The aim of this study was to determine the prevalence and determinants of MS among pregnant women followed-up at the Dschang District Hospital (DDH), in the west region of Cameroon. Patients and Methods This study was a hospital based cross-sectional study, carried out among pregnant women followed-up at the antenatal care unit of the DDH, from September 2019 to June 2020. Participants were assessed on sociodemographic, lifestyle parameters, and dietary habits using standardized and structured questionnaires. Anthropometric parameters, blood pressure, and biochemical markers were measured using standard procedures. Metabolic syndrome was diagnosed using the HNLBI/AHA definition, modified for pregnant women by Chatzi et al. A participant was recorded as having MS if presenting at least three of the following criteria: Pre-gestational BMI >30 kg/m2; triglycerides ≥150 mg/dl; HDL cholesterol <50 mg/dl; SBP ≥130/DBP ≥85 mm/Hg; and fasting blood glucose ≥100 mg/dl. Results Six hundred and four (604) pregnant women were included in the study. The prevalence of MS was 17.88% (95% CI: 15.03–21.14) and its most frequent individual components were low levels of HDL-cholesterol (66.23% (95% CI: 62.36–69.88)) and hypertriglyceridemia (28% (95% CI: 54.31–62.15)). Grand multiparous shows a higher risk of presenting MS (OR:3.06, 95% CI: 1.24–7.12; p = 0.011) compared to nulliparous. Pregestational BMI appears to be the best predictor of MS during pregnancy even after adjustment on age, parity, lifestyle and dietary habits (OR: 46.46, 95% CI: 15.58–138.49; p ˂ 0.0001). Conclusion The prevalence of MS on pregnant women in the Dschang health district is 17.88% (95% CI: 15.03–21.14) and its major determinant is pre-gestational obesity. This work provides quality preliminary data for the design and improvement of prevention strategies.
Wide-aperture deformable mirror for correcting and improving focusing of multi-petawatt Ti:Sa laser beam

A bimorph deformable mirror with a diameter of 320 mm, including 127 control electrodes, has been developed and investigated. The flatness of the initial surface of the mirror RMS = 0.16 μm was achieved due to mechanical adjustment in the system of fixing the mirror substrate in the frame. An adaptive system with deformable mirrors and a ShackHartmann-type wavefront sensor was installed in a 4.2 PW Ti: Sa laser. Correction of the wavefront made it possible to obtain a record radiation intensity in the focusing plane of 1.1x1023 W/cm2, while the Strehl ratio was 0.84.
Deep-Learning-Based Detection of Paroxysmal Supraventricular Tachycardia Using Sinus-Rhythm Electrocardiograms

Background: Paroxysmal supraventricular tachycardia (PSVT) is a common arrhythmia associated with palpitation and a decline in quality of life. However, it is undetectable with sinus-rhythmic ECGs when patients are not in the symptomatic onset stage. Methods: In the current study, a convolution neural network (CNN) was trained with normal-sinus-rhythm standard 12-lead electrocardiographs (ECGs) of negative control patients and PSVT patients to identify patients with unrecognized PSVT. PSVT refers to atrioventricular nodal reentry tachycardia or atrioventricular reentry tachycardia based on a concealed accessory pathway as confirmed by electrophysiological procedure. Negative control group data were obtained from 5107 patients with at least one normal sinus-rhythmic ECG without any palpitation symptoms. All ECGs were randomly allocated to the training, validation and testing datasets in a 7:1:2 ratio. Model performance was evaluated on the testing dataset through F1 score, overall accuracy, area under the curve, sensitivity, specificity and precision. Results: We retrospectively enrolled 407 sinus-rhythm ECGs of PSVT procedural patients and 1794 ECGs of control patients. A total of 2201 ECGs were randomly divided into training (n = 1541), validation (n = 220) and testing (n = 440) datasets. In the testing dataset, the CNN algorithm showed an overall accuracy of 95.5%, sensitivity of 90.2%, specificity of 96.6% and precision of 86.0%. Conclusion: Our study reveals that a well-trained CNN algorithm may be a rapid, effective, inexpensive and reliable method to contribute to the detection of PSVT.
Identifying Subjective Perspectives on Managing Underground Risks at Schiphol Airport

Recently, scholars have called for a focus on subjective aspects of risk management as a suitable lens for understanding how it functions. In line with this lens, this study focuses on project actors’ viewpoints on risk management in the context of construction projects to provide novel insights in risk management. Drawing on Renn's model and following a Q methodology, we identify four risk management approaches among asset managers and project managers working at the Dutch Schiphol Airport. The action-oriented and future-oriented viewpoints are dominant, while the expert input and stakeholder-centric viewpoints are in the minority. Our findings extend the risk management debate by showing that (1) there are various approaches to risk management that have been identified independently from the formal risk management; (2) these approaches cannot be explained by a project actor's role or objective within the project; and (3) that project actors have a dominant focus on managing complexity-induced risks at the expense of managing other types of risks.
The Plastome Sequences of Triticum sphaerococcum (ABD) and Triticum turgidum subsp. durum (AB) Exhibit Evolutionary Changes, Structural Characterization, Comparative Analysis, Phylogenomics and Time Divergence

The mechanism and course of Triticum plastome evolution is currently unknown; thus, it remains unclear how Triticum plastomes evolved during recent polyploidization. Here, we report the complete plastomes of two polyploid wheat species, Triticum sphaerococcum (AABBDD) and Triticum turgidum subsp. durum (AABB), and compare them with 19 available and complete Triticum plastomes to create the first map of genomic structural variation. Both T. sphaerococcum and T. turgidum subsp. durum plastomes were found to have a quadripartite structure, with plastome lengths of 134,531 bp and 134,015 bp, respectively. Furthermore, diploid (AA), tetraploid (AB, AG) and hexaploid (ABD, AGAm) Triticum species plastomes displayed a conserved gene content and commonly harbored an identical set of annotated unique genes. Overall, there was a positive correlation between the number of repeats and plastome size. In all plastomes, the number of tandem repeats was higher than the number of palindromic and forward repeats. We constructed a Triticum phylogeny based on the complete plastomes and 42 shared genes from 71 plastomes. We estimated the divergence of Hordeum vulgare from wheat around 11.04–11.9 million years ago (mya) using a well-resolved plastome tree. Similarly, Sitopsis species diverged 2.8–2.9 mya before Triticum urartu (AA) and Triticum monococcum (AA). Aegilops speltoides was shown to be the maternal donor of polyploid wheat genomes and diverged ~0.2–0.9 mya. The phylogeny and divergence time estimates presented here can act as a reference framework for future studies of Triticum evolution.
HCK is a Potential Prognostic Biomarker that Correlates with Immune Cell Infiltration in Acute Myeloid Leukemia

Background The tumor microenvironment (TME) plays a significant role in the progression and prognosis of acute myeloid leukemia (AML). This study is aimed at exploring TME-associated biomarkers and identify their potential mechanism in the microenvironment of AML. Method In this study, the stromal, immune, and ESTIMATE scores of AML patients were evaluated with the ESTIMATE and CIBERSORT algorithms; then, the AML samples were divided into high- and low-score groups. We evaluated the association between clinicopathological characteristics, survival rate, and the stromal/immune/ESTIMATE scores. Furthermore, we identified TME-associated differentially expressed genes (DEGs) then carried out pathway enrichment analysis, protein-protein interaction (PPI) network, Cox regression analysis, and Kaplan-Meier survival analysis to select the most crucial genes. In addition, we further explored the potential mechanism of HCK in the AML microenvironment. Results We identified 624 TME-associated DEGs and found that HCK was the most promising biomarker associated with AML. The results of the gene set enrichment analysis (GSEA) indicated that HCK was mainly involved in immune and inflammation-related signaling pathways. In addition, CIBERSORT analysis showed that HCK was closely related to tumor immune infiltration, with HCK expression associated with various infiltrating immune cells, including B cells, T cells, tumor-associated macrophages (TAM), NK cells, plasma cells, eosinophils, and neutrophils. Furthermore, HCK expression was closely related with ELN risk stratification in patients with AML. Conclusion HCK could regulate immune cell infiltration in the microenvironment of AML and may act as a potential biomarker for the treatment and prognosis of AML patients.